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Entrepreneurship policy is a vital component of any entrepreneurial ecosystem. However, the specific policy initiatives that have a greater impact on women's entrepreneurship remain unclear in many developing economies. Therefore, this study aims to evaluate the effectiveness of entrepreneurship policies targeted at women’s entrepreneurship in sub-Saharan Africa (SSA).

Employing fuzzy-set qualitative comparative analysis (fsQCA), this paper utilises and analyses secondary data collected by the World Bank's Women, Business, and the Law (WBL) from 1970 to 2020, encompassing 48 countries within SSA.

Through our analysis, we identified two configurations that sufficiently support women's entrepreneurship. First, a combination of gender-based policies focussing on enabling “access to credit” and “signing of contracts”; and second, a blend of policies supporting “signing of contracts”, “business registration”, and “opening a bank account”, represent significant antecedents to supporting women's entrepreneurship. These distinct pathways are crucial to fostering women’s entrepreneurship in the SSA region.

The study's findings indicate that the impact and effectiveness of entrepreneurship policies targeted at women entrepreneurs in developing economies depend on the effectiveness of other policies that are in place.

This study offers new insights into the intricate interrelationship between entrepreneurship policies and women’s entrepreneurship in developing countries by considering the interdependence and combinative value of gender-based policies that effectively support women’s entrepreneurship in sub-Saharan Africa.

The authors analyse six actively traded VIX Exchange Traded Products (ETPs) including 1x long, −1x inverse and 2x leveraged products. The authors assess their impact on the VIX Futures index benchmark.

Long-run causal relations between daily price movements in ETPs and futures are established, and the impact of rebalancing activity of leveraged and inverse ETPs evidenced through causal relations in the last 30 min of daily trading.

High frequency lead lag relations are observed, demonstrating opportunities for arbitrage, although these tend to be short-lived and only material in times of market dislocation.

The causal relations between VXX and VIX Futures are well established with leads and lags generally found to be short-lived and arbitrage relations holding. The authors go further to capture 1x long, −1x inverse as well as 2x leveraged ETNs and the corresponding ETFs, to give a broad representation across the ETP market. The authors establish causal relations between inverse and leveraged products where causal relations are not yet documented.

The impact of COVID-19 on tourism destinations has been severe, but a future crisis is never far away. How communities can better prepare for disasters to come in the near future continues to be researched. This research aims to understand the tourism community’s responses to the COVID-19 pandemic and present the Tourism Community Resilience Model as a useful instrument to help communities better respond to disasters in the future.

This research uses a qualitative research approach which seeks to understand phenomena, events, social activities, attitudes, beliefs, perceptions and individual and group opinions that are dynamic in character in accordance with the situation in the field. Research primary data is in the form of Kuta Traditional Village local community responses in enduring the COVID-19 pandemic conducted between January and May 2022. These data were obtained through in-depth observations and interviews involving informants based on purposive sampling, including traditional community leaders, village officials, tourism actors (i.e. street vendors, tourist local guides, taxi drivers and art workers) and tourism community members. We selected the informants who are not only directly impacted by the pandemic, but also some of them have to survive during the pandemic because they do not have other job options. The results of previous research and government data concerning the pandemic and community resilience were needed as secondary data, which were obtained through a study of the literature. The data which had been obtained were further analysed based on the Interpretative Phenomenological Analysis (IPA) technique, which seeks to make meaning of something from the participants’ perspective and the researchers’ perspective as a result there occurs a cognition of a central position.

Based on findings from Bali, Indonesia, this resilience model for the tourism community was created in response to the difficulties and fortitude shown by the community during the COVID-19 pandemic. It comprises four key elements, namely the Local Wisdom Foundation, Resource Management, Government Contributions and External Community Support. These elements are all rooted in the concepts of niskala (spirituality) and sekala (real response); it is these elements that give the tourism community in the Kuta Traditional Village a unique approach, which can inspire other tourism destinations in other countries around the world.

A tourism community resilience model based on local community responses has implications for the process of enriching academic research and community management practices in facing future crisis, particularly by involving local wisdom foundation.

A tourism community resilience model based on local community responses has implications for the process of enriching academic research and community management practices in facing future crisis, particularly by involving local wisdom foundation.

The existence of the resilience model strengthens local community social cohesion, which has been made stronger by the bonds of culture and shared faith in facing disaster. This social cohesion then stimulates the strength of sustainable and long-term community collaboration in the post-pandemic period. For tourism businesses, having strong connections with the local communities is an important condition to thrive.

