Search results

This study aims to experimentally investigate branded functional beverage (BFB) consumption behaviour post-COVID-19 through the lens of a conceptual framework built on three renowned behaviour modification models and to critically evaluate how well subjective norms serve as a moderator in the consumption behaviour relating to such beverage products.

A conceptual model was developed based on the tenets of the theory of planned behaviour (TPB), health belief model (HBM) and value-attitude-behaviour (VAB) model. The study was performed on a convenience sample of 537 respondents aged 18 and up from diverse regions in India using the PLS-SEM method. A total of 444 useable questionnaires were utilized for the final data analysis.

Given the post-pandemic setting, the perceived benefits of BFBs significantly influenced its purchase intention and consumption behaviour. It could grossly impact the media's role (information about COVID-19) and the consumers' interest in healthy food. The study revealed that the information about COVID-19 (role of media) strongly increased interest in healthy food, whereas interest in healthy food positively influenced purchase intention of functional beverages. With interest in healthy food as a “mediator”, the role of media (information about COVID-19) positively influenced purchase intention. It is worth noting the moderating role of subjective norms in the relationship between the role of media (information about COVID-19) and interest in healthy food and that between interest in healthy food and BFB purchase intention.

Food marketers shall skillfully use “opinion” leaders and subject experts in marketing communication campaigns to popularize the link between good food and immunity through COVID-19 and healthy diet-related messages sent via a suitable media platform. This would grab food consumers' interest in BFBs and persuade them to incorporate such items in their daily food milieu. Consumers need to be assured that consuming “functional” products would deliver health benefits and upkeep their body immunity in the post-COVID-19 times.

There has been minimal research on the link between perceived benefits, the role of media, interest in healthy food and consumption behaviour on functional beverages in the post-COVID-19 setting. Moreover, subjective norms have never been probed as a moderator in the consumer behaviour studies on BFBs. This pioneering study applied the tenets of the TPB, HBM and VAB model in the context of post-pandemic functional beverage consumption. The altered study settings caused by the COVID-19 pandemic and the context of a developing economy like India have amplified the research value of this study.

Some studies have been reported in the past on diaphragmatic hernia (DH) surgery techniques using additive manufacturing (AM) technologies, symptoms of a hernia and post-surgery complications. But hitherto little has been reported on bibliographic analysis (BA) for health monitoring of bovine post-DH surgery for long-term management. Based on BA, this study aims to explore the sensor fabrication integrated with innovative AM technologies for health monitoring assistance of bovines post-DH surgery.

A BA based on the data extracted through the Web of Science database was performed using bibliometric tools (R-Studio and Biblioshiny).

After going through the BA and a case study, this review provides information on various 3D-printed meshes used over the sutured site and available Internet of Things-based solutions to prevent the recurrence of DH.

Research gaps exist for 3D-printed conformal sensors for health monitoring of bovine post-DH surgery.

Recently, powerful instruments for biomedical engineering research studies, including disease modeling, drug designing and nano-drug delivering, have been extremely investigated by researchers. Particularly, investigation in various microfluidics techniques and novel biomedical approaches for microfluidic-based substrate have progressed in recent years, and therefore, various cell culture platforms have been manufactured for these types of approaches. These microinstruments, known as tissue chip platforms, mimic in vivo living tissue and exhibit more physiologically similar vitro models of human tissues. Using lab-on-a-chip technologies in vitro cell culturing quickly caused in optimized systems of tissues compared to static culture. These chipsets prepare cell culture media to mimic physiological reactions and behaviors.

The authors used the application of lab chip instruments as a versatile tool for point of health-care (PHC) applications, and the authors applied a current progress in various platforms toward biochip DNA sensors as an alternative to the general bio electrochemical sensors. Basically, optical sensing is related to the intercalation between glass surfaces containing biomolecules with fluorescence and, subsequently, its reflected light that arises from the characteristics of the chemical agents. Recently, various techniques using optical fiber have progressed significantly, and researchers apply highlighted remarks and future perspectives of these kinds of platforms for PHC applications.

