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The study aims to investigate how attribution theory in the context of pricing strategies can help tourism destinations recover from the negative impacts of the COVID-19 pandemic.

The study adopted a qualitative research design using semi-structured interviews to address the lack of research in this area. Interview participants included tourists and tourism customers. The interview responses were then analyzed using “Nvivo” qualitative data analysis software to identify critical themes regarding applying attribution theory to pricing strategies.

The findings revealed that tourists prefer bundled and hedonic pricing strategies that integrate the service providers' pricing strategies' locus of control, stability and controllability. Tourists do not favor dual pricing strategies unless the reasons for price controllability or stability are justified. Tourists also prefer the controllable pay-what-you-want pricing strategy. Although tourists accept dynamic pricing, certain conditions related to price locus, stability and controllability must be met.

The research shows tourists prefer pricing strategies that give them control and flexibility, like bundled packages and pay-what-you-want models. Service providers should integrate pricing strategies that transparent costs and justify price fluctuations. While dynamic pricing is accepted if necessitated by external factors, tourists are wary of unnecessary price changes. Providers can build trust and satisfaction by explaining pricing rationale and offering controllable options like bundles.

The study contributes to the theory by applying attribution theory to the context of pricing strategies in tourism. It also provides innovative recommendations for tourism managers on how to use pricing strategies after the COVID-19 pandemic. The findings offer new insights that extend beyond previous research.

Hedonic shopping is a growing phenomenon designed to enhance gamers’ virtual content shopping experience with increasing economic significance, yet limited attention has been dedicated to this area. Our study explores key hedonic motivations of virtual content shopping and how hedonic shopping value builds trust (trust in virtual content and trust in virtual retailers) that enhances the intention to pay for premium.

This research adopts a mixed-methods approach. Study 1 is qualitative; 19 semi-structured interviews were conducted with virtual game retail platform users. Study 2, based on the literature review and qualitative inquiry findings (obtained from Study 1), proposes a research model empirically validated by analyzing survey data administered to 437 online gamers from gaming zones, cybercafés and e-sports centers.

The results show that in-game shopping-related adventure-, gratification-, role- and idea-seeking motivations significantly influence gamers' perceived hedonic shopping value. In turn, perceived shopping value has a significant indirect effect through trust on gamers’ intention to pay for premium.

This research contributes to gaming literature by offering a comprehensive model that elucidates the role of hedonic shopping in increasing gamers’ trust, which explains purchase behavior in the virtual game retail context. The findings deepen the understanding of the game retailing landscape and offer strategies to build gamers’ trust, increase premium usage and retain existing spenders.

Luxury consumption has evolved, and two important reasons behind the change include globalization and the COVID-19 crisis. These factors have led to the rise of new luxury consumption, which is different from traditional luxury consumption. This study examines how consumers’ identities shape their intentions to consume traditional luxury and new luxury brands.

The theoretical underpinnings of the schema congruity theory and heuristic systematic framework were applied to understand the role of identities in determining consumers’ regulatory focus, price luxuriousness inference and preference for traditional and new luxury brands.

Findings suggest that the global identity of consumers shapes their promotion focus and price luxuriousness inferences. However, their local identities induce a prevention goal. Consumers with such a goal are unlikely to make price luxuriousness inferences. Further, these inferences lead to the choice of traditional luxury over new luxury brands. The results also establish the moderating effects of consumer flexibility.

The extant literature is inconclusive on the role of globalization in luxury consumption and ignores new luxury brands. The current study shows the impact of identities and regulatory focus on traditional and new luxury consumption. The findings also indicate consumers’ regulatory focus and price luxuriousness inference as the reasons behind the influence. The paper also implies that consumers open to renting, sharing or buying second-hand goods will prefer new luxury over traditional luxury brands.

Drawing from stakeholder (ST) and social exchange theory (SET), the purpose of this study is to examine the relationship between customer perceived ethicality (CPE), electronic word of mouth (eWOM), customer trust (CT) and customer loyalty (CL). Furthermore, this study aimed to understand the dual role of CPE and eWOM in obtaining CT and achieving CL.

Using a quantitative, cross-sectional research design, data were collected from face-to-face surveys, yielding 358 responses. The partial least square algorithm was used to test the proposed hypothesis.

The analysis revealed that CPE and eWOM positively affect CT and CL, and CT has a mediating effect on the association between CPE–CL and eWOM–CL. CT was also found to positively affect CL.

Hotel managers can prioritize ethical practices and leverage the power of eWOM to build trust and achieve loyalty. This integrated approach not only enhances customer satisfaction and retention but also creates a competitive advantage.

The novelty of this study lies in the investigation of the dual role played by CPE and eWOM as antecedents of CT and CL within the hotel industry. Finally, this study explains the drivers of CT and CL, thereby making a novel contribution to the literature.

We are the first to investigate the relationship between seasoned equity offerings (SEOs) and anchoring on historical high prices in China.

We use the ratio of the recent closing price to its historical high in the previous 12–60 months (anchoring-high-price ratio) to study its impact on the market timing of SEOs.

Empirical results show that the anchoring-high-price ratio significantly and positively affects the probability of additional stock issuances. Contrary to the USA market, the Chinese stock market reacts negatively to the SEOs at historical highs. Moreover, the anchoring-high-price ratio exacerbates the negative effect of announcements and leads to long-term underperformance. Finally, we investigate the impact of the anchoring-high-price ratio on a company’s capital structure, showing that the additional issuance anchoring on historical highs reduces the company’s leverage ratio in the long run. Overall, our findings support the anchoring theory and can help understand better the anchoring behavior of managers and the company’s decision on additional stock issuances.