The value of this research is the Tourism Resilience Community Model, which is a helpful tool to optimise and improve future strategies for dealing with disasters. Illustrated by this Balinese example, this paper emphasises the importance of adding social factors such as niskala and sekala to existing community resilience models. Addressing these local characteristics is the innovative aspect of this paper and will help inspire communities around the world to prepare for future disasters better and build more sustainable and resilient tourism destinations elsewhere.

The COVID-19 pandemic, a sudden and disruptive external shock to the USA and global economy, profoundly affected various operations. Thus, it becomes imperative to investigate the repercussions of this pandemic on the US housing market. This study investigates the impact of the COVID-19 pandemic on a crucial facet of the real estate market: the Time on the Market (TOM). Therefore, this study aims to ascertain the net effect of this unprecedented event after controlling for economic influences and real estate market variations.

Monthly time series data were collected for the period of January 2010 through December 2022 for statistical analysis. Given the temporal nature of the data, we conducted the Durbin–Watson test on the OLS residuals to ascertain the presence of autocorrelation. Subsequently, we used the generalized regression model to mitigate any identified issues of autocorrelation. However, it is important to note that the response variable derived from count data (specifically, the median number of months), which may not conform to the normality assumption associated with standard regression models. To better accommodate this, we opted to use Poisson regression as an alternative approach. Additionally, recognizing the possibility of overdispersion in the count data, we also explored the application of the negative binomial model as a means to address this concern, if present.

This study’s findings offer an insightful perspective on the housing market’s resilience in the face of COVID-19 external shock, aligning with previous research outcomes. Although TOM showed a decrease of around 10 days with standard regression and 27% with Poisson regression during the COVID-19 pandemic, it is noteworthy that this reduction lacked statistical significance in both models. As such, the impact of COVID-19 on TOM, and consequently on the housing market, appears less dramatic than initially anticipated.

This research deepens our understanding of the complex lead–lag relationships between key factors, ultimately facilitating an early indication of housing price movements. It extends the existing literature by scrutinizing the impact of the COVID-19 pandemic on the TOM. From a pragmatic viewpoint, this research carries valuable implications for real estate professionals and policymakers. It equips them with the tools to assess the prevailing conditions of the real estate market and to prepare for potential shifts in market dynamics. Specifically, both investors and policymakers are urged to remain vigilant in monitoring changes in the inventory of houses for sale. This vigilant approach can serve as an early warning system for upcoming market changes, helping stakeholders make well-informed decisions.

This case study provides in-depth, practical knowledge to develop business strategies for the management program. After reading this case study, the students will be able to learn about the challenges and problems that service firms face during a crisis, the drastic changes in the market environment due to a crisis and the analysis tools that can be used when analyzing the shifted market environment. By analyzing this case study, students will be trained for the decision-making that arises in the process of crisis management in the hotel industry.

Nam Nghi Resort, situated on the picturesque Phu Quoc Island in Vietnam, experienced the tumultuous period of the COVID-19 pandemic. Before the pandemic, Nam Nghi was a thriving five-star resort, deeply rooted in Vietnamese culture and renowned for its luxurious amenities and breathtaking location. However, the onset of COVID-19 brought unprecedented challenges to the hospitality industry, leading to a sharp decline in tourism and revenue. Despite the adversity, Nam Nghi implemented risk management practices successfully and displayed resilience and adaptability. Through rigorous cost minimization, strategic facility upgrades and targeted marketing efforts, Nam Nghi managed to navigate the crisis and gradually rebuild its business as travel restrictions eased. As the industry began to show signs of recovery, the general manager faced new challenges in restoring the resort’s prepandemic vitality. The challenge remained of understanding changing consumer values and market dynamics.

This case study can be used as class material for Master of Business Administration (MBA) students. In particular, MBA students in the hospitality industry such as hotels, resorts, travel agencies and restaurants are the target audience.

Teaching notes are available for educators only.

CSS 12: Tourism and hospitality.

This study aims to investigate the factors influencing the citrus trade in Indonesia, the effects of tariff and non-tariff policies on the industry and the welfare of producers and consumers.

The research used annual series data from 1991 to 2021 and employed inferential, simulation, and descriptive analyses. The two-stage least squares (2SLS) of 19 simultaneous equations were used to estimate parameters.

The results indicate that free trade policies and restrictions have influenced the citrus industry, leading to a reduction in Indonesian citrus imports, and increased consumer and producer prices. However, eliminating import tariff policies on citrus from China and import restrictions increased producer surplus while decreasing consumer surplus, government revenue, and total welfare. Therefore, trade policies should be combined with non-trade policies such as citrus region development policies and advancing cultivation technology.

