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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.

Nature and occurrence of food-borne pathogens in raw and processed food products evolved greatly in the past few years due to new modes of transmission and resistance build-up against sundry micro-/macro-environmental conditions. Assurance of food health and safety thus gained immense importance, for which bio-sensing technology proved very promising in the detection and quantification of food-borne pathogens. Considering the importance, different studies have been performed, and different biosensors have been developed. This study aims to summarize the different biosensors used for the deduction of food-borne pathogens.

The present review highlights different biosensors developed apropos to food matrices, factors governing their selection, their potential and applicability. The paper discusses some related key challenges and constraints and also focuses on the needs and future research prospects in this field.

The shift in consumers’ and industries’ perceptions directed the further approach to achieve portable, user and environmental friendly biosensing techniques. Despite of these developments, it was still observed that the comparison among the different biosensors and their categories proved tedious on a single platform; since the food matrices tested, pathogen detected or diagnosed, time of detection, etc., varied greatly and very few products have been commercially launched. Conclusively, a challenge lies in front of food scientists and researchers to maintain pace and develop techniques for efficiently catering to the needs of the food industry.

Biosensors deduction limit varied with the food matrix, type of organism, material of biosensors’ surface, etc. The food matrix itself consists of complex substances, and various types of food are available in nature. Considering the diversity of food there is a need to develop a universal biosensor that can be used for all the food matrices for a pathogen. Further research is needed to develop a pathogen-specific biosensor that can be used for all the food products that may have accuracy to eliminate the traditional method of deduction.

The present paper summarized and categorized the different types of biosensors developed for food-borne pathogens.

The purpose of this study is to analyze the technological change under development linked to the convergence of the Internet of Things (IoT) and digital transformation (DT) from the perspective of a scientific mapping in a context marked by the occurrence of an unexpected event that accelerated this process such as the SARS-CoV-2 pandemic and its variants.

The study was developed under the longitudinal scientific mapping approach and considered the period 1990–2021 using as a basis the descriptors DT and IoT. The steps followed were identification and selection of keywords; design and application of an algorithm to identify these selected keywords in titles, abstracts and keywords using terms in Web of Science (WoS) to contrast them; and performing a data processing based on the journals in the Journal Citation Report during 2022. The longitudinal study uses scientific mapping to analyze the evolution of the scientific literature that seeks to understand the acceleration in the integration of technology and its impact on the human factor, processes and organizational culture.

This study showed that the technologies converging around IoT form the basis of the main DT processes being experienced on a global scale; furthermore, it was shown that the pandemic accelerated the convergence and application of new technologies to support the major changes required for a world with new needs. Finally, China and the USA differ significantly in the production of scientific knowledge with respect to the first eight followers.

The knowledge gap addressed by this study is to identify the production of scientific knowledge related to IoT and its impact on DT processes at the scale of individuals, organizations and the new way of delivering value to society. This knowledge about researchers, institutions, countries and the derivation is multiple indicators allows improving decision-making at multiple scales on these issues.

This paper aims to apply the novel numerical model to analyze the effect of pillar material on the response of compound quartz crystal resonator (QCR) with an array of pillars. The performance of the proposed device compared to conventional QCR method was also investigated.

A finite element method model was developed to analyze the behavior of QCR coupled with an array of pillars. The model was composed of an elastic pillar, a solution and a perfectly matched layer. The validation of the model was performed through a comparison between its predictions and previous experimental measurements. Notably, a good agreement was observed between the predicted results and the experimental data.

The effect of pillar Young’s modulus on the coupled QCR and pillars with a diameter of 20 µm, a center-to-center spacing of 40 µm and a density of 2,500 kg/m³ was investigated. The results indicate that multiple vibration modes can be obtained based on Young’s modulus. Notably, in the case of the QCR–pillar in air, the second vibration mode occurred at a critical Young’s modulus of 0.2 MPa, whereas the first mode was observed at 3.75 Mpa. The vibration phase analysis revealed phase-veering behavior at the critical Young’s modulus, which resulted in a sudden jump-and-drop frequency shift. In addition, the results show that the critical Young’s modulus is dependent on the surrounding environment of the pillar. For instance, the critical Young’s modulus for the first mode of the pillar is approximately 3.75 Mpa in air, whereas it increases to 6.5 Mpa in water.

It was concluded that the performance of coupled QCR–pillar devices significantly depends on the pillar material. Therefore, choosing pillar material at critical Young’s modulus can lead to the maximum frequency shift of coupled QCR–pillar devices. The model developed in this work helps the researchers design pillars to achieve maximum frequency shift in their measurements using coupled QCR–pillar.

In this paper, the authors emphasize that COVID-19 pandemic is a serious pandemic as it continues to cause deaths and long-term health effects, followed by the most prolonged crisis in the 21st century and has disrupted supply chains globally. This study questions “can technological inputs such as big data analytics help to restore strength and resilience to supply chains post COVID-19 pandemic?”; toward which authors identified risks associated with purchasing and supply chain management by using a hypothetical model to achieve supply chain resilience through big data analytics.

The hypothetical model is tested by using the partial least squares structural equation modeling (PLS-SEM) technique on the primary data collected from the manufacturing industries.

It is found that big data analytics tools can be used to help to restore and to increase resilience to supply chains. Internal risk management capabilities were developed during the COVID-19 pandemic that increased the company's external risk management capabilities.

The findings provide valuable insights in ways to achieve improved competitive advantage and to build internal and external capabilities and competencies for developing more resilient and viable supply chains.

To the best of authors' knowledge, the model is unique and this work advances literature on supply chain resilience.

The purpose of this study is to examine the direct/indirect effects of sustainable competitive advantage (SCA) antecedents (entrepreneurial orientation, marketing capability, innovation capability and marketing innovation) on market performance (MP) in travel agencies.

