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The COVID-19 pandemic was a shock to the food supply chain without modern precedent. Challenges in production, manufacturing, distribution and retailing led to the highest rates of food price inflation in the US since the 1970s. The major goal of this paper is to describe statistically the impact of the pandemic of food price inflation and volatility in the US and to discuss implications for industry and for policymakers.

We use Bureau of Labor Statistics data to investigate food prices in the US, 2020–2021. We apply 16 statistical approaches to measure price changes and volatility and three regression approaches to measure counterfactuals of food prices, had the pandemic not occurred.

Food price inflation and volatility increased substantially during the early months of the pandemic, with a great deal of heterogeneity across food products and geographic regions. Food price inflation was most pronounced for meats, and contrary to expectations, highest in the western US Forecasting approaches demonstrate that grocery prices were about 7% higher than they would have been without the pandemic as of the end of 2021.

The research on COVID-19 and the food system remains in its nascent stage. As findings on food loss and waste, employment and wages, food insecurity and more proliferate, it is vital to understand how food prices were connected to these phenomena and affected. We also motivate several ideas for future work.

In a supply-constrained region like Asia, promoting exports has always been a challenge particularly at a time when Asia’s trade has been severely affected by lack of external demand. This paper argues that price barriers have taken a new shape during the global financial crisis period which may generate differential impacts on trade flows as we proceed toward recovery. The size and shape of price barriers would be higher if NTBs, applied by the countries during the crisis period, were counted. One of the conclusions of this paper is that ‘price’ barrier is still more important than ‘non-price’ barrier in enhancing Asia’s trade and integration. The higher the price barrier between countries in a pair, the less they trade. In other words, a 10 percent increase in the ad-valorem price (transport and tariff) lowered trade by 6 percent. Tariff and transport costs, each considered separately, also influence the trade flow in the same direction, to more or less the same extent. There are indications of huge domestic infrastructure bottlenecks in countries in Asia. Based on direct and indirect evidence related to trade barriers, this paper concludes that complementary trade policies focusing on price and non-price barriers have immense importance in enhancing international trade and integration in the post-crisis period.

A stylized fact in finance literature is the belief in positive relationship between ex ante return and risk. Hence, a rational investor, by utility preference axiom can only consider committing fund in asset which promises commensurate higher return for higher risk. Questions have been asked as to whether this holds true across securities, sectors and markets. Empirical evidence appears less convincing, especially in developing markets. Accordingly, the author investigates the nature of reward for taking risk in the Nigerian Capital Market within the context of individual assets and markets.

The author employed ex post design to collect weekly stock prices of firms listed on the Premium Board of Nigerian Stock Exchange for period 2014–2022 to attempt to answer research questions. Data were analyzed using a unique M Vec TGarch-in-Mean model considered to be robust in handling many assets, and hence portfolio management.

The study found that idea of risk-expected return trade-off is perhaps more general than as depicted by traditional finance literature. The regression revealed that conditional variance and covariance risks reveal minimal or no differences in sign and sizes of coefficients. However, standard errors were also found to be large suggesting somewhat inconclusive evidence of existence of defined incentive structure for taking additional risk in the market.

In terms of choice of methodology and outcomes, this research adds substantial value to body of knowledge. The adapted multivariate model used in this paper is a rare approach especially for management of portfolios in developing markets. Remarkably, the research found empirical evidence that positive risk-expected return trade-off, as known in mainstream literature, is not supported especially using a typical developing country data.

In this research, the main purpose is to use a suitable structure to predict the trading signals of the stock market with high accuracy. For this purpose, two models for the analysis of technical adaptation were used in this study.

It can be seen that support vector machine (SVM) is used with particle swarm optimization (PSO) where PSO is used as a fast and accurate classification to search the problem-solving space and finally the results are compared with the neural network performance.

Based on the result, the authors can say that both new models are trustworthy in 6 days, however, SVM-PSO is better than basic research. The hit rate of SVM-PSO is 77.5%, but the hit rate of neural networks (basic research) is 74.2.

In this research, two approaches (raw-based and signal-based) have been developed to generate input data for the model: raw-based and signal-based. For comparison, the hit rate is considered the percentage of correct predictions for 16 days.

This current review examines the scientific literature report on non-timber forest products (NTFPs) commercialisation and forest conservation in different jurisdictions.

A systematic review using Scopus-indexed articles on NTFP commercialisation and forest conservation was done using the PRISMA framework.

The review categorised the factors influencing the commercialisation of NTFPs and forest conservation into five broad factors and sub-factors: socioeconomic, market-based, ecosystem, cultural and institutional factors. The scholarly publications on NTFP commercialisation and forest conservation have been undulating, with two years recording no publication on the subject matter under review. Besides, China and India in Asia are leading in the number of publications on NTFPs’ commercialisation. The review revealed ambivalence and symbiotic relationship among the factors influencing the commercialisation of NTFPs and forest conservation. Specifically, tenure arrangement, strict regulations to forest entry, market information asymmetry, bureaucracy in certification acquisition, seasonality and distance were identified as barriers to NTFPs’ commercialisation. While market demands for NTFPs increased, NTFPs’ prices and unsustainable harvesting activities were threats to forest conservation. Policymakers should focus on safeguarding customary property rights and indigenous knowledge in forest conservation, designing workable capacity-building schemes for NTFP entrepreneurs and reducing the cost and processes in certification acquisition.

