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The purpose of this paper is to investigate specific marketing mix activities and influencing factors in hotels coping with falling room demand derived from drug cartel-related risk and insecurity.

A case study research was carried out using semistructured interviews with key informants (hotel managers) in two neighboring destinations at the US–Mexico border, an area where criminal organizations' drug trafficking-related violence has impacted the hospitality industry.

The research identifies factors that are internal (market segment diversification, type of ownership, magnitude of investments) and external (tourism promotion organizations, media coverage, tourist flow volume) to the firms as they affect their marketing mix implementation.

The research developed a framework to better understand the use of marketing mix practices and influencing factors in criminal insecurity contexts, which could be further studied in other risk and conflict scenarios.

The pricing and communication tactics are employed more intensively, while product-service and distribution channel actions are used to a lesser extent. Greater emphasis should be placed on product-service, distribution and market segment diversification.

Considering the positive impacts that tourism and hospitality businesses have on local communities, it is recommended that the hotel sector works together with government and industry associations to improve the safety and security at tourism destinations.

The research extends the extant knowledge in hospitality crisis management by investigating the full marketing mix tactics in hotels at destinations stricken by cartel-related organized crime, an understudied context in the literature.

After the COVID-19 outbreak began, travel demand dropped sharply and the potential impact of COVID-19 on sharing accommodations appears to be significant. Thus, it would be meaningful to investigate how travelers have changed their perceptions of staying at sharing accommodations in the wake of the coronavirus pandemic. The purpose of this research was to compare consumers' perceived risks of using sharing accommodations, such as Airbnb, before and during the coronavirus pandemic.

Paired sample t-tests were applied, using two surveys collected in 2017 (pre-pandemic) and 2020 (peri-pandemic). The effects of stress levels from COVID-19 and previous experience with sharing lodging services on risk perception changes were also examined.

Consumers showed higher social, physical, performance and convenience risk perceptions during the pandemic. Not surprisingly, those respondents who were more conscious of the pandemic in terms of concern and anxiety had higher changes in their risk perceptions. In addition, changes in risk perception differed by consumers' usage experience.

The results of this study add to the body of knowledge about consumers' risk perceptions of the sharing economy, particularly in connection with a huge disruption such as the COVID-19 pandemic.

The purpose of this paper is to investigate and identify the price sensitivity of consumers of three- and five-star hotels and to determine the impact of bundling strategies on consumers’ price sensitivity.

To calculate price sensitivity, authors apply the van Westendorp’s price sensitivity meter (PSM). To understand the impact of bundling strategies, univariate and bivariate techniques are applied.

PSM results reveal the optimal prices and the range of acceptable prices for three- and five-star hotel. The bundling strategy results reveal that five-star customers are less sensitive to mixed-leader bundling. Regarding mixed-joint bundling, managers could improve sales through bundling strategies if they selected an attractive service (e.g. restaurants).

Findings assist hotel managers to understand the different price sensitivities, according to the hotel typology. Managers can manage prices without the risk of losing market share or revenue. The results help managers in deciding which bundling strategies they can create, as well as the services to be included to achieve highest profitability.

No research to date to the best of the authors’ knowledge has attempted to understand and compare the role of bundling strategies in three- and five-stars hotels. Moreover, no research has attempted to measure and compare customers’ price sensitivity of three- and five-stars hotels.

This study evaluates the moderating role of work-based social supports (i.e. supervisor support and co-worker support) in the relationship between job insecurity and job burnout among hospitality employees in Malaysia. Besides, the direct effect between job insecurity and job burnout is examined.

The cross-sectional data of this study were based on a total of 220 self-administered questionnaires that have been completed by hospitality employees from three different states in Malaysia. Respondents were recruited based on a snowball sampling approach. The data were collected during the COVID-19 pandemic, which was from October 2020 to January 2021.

Partial least square-structural equation modeling (PLS-SEM) was performed via SmartPLS software. The finding confirmed that job insecurity significantly intensifies employees' job burnout. Supervisor support and co-worker support were found to moderate the link between job insecurity and burnout. As anticipated, the relationship between job insecurity and job burnout increased when supervisor support is low. But high co-worker support was found to strengthen the impact of job insecurity on job burnout instead of the reverse.

This study supplements the existing literature by clarifying which sources of work-based social support (i.e. co-worker support or supervisor) is more salient in alleviating the adverse impact of job insecurity on job burnout during the COVID-19 pandemic among hospitality employees in Malaysia.

Despite the abundance of small-scale farms in the USA and their importance for both rural economic development and food availability, the extensive research on small business management and entrepreneurship has mostly neglected the agricultural context, leaving many of these farms' business challenges unexplored. The authors focus on informing a specific decision faced by small farm managers: selling directly to consumers (i.e. farmer's markets) versus selling through aggregators. By collecting historical data and a series of interviews with industry experts, the authors employ simulation methodology to offer a framework that advises how small-scale farmers can allocate their product across these two channels to increase revenue in a given season. The results, which are relevant for operations management, small business management and entrepreneurship literature, can help small-scale farmers improve their performance and compete against their larger counterparts.