A survey was used for data collection randomly from 315 managers in travel agencies and structural equation modelling was used for testing research hypotheses.

The findings of this study showed that SCA is a partial mediator between SCA antecedents and MP. SCA antecedents significantly improve the prediction of travel agencies’ MP.

This study offers useful insights to managers, services providers and marketers of travel services who seek to achieve competitive positions and strengthen their marketing and innovation capabilities to support their survival in the travel supply chain in an accelerated technological changeable travel and tourism market.

The literature review lacks an integrated model that investigates the effect of SCA and its antecedents on MP. The introduced research model provides a deep insight into the mediating role of SCA in improving business performance.

This study examines how applying innovative I4.0 technologies at the design stage can help reduce construction waste and improve the recovery, reuse, and recycling of construction materials.

The study adopts a three-stage sequential mixed methods approach, involving a thorough review of current literature, interviews with six experts in digital construction, and a survey of 75 experienced industry practitioners.

The study identifies and discusses how ten specific digital technologies can improve design stage processes leading to improved circularity in construction, namely, (1) additive and robotic manufacturing; (2) artificial intelligence; (3) big data analytics; (4) blockchain technology; (5) building information modelling; (6) digital platforms; (7) digital twins; (8) geographic information systems; (9) material passports and databases; and (10) Internet of things. It demonstrates that by using these technologies to support circular design concepts within the sector, material recycling rates can be improved and unnecessary construction waste reduced.

This research provides researchers and practitioners with improved understanding of the potential of digital technology to recycle construction waste at the design stage, and may be used to create an implementation roadmap to assist designers in finding tools and identifying them.

Little consideration has been given to how digital technology can support design stage measures to reduce construction waste. This study fills a gap in knowledge of a fast-moving topic.

The purpose of this study, most recent advancements in threedimensional (3D) printing have focused on the fabrication of components. It is typical to use different print settings, such as raster angle, infill and orientation to improve the 3D component qualities while fabricating the sample using a 3D printer. However, the influence of these factors on the characteristics of the 3D parts has not been well explored. Owing to the effect of the different print parameters in fused deposition modeling (FDM) technology, it is necessary to evaluate the strength of the parts manufactured using 3D printing technology.

In this study, the effect of three print parameters − raster angle, build orientation and infill − on the tensile characteristics of 3D-printed components made of three distinct materials − acrylonitrile styrene acrylate (ASA), polycarbonate ABS (PC-ABS) and ULTEM-9085 − was investigated. A variety of test items were created using a commercially accessible 3D printer in various configurations, including raster angle (0°, 45°), (0°, 90°), (45°, −45°), (45°, 90°), infill density (solid, sparse, sparse double dense) and orientation (flat, on-edge).

The outcome shows that variations in tensile strength and force are brought on by the effects of various printing conditions. In all possible combinations of the print settings, ULTEM 9085 material has a higher tensile strength than ASA and PC-ABS materials. ULTEM 9085 material’s on-edge orientation, sparse infill, and raster angle of (0°, −45°) resulted in the greatest overall tensile strength of 73.72 MPa. The highest load-bearing strength of ULTEM material was attained with the same procedure, measuring at 2,932 N. The tensile strength of the materials is higher in the on-edge orientation than in the flat orientation. The tensile strength of all three materials is highest for solid infill with a flat orientation and a raster angle of (45°, −45°). All three materials show higher tensile strength with a raster angle of (45°, −45°) compared to other angles. The sparse double-dense material promotes stronger tensile properties than sparse infill. Thus, the strength of additive components is influenced by the combination of selected print parameters. As a result, these factors interact with one another to produce a high-quality product.

The outcomes of this study can serve as a reference point for researchers, manufacturers and users of 3D-printed polymer material (PC-ABS, ASA, ULTEM 9085) components seeking to optimize FDM printing parameters for tensile strength and/or identify materials suitable for intended tensile characteristics.

The purpose of this study is to analyze the corporate social responsibility (CSR) communication of the Fortune top-100 companies during the coronavirus disease 2019 (COVID-19) pandemic. Specifically, the authors examine the messages of international companies' CSR communication to customers during the pandemic, focusing particularly on the companies' posts on Twitter. In addition to identifying what international companies communicate, the authors determine the motives of companies' COVID-19-related CSR communication as well as how companies strategically approach CSR communication.

Using Nvivo, the authors carried out content analysis of the COVID-19-related tweets of the Fortune top-100 companies using Twitter's ‘advanced search’ tool. The analysis included tweets posted between 1 February 2020 and September 2021, a period that represents the peak of the pandemic.

Study findings indicate that COVID-19-related CSR responses of international companies are driven by commitment to organizational values, attainment of recognition for timely response to COVID-19, altruistic motives to combat COVID-19 and congruence with social movements that create expectations from customers to respond to the COVID-19 pandemic. Most companies adopt a response strategy to CSR communication, by informing customers of their COVID-19 responses in relation to several issues such as alterations in companies' processes and the impacts of the pandemic on health.

The study suggests that the CSR practices of companies should be strategically embedded in organizations' international marketing plans and not remain just on-off responses to crises should marketing-related benefits be obtained. Several recommendations are made to strengthen companies' adoption of a proactive, engagement-oriented approach to CSR communication.

The CSR communication of international companies during external crises has not been sufficiently studied in relation to international marketing, as most studies considered internal corporate crises. Focusing on an external crisis (COVID-19 pandemic) with global impacts, this study advances existing knowledge on international companies' CSR communication to their customers. Additionally, this study offers new insights on the role of integrated, coordinated and consistent CSR messages and strategies, which are targeted to the needs and expectations of domestic and international customers in response to COVID-19 pandemic.