This study provides empirical evidence for the Indonesian government to formulate effective citrus trade and development policies. It emphasizes the importance of carefully considering the impact of trade policy on the citrus industry and the need to implement non-trade policies such as citrus zone development policies and advancing cultivation technology to benefit both producers and consumers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0148

Contemporary focus on infections and deaths in the event of pandemics may distract health institutions and medical practitioners from the psychosocial consequences of the outbreak in individuals. In light of the devastation, persistency and scarcity of pandemics, it is imperative to delve into individuals' psychological state and self-preservation instincts when confronted with the environmental danger arising from pandemic conditions and the environmental restrictions being imposed.

Guided by the self-preservation theory, the authors advance a research model to elucidate the moderated mediation effect of secondary traumatic stress on an individual's reactions when faced with environmental danger and restriction. The authors also consider the moderating influence of environmental restriction and media use diversity. The authors subsequently validated the research model via a survey with 2,016 respondents in China. The authors employed PLS-SEM to analyze the data and assess the hypothesized paths.

Analytical results revealed that secondary traumatic stress fully mediated the impact of environmental danger on external reliance but suppresses the mediating effects on internal reliance. The authors further confirmed that environmental restriction moderated the relationship between environmental danger and reliance. Furthermore, the authors attest to the moderating influence of media use diversity on the relationship between secondary traumatic stress and external reliance.

This study not only extends the theoretical lens of self-preservation to public health emergencies but also yields practical guidelines for coping with pandemics. Insights from this study can be harnessed to aid populations worldwide in coping and recovering from pandemics.

Since 2008, bitcoin has continued to attract investors due to its growing capitalization and opportunity for speculation. The purpose of this paper is to analyze the impact of bitcoin (BTC) on gold, the volatility index (VIX) and the dollar index (USDX).

The series used are weekly and cover the period from January 2016 to November 2022. To generate the results, the unrestricted vector autoregression (VAR), structural vector autoregression (SVAR) and wavelet coherence were performed.

The findings are mixed as not all tests show the exact effects of BTC in the three asset classes. However, common to all the tests is the significant influence that BTC maintains on gold and vice versa. The positive shock in BTC significantly increases the gold prices, confirmed in three different tests. The effects on the VIX and USDX are still being determined, where in some tests, it appears to be influential while in others not.

BTC’s diversification potential with equity stocks and USDX makes it a valuable security for portfolio managers. Furthermore, regulatory authorities should consider that BTC is not an isolated phenomenon and can significantly influence other asset classes such as gold.

This chapter analyzes how the macro-environment determines corporate dividend decisions. First, political factors including political uncertainty, economic policy uncertainty, political corruption, and democracy may have two opposite effects on dividend decisions. For example, firms learn democratic practices to improve their corporate governance, but dividend policy may be the outcome of strong corporate governance or the substitute for poor corporate governance. Second, firms in countries of high national income, low inflation, and highly developed stock markets tend to pay more dividends. A monetary restriction (expansion) reduces (increases) dividend payments, as economic shocks like financial crises and the COVID-19 may negatively affect corporate dividend policy through higher external financial constraint, economic uncertainty, and agency costs. On the other hand, they may positively influence corporate dividend policy through agency costs of debt, shareholders' bird-in-hand motive, substitution of weak corporate governance, and signaling motive. Third, social factors including national culture, religion, and language affect dividend decisions since they govern both managers' and shareholders' views and behaviors. Fourth, firms tend to reduce their dividends when they face stronger pressure to reduce pollution, produce environment-friendly products, or follow a green policy. Finally, firms have high levels of dividends when shareholders are strongly protected by laws. However, firms tend to pay more dividends in countries of weak creditor rights since dividend payments are a substitute for poor legal protection of creditors. Furthermore, corporate dividend policy changes when tax laws change the comparative tax rates on dividends and capital gains.

The purpose of this paper is to investigate for symmetries – in sign and size – between spot and futures prices in the markets of energy commodities.

The aforementioned objective is pursued using daily observations of spot and futures prices for the commodities of crude oil, Brent, heating oil, gasoline and natural gas, along with local nonlinear regression.

Symmetry in sign and size cannot be rejected. This means that, shocks of the same absolute magnitude, but of different sign, are transmitted from futures prices to spot prices with the same intensity. In addition, larger absolute value price shocks in the futures are transmitted to the spot markets with the same intensity compared with smaller ones. The findings of symmetry in the comovements among prices reveal a lack of those commodities on diversifying the investors’ investment risk.

To the best of the authors’ knowledge, this is the first study to use local nonlinear regression to test for sign and size symmetry between futures and spot prices in the energy commodities markets.