We are the first to use the anchoring-high-price ratio to study the timing of SEOs. We find that the anchoring-high-price ratio positively affects the probability of SEOs. Unlike the USA, the Chinese stock market reacts negatively to SEOs at high prices. SEOs anchoring on historical highs reduce a firm’s leverage ratio in the long run. Finally, our results support the anchoring theory.

This study aims to analyse the way the internal resources and their attributes contribute to the competitive advantages in an intensive organisation in knowledge of the pharmaceutical industry in an emerging market.

This is a qualitative case study focused where the NVivo software was used for information analysis and thematic analysis.

The outcomes showed that from the VRIO framework (value, rarity, imitability and organisation), the plant and equipment and the technical knowledge of its workers are the resources that, due to their attributes, especially the rare, those that grant an advantage competitive position compared to other companies in its sector. Those findings highlight that the resource-based view (RBV) is a good approximation to explain the construction of competitive advantage (CA) and, in addition, the relevance of rare attribute in pharmaceutical companies was confirmed.

The study points out empirical evidence on the relevancy of RBV, from the VRIO framework and the competitive profile matrix (CPM) for the analysis of the management of organisations from the emerging market (economy) perspective. The study also provides competitive advantage analysis tools with which managers can identify strategic resources for their companies.

The VRIO framework and CPM were integrated in the study to analyse the role of internal resources and their attributes in achieving CAs. This integration is the first time that it has been carried out in companies in the context of an emerging market.

This study aims to analyse the effect of competition on retail fuel prices in a small European Union (EU) country with high market concentration.

The researchers use a panel data set to estimate a fuel price equation that includes supply and demand factors as well as time-fixed effects.

The study finds that more competitors in the local market decrease prices, whereas the high market share of oligopoly brands does not condition this effect. Additionally, independent brands set lower prices than wholesalers, and gas stations located near the borders of almost all neighbouring countries are associated with higher prices.

The study suggests that Slovenia’s retail fuel market maintains competitive pricing despite high oligopolistic shares because of historical regulatory influences that shaped firm behaviour and pricing strategies, along with geographical and economic factors such as Slovenia’s role as a transit country. External competitive pressures from neighbouring countries and high levels of traffic, combined with the remnants of regulatory structures, help prevent market abuses and keep fuel prices lower than in other EU countries.

It also indicates that policy should encourage fiercer competition in the local market by increasing the density of gas stations, especially from independent brands.

These findings may be associated with specific country characteristics. This paper introduces unique findings that shed light on the impact of a small market on competition, with a particular focus on highlighting the effect of oligopolistic brands.

Short-term rentals (STRs) (like Airbnb) are reshaping social behaviour, notably in gastronomy, altering how people dine while travelling. This study delves into revenue management, examining the impact of seasonality and dining options near guests’ Airbnb. Machine Learning analysis of Airbnb data suggests owners enhance revenue strategies by adjusting prices seasonally, taking nearby food amenities into account.

This study analysed 220 Airbnb establishments from Madrid, Spain, using consistent monthly price data from Seetransparent and environment variables from MapInfo GIS. The Machine Learning algorithm calculated average prices, determined seasonal prices, applied factor analysis to categorise months and used cluster analysis to identify tourism-dwelling typologies with similar seasonal behaviour, considering nearby supermarkets/restaurants by factors such as proximity and availability of food options.

The findings reveal seasonal variations in three groups, using Machine Learning to improve revenue management: Group 1 has strong autumn-winter patterns and fewer restaurants; Group 2 shows higher spring seasonality, likely catering to tourists, and has more restaurants, while Group 3 has year-round stability, fewer supermarkets and active shops, potentially affecting local restaurant dynamics. Food establishments in these groups may need to adapt their strategies accordingly to capitalise on these seasonal trends.

Current literature lacks information on how seasonality, rental housing and proximity to amenities are interconnected. The originality of this study is to fill this gap by enhancing the STR price predictive model through a Machine Learning study. By examining seasonal trends, rental housing dynamics, and the proximity of supermarkets and restaurants to STR properties, the research enhances our understanding and predictions of STR price fluctuations, particularly in relation to the availability and demand for food options.

Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.

The authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.

The results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.

This study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.

Foreign subsidiaries of multinational enterprises (MNEs) operate in complex and competitive international environments, implement market and non-market strategies, manage resources and value-added activities and contribute to the overall performance of their parent firms. Thus, the research question on the determinants of MNE foreign subsidiaries’ performance is of interest to managers and academic researchers. The empirical literature has flourished over the recent decades; however, the domains are fragmented, and the findings are inclusive. The purpose of this study is to systematically review, analyse and synthesize the empirical articles in this area, identify research gaps and suggest a future research agenda.

This study uses the qualitative content analysis method in reviewing and analysing 150 articles published in 24 scholarly journals during the period 2000–2023.

The literature uses a variety of theoretical perspectives to examine the key determinants of subsidiary performance which can be grouped into six major domains, namely, home- and host country-level factors; distance between home and host countries; the characteristics of parent firms and of subsidiaries; and governance mechanisms (the establishment modes and ownership strategy, subsidiary autonomy and the use of home country expatriates for transferring knowledge from the headquarters and controlling foreign subsidiaries). A range of objective and subjective indicators are used to measure subsidiary performance. Yet, the research shows a lack of broader integration of theories and presents inconsistent theoretical predictions, inconclusive empirical findings and estimation bias, which hinder our understanding of how the determinants independently and jointly shape the performance of foreign subsidiaries.

This study provides a comprehensive, nuanced and systematic review that synthesizes and clarifies the determinants of subsidiary performance, offers deeper insights from both theoretical, methodological and empirical aspects and proposes some promising avenues for future research directions.