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This study explores consumers' perceptions of purchasing fast food items through online platforms. The central idea of this research is to practically assess the various elements impacting the consumers’ perceptions of online purchasing of fast food items and find out the factors with high importance and performance value.

A quantitative research approach was used to collect data from 402 participants in the form of a pen-and-paper-based method using a 5-point Likert scale. The collected data were analyzed using structural equation modeling (SEM) and importance-performance analysis. Theory of planned behavior and technology acceptance model form the basis for this research.

The findings indicate that constructs such as convenience, perceived quality and perceived healthiness positively influence consumers' perceptions of online purchasing of fast food items. On the other hand, competitive prices, discounts and promotions (CPDP) and online shopping experience have no significant impact on perceived value for money.

A constraint of this study is that it was done in a particular geographical location, which restricts the generalizations of the findings. The study only examined consumers' perceptions of online fast food purchasing, and future research could explore consumers' actual behaviors toward personalized fast food recommendations by online sellers.

The research supports and extends the existing literature by comprehensively understanding consumers' perceptions of purchasing fast food online. These findings can help online fast food sellers improve their services and develop targeted marketing strategies.

Three-dimensional (3D) printing has great potential in the food industry. While 3D printing technology offers customised food products to consumers, it also allows producers to develop new products using a wide variety of alternative food ingredients, modernise the production process and carry out environmentally friendly production. This research aims to determine the attitudes of students towards 3D foods who are studying in the Department of Gastronomy and Culinary Arts, as they are both consumers and examine different food processing systems and use them in the field of application. As a result of the study, it was identified that the participants believed that 3D printing is a great modern technology that allows the development of new foods, that it will bring benefit to us in the future, reduce the cost of food and food waste, increase the sustainability of food and that they see it as environmentally friendly. In addition, it was determined that the participants did not think that 3D-printed foods were disgusting; they found these foods reliable, could try them in the future and were excited to experience them.

Food safety is among the most important topics in the world. According to WHO guidelines, aflatoxins are one of the most hazardous food toxins. Therefore, their detection in food products seems crucial due to health problems. The purpose of this paper is to discuss the different types of biosensors in aflatoxin determination.

Traditional detection methods are time consuming and expensive. As fast and accurate detection is important in monitoring food contaminants, alternative analytical methods would be essential. Biosensors are the intelligent design of sensitive sensors for precise detection of toxins in a short time. Various biosensors are being applied for aflatoxins detection in food products with many advantages over the traditional methods.

Biosensors are cost-effective, stable and have possessed high selectivity, specificity and accuracy in aflatoxins detection. Applying biosensors has been increased recently, so biosensing methods (optical, electrochemical, piezoelectrical, immunosensors, surface plasmon resonance and calorimetric) are discussed along with their advantages in this article.

More efforts should be occurred to detect and decrease the aflatoxins by biosensors, and some traits like accuracy and selectivity would be the purpose of future projects. The combination of various techniques would also help in toxin detection issue in food products, so high efforts in this regard are also required for the upcoming years.

This article also reviews different types of biosensors simultaneously and explains their specificity for aflatoxin determination in different food products and also the future trends and requirements.

This study aims to examine the most influential drivers, both product-specific and consumer-specific, affecting Asian consumers' willingness to pay (WTP) for organic olive oil.

To individuate the most influential drivers of WTP for organic products and to assess their effect, in terms of configurational paths and consumer profiles, this study sequentially employs explorative factor analysis approach and a fuzzy-set qualitative comparative analysis method. The survey is carried out in different areas of Asia (e.g. Pakistan, Vietnam and China).

The results suggest that Asian consumers' WTP for organic products is described by consumer-specific drivers (gender, occupation and household size) as well as product-specific drivers (product authenticity and sustainability, consumer ethnocentrism and food fraud risk perception).

The findings of the study permit the identification of different drivers that move consumers' WTP for organic olive oil. The study contributes to setting the ground for companies to propose and implement efficacious marketing strategies for organic olive oil in importing countries, such as Asia.

In the reduction of food waste and the provision of food to the hungry, food banks play critical roles. However, as they are generally run by charitable organisations that are chronically short of human and other resources, their inbound logistics efforts commonly experience difficulties in two key areas: 1) how to organise stocks of donated food, and 2) how to assess the donated items quality and fitness for purpose. To address both these problems, the authors aimed to develop a novel artificial intelligence (AI)-based approach to food quality and warehousing management in food banks.