The authors rely on historical and interview data from key industry players (an aggregator and a small farm manager) to design a simulation analysis that determines which factors influence season-long farm revenue performance under varying strategies of channel allocation and commodity production.

The model suggests that farm managers should plan to evenly split their production between the two distribution channels, but if an even split is not possible, they should plan to keep a larger percentage in the nonaggregator (farmers' market/direct) channel. Further, the authors find that farmers can benefit significantly from a strong aggregator channel customer base, which suggests that farmers should promote and advertise the aggregator channel even if they only use it for a limited amount of their product.

The authors integrate small business management and operations management literature to study a widely understudied context and present practical implications for the performance of small-scale farms.

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

The purpose of this paper is to explain why the high quality cassava flour (HQCF) value chain in Nigeria has not performed as well as expected. The specific objectives are to: analyse important sources of uncertainty influencing HQCF value chains; explore stakeholders’ strategies to respond to uncertainty; and highlight the implications of different adaptation strategies for equity and the environment in the development of the value chain.

The authors used a conceptual framework based on complex adaptive systems to analyse the slow development of the value chain for HQCF in Nigeria, with a specific focus on how key stakeholders have adapted to uncertainty. The paper is based on information from secondary sources and grey literature. In particular, the authors have drawn heavily on project documents of the Cassava: Adding Value for Africa project (2008 to present), which is funded by the Bill & Melinda Gates Foundation, and on the authors’ experience with this project.

Policy changes; demand and supply of HQCF; availability and price of cassava roots; supply and cost of energy are major sources of uncertainty in the chain. Researchers and government have shaped the chain through technology development and policy initiatives. Farmers adapted by selling cassava to rival chains, while processors adapted by switching to rival cassava products, reducing energy costs and vertical integration. However, with uncertainties in HQCF supply, the milling industry has reserved the right to play. Vertical integration offers millers a potential solution to uncertainty in HQCF supply, but raises questions about social and environmental outcomes in the chain.

The use of the framework of complex adaptive systems helped to explain the development of the HQCF value chain in Nigeria. The authors identified sources of uncertainty that have been pivotal in restricting value chain development, including changes in policy environment, the demand for and supply of HQCF, the availability and price of cassava roots, and the availability and cost of energy for flour processing. Value chain actors have responded to these uncertainties in different ways. Analysing these responses in terms of adaptation provides useful insights into why the value chain for HQCF in Nigeria has been so slow to develop.

Recent developments suggest that the most effective strategy for the milling industry to reduce uncertainty in the HQCF value chain is through vertical integration, producing their own cassava roots and flour. This raises concerns about equity. Until now, it has been assumed that the development of the value chain for HQCF can combine both growth and equity objectives. The validity of this assumption now seems to be open to question. The extent to which these developments of HQCF value chains can combine economic growth, equity and environmental objectives, as set out in the sustainable development goals, is an open question.

The originality lies in the analysis of the development of HQCF value chains in Nigeria through the lens of complex adaptive systems, with a particular focus on uncertainty and adaptation. In order to explore adaptation, the authors employ Courtney et al.’s (1997) conceptualization of business strategy under conditions of uncertainty. They argue that organisations can assume three strategic postures in response to uncertainty and three types of actions to implement that strategy. This combination of frameworks provides a fresh means of understanding the importance of uncertainty and different actors’ strategies in the development of value chains in a developing country context.

The COVID-19 pandemic has resulted in significant changes in tourists’ attitudes and behaviors mostly as a result of confinement-related problems. Although various studies have been conducted to analyze customers’ perceptions of service quality and satisfaction using a drop-off/pick-up method, the influence of COVID-19 on customers’ perceptions of service quality and satisfaction has not been examined using online reviews. It is critical to evaluate satisfaction aspects from user-generated content to ascertain their preferences for hotel services during the pandemic. This research aims to explore the viewpoint shared online by hotel tourists, as well as identify which service practice is associated with higher and lower satisfaction during the COVID-19 pandemic.

This study integrates the theory of planned behaviour (TPB) and value-belief-norm (VBN) theory to investigate tourists' intention and behaviour to visit green hotels in Malaysia.

A total of 160 valid questionnaire responses were collected via an online survey. The partial least square–structural equation modelling (PLS-SEM) technique was utilised to assess the study framework and the hypothesised relationship.

The study's results confirmed that tourists' intention to stay at a green hotel is directly influenced by their subjective norms and perceived behavioural control. Besides, the study confirms the insignificant relationship between green trust, personal norms and tourists' stay intention. On the other hand, perceived morals, responsibility, willingness to pay more and perceived consumer effectiveness were significant in explaining the customer's subjective norms, personal norms and perceived behaviour control.

The hotel industry may benefit from this empirical outcome to devise effective marketing strategies for retaining their customers, particularly in rejuvenating the impact of the COVID-19 pandemic on the industry.

This study provides valuable practical implications for green hotel operators to develop effective strategies to attract tourists to green hotel visits.

This study is the first to integrate the extended TPB and VBN theory to understand tourist intention to visit a green hotel. Notably, the extended TPB and VBN theory was practical and helpful in predicting tourist intention to visit a green hotel.