There are reviews on NTFPs’ commercialisation and livelihoods, but a synergy between NTFPs’ commercialisation and forest conservation for forest policy direction is yet to be done in the literature. Also, while earlier studies systematically reviewed literature on NTFPs’ commercialisation, they did not relate the studies to forest conservation.

This paper examines how the macroeconomic environment affects the determinants of prepayment of mortgage loans from October 2004 to February 2020. For more accurate analysis, the authors define the timing of prepayment not only before the loan maturity but also at the time when 50% or more of the loan principal is repaid. The results show that, during the global financial crisis as well as the recent period of low interest rates, macroeconomic variables such as interest rate spreads and housing prices have a different effect compared to the normal situation. Also, significant explanatory variables, such as debt to income (DTI) ratio, loan amount ratio and poor credit score, have different effects depending on the macroenvironment. On the other hand, in all periods, the possibility of prepayment increases as comprehensive loan to value (CLTV) increases, and the younger the age, the shorter the loan maturity. The results suggest that, in the case of ultralong (40 years) mortgage loans recently introduced to support young people purchasing houses, the prepayment risk can be, at least partially, migrated by offsetting the increase in prepayment by young people and the decrease in prepayment due to long loan maturity. In addition, this study confirms that the accelerated time failure model compared to the logit model and COX proportional risk model has the potential to be more appropriate as a prepayment model for individual borrower analysis in terms of the explanatory power.

Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study aims to apply the signaling theory to the booking of Airbnb listings and explore the influence of quality signals on the odds of an Airbnb listing being booked.

A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt.

Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments.

This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.

This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market.

The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region.

The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values.

The robustness of the models would be enhanced by the addition of further spatial levels and larger data sets.

The methods introduced in this study can be used by real estate agents, valuers and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments.

The application of these methods is intended to inform a fairer approach to setting insurance premiums and a better basis for determining policy interventions and public investment designed to mitigate potential earthquake risk.

The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach.

The purpose of this paper is to present the findings of research on mothers and midwives’ understanding of the concept of respectful care in the Ugandan public health settings. It focusses on one aspect of respect; namely communication that is perhaps least resource-dependent. The research found endemic levels of disrespect and tries to understand the reasons behind these organisational cultures and the role that governance could play in improving respect.

The study involved a combination of in-depth qualitative interviews with mothers and midwives together with focus groups with a cohort of midwives registered for a degree.

The findings highlight an alarming level of verbal abuse and poor communication that both deter women from attending public health facilities and, when they have to attend, reduces their willingness to disclose information about their health status. Respect is a major factor reducing the engagement of those women unable to afford private care, with health facilities in Uganda.

Access to quality care provided by skilled birth attendants (midwives) is known to be the major factor preventing improvements in maternal mortality and morbidity in low income settings. Although communication lies at the agency end of the structure-agency continuum, important aspects of governance contribute to high levels of disrespect.

Whilst there is a lot of research on the concept of respectful care in high income settings applying this to the care environment in low resource settings is highly problematic. The findings presented here generate a more contextualised analysis generating important new insights which we hope will improve the quality of care in Uganda health facilities.

South Africa is the leading market for luxury goods in Africa – a fact evident from the statistics on luxury retail and the expanding footprint of international and local luxury brands. In a market that is dominated by prominent international brands, indigenous South African brands are seldom the subject of empirical research. This study addresses this gap by analysing the consumer-based brand equity (CBBE) of South African luxury fashion brands and its outcomes on the purchase/repurchase intention of consumers of South African luxury fashion brands.

The study adopted quantitative research methods and utilized survey questionnaires to acquire data from 130 respondents. Structural equation modelling was used in testing the proposed alternative hypotheses.

The study affirmed the relevance of Aaker's (1991) CBBE model for luxury goods in the emerging economy of South Africa. It established perceived quality and behavioural loyalty as significant predictors of brand equity while affirming the prevalence of hedonism and behavioural loyalty in South Africa's luxury fashion market.

The small sample size and the limited geographic scope of the study had a significant adverse impact on the broad application of the study's outcome. Furthermore, Aaker's (1991) CBBE model, while adequate, may have diminished the probability of a nuanced outcome.

This study advances the frontiers of interdisciplinary research by applying the marketing framework of CBBE to fashion studies in South Africa. The validated measurement scale, which emphasises the relevance of hedonism and behavioural loyalty in South Africa, may be useful for a similar study on luxury fashion brands in other emerging economies.