For diagnosing the quality of donated food items, the authors designed a convolutional neural network (CNN); and to ascertain how best to arrange such items within food banks' available space, reinforcement learning was used.

Testing of the proposed innovative CNN demonstrated its ability to provide consistent, accurate assessments of the quality of five species of donated fruit. The reinforcement-learning approach, as well as being capable of devising effective storage schemes for donated food, required fewer computational resources that some other approaches that have been proposed.

Viewed through the lens of expectation-confirmation theory, which the authors found useful as a framework for research of this kind, the proposed AI-based inbound-logistics techniques exceeded normal expectations and achieved positive disconfirmation.

As well as enabling machines to learn how inbound logistics are handed by human operators, this pioneering study showed that such machines could achieve excellent performance: i.e., that the consistency provided by AI operations could in future dramatically enhance such logistics' quality, in the specific case of food banks.

This paper’s AI-based inbound-logistics approach differs considerably from others, and was found able to effectively manage both food-quality assessments and food-storage decisions more rapidly than its counterparts.

This study aims to examine the motivations and supports of stakeholders in the slum communities, Ghana.

Two-stage methodologies were used for data collection. Published Google News articles about the phenomenon as well as exploratory qualitative in-depth interviews with 15 participants.

The evidence shows that structured and unstructured are the two main categories of stakeholders operating in the space of slums in Ghana. It shows that stakeholders are motivated by their objectives and ethical or moral obligations to provide support in the form of consumables, housing and finance to the slums.

Because of the data collection regime used in this project, findings are specific to the Ghanaian context and not generalisable. However, the results could be beneficial in other contexts with similar slum phenomena.

The conclusions drawn serve as a springboard for urban managers responsible for slum administration and management to develop policy packages to incentivise and enlist more non-slum stakeholders in the existing stakeholders.

To the best of the authors’ knowledge, this study is one of the few that expands the frontiers of the stakeholder model within context to discover specific slum stakeholders, their motivations and support for the slums in a consolidated manner.

The coronavirus disease (COVID-19) pandemic continues to impact economic systems, with devastating consequences on livelihoods. Anecdotal evidence has predicted the adverse effects of COVID-19 on the livelihood of food system actors. Uganda experienced two lockdowns in March 2020 and June 2021 with varying government containment measures. During the first lockdown, fresh food market vending was deemed essential to meet urban food demand, and was consequently exempted from a total shutdown despite the ban on public and private transport. Thus, this study sought to examine the effect of COVID-19 containment measures on fresh food market vending businesses in Uganda.

Using primary data collected from fresh food market vendors, this study applied a pooled time-series estimation to examine the effect of the first lockdown COVID-19 containment measures on fresh food vendors' welfare.

The study revealed that COVID-19 had a significant negative impact on the income of fresh food vendors, with female vendors being the most affected. COVID-19 containment measures reduced the diversity of buyers, individual customers and the number of commodities traded in causing a greater impact on vendors' income.

The unavailability of data for vendors who did not return to the market at the time of data collection limits the scope of the study. Additionally, the absence of data for the second lockdown limited the analysis to only March 2020 lockdown period.

The empirical analysis highlights how vulnerabilities of different gender categories could be exacerbated by crises. The study provides empirical evidence of various market distortions caused by the COVID-19 pandemic and the disproportionate impact on women and men market vendors which calls for the need to integrate women's perspectives in future planning for market systems as well as advocating for gender-sensitive recovery responses.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

The purpose of this study is to develop a new framework to measure waqif preference of waqf-based qardhul hassan financing in Malaysia.

Using a maqāṣid approach, this study’s data were drawn from 286 valid usable questionnaires to examine the effects of consumer, family, ummah and humanity factors on the preference.

The study found that the said factors sourced from Attia’s maqāṣid al-Shariah were instrumental in determining waqif preference to donate in waqf-based qardhul hassan financing.

Like others, this study’s findings are limited in terms of their generalisations and applications. The theory, context and variables used should be expanded in future works.

The results obtained are useful as a yardstick to enable the offered waqf-based qardhul hassan financing for improved mutual well-being among different classes of the wealth of societal groups in Malaysia. Furthermore, the results provide valuable insights into the direction for practitioners mainly managers involved in introducing waqf-based qardhul hassan financing as a new Islamic social financial instrument for poor and needy folks, at best.

This study is novel in terms of the proposed conceptual framework, where the waqif perspective comes into play.