The authors assembled several microfluidic chips through cell culture and immune-fluorescent, as well as using microscopy measurement and image analysis for RNA sequencing. By this work, several chip assemblies were fabricated, and the application of the fluidic routing mechanism enables us to provide chip-to-chip communication with a variety of tissue-on-a-chip. By lab-on-a-chip techniques, the authors exhibited that coating the cell membrane via poly-dopamine and collagen was the best cell membrane coating due to the monolayer growth and differentiation of the cell types during the differentiation period. The authors found the artificial membrane, through coating with Collagen-A, has improved the growth of mouse podocytes cells-5 compared with the fibronectin-coated membrane.

The authors could distinguish the differences across the patient cohort when they used a collagen-coated microfluidic chip. For instance, von Willebrand factor, a blood glycoprotein that promotes hemostasis, can be identified and measured through these type-coated microfluidic chips.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

This paper aims to determine the knowledge and attitudes of the physicians regarding human immunodeficiency virus (HIV)/acquired immune deficiency syndrome (AIDS), to emphasize that these patients exist and they will exist in the future and to raise awareness so as to prevent that their rights to treatment are revoked.

The survey was conducted via a link sent through an online system. Random physicians from 81 cities of the country were invited to the survey. The survey has 41 questions regarding knowledge and attitudes in total, including epidemiological information such as age, gender and title.

A total of 3,107 physicians has voluntarily participated in the study. In total, 2,195 (70.7%) are internal physicians and 912 (29.3%) are surgical physicians among the participant physicians. In total, 1,452 (46.7%) of the participants are specialist physicians, 608 (19.6%) of the participants are practising physician and the rest of it is physician assistants, academicians and dentists, respectively.

In this study, it has been found out that the physicians have a lack of knowledge on HIV/AIDS and they adopt a discriminatory attitude towards HIV-positive persons. HIV-positive patients who are exposed to discrimination and scared of being uncovered refrain from applying to hospitals for treatment, which puts public health into jeopardy due to the high viral load and these patients are faced with difficulties in coping with both medical and emotional load of the disease.

Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.

The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.

The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.

In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.

The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).

This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

The purpose of this study is to determine the viability of Lacticaseibacillus rhamnosus GR-1 (L. rhamnosus GR-1) in five yogurt samples with or without quinoa, chickpea, soybean and rice flour over various fermentation periods and refrigerated storage durations, with a focus on exploring the potential of functional foods, which provide health benefits beyond nutritional value. Additionally, the study aimed to evaluate consumer acceptance of yogurt fortified with functional flour. Using a nine-point hedonic scale, from 1 (dislike extremely) to 9 (like extremely), participants rated appearance, flavour, texture and overall acceptability.

The samples were inoculated with the probiotic strain L. rhamnosus GR-1 and fermented for 0, 2, 4 and 6 h at 38°C, followed by refrigerated storage at 4°C for 1, 15 and 30 days, respectively. Microbial enumeration was performed throughout fermentation and storage to assess the viability of L. rhamnosus GR-1. A sensory evaluation involving 86 participants was conducted to assess the consumer acceptability of the yogurt samples.

Notably, L. rhamnosus GR-1 achieved viable counts of 108 colony-forming units per mL in all treatments at all fermentation time points. Over the 30-day storage period, no statistically significant differences (p < 0.05) in average pH values were observed among the five treatments, and within each treatment, pH levels remained stable, with an overall mean of 4.2 ± 0.64. Treatment 4, which featured rice flour fortification, received higher hedonic scores from sensory panellists in terms of appearance, flavour, texture and overall acceptability. These findings indicate that incorporating functional flours in conjunction with cow’s milk effectively promotes and preserves the viability of L. rhamnosus GR-1 in yogurt.

Exploring the potential of probiotic yogurt enriched with diverse functional flours to enhance nutritional content and health benefits as well as attract new consumers, this study addressed a critical gap in understanding consumer perceptions and generated insights for creating innovative and health-promoting dairy products.

This study presents the results of an assessment of the barriers that can hinder the deployment of robotics and automation systems in developing countries through the lens of the Nigerian construction industry.

A scoping literature review was conducted through which barriers to the adoption of robotics and automation systems were identified, which helped in the formulation of a questionnaire survey. Data were obtained from construction professionals including architects, builders, engineers and quantity surveyors. Retrieved data were analyzed using percentages, frequencies, mean item scores and exploratory factor analysis.

Based on the mean scores, the top five barriers were the fragmented nature of the construction process, resistance by workers and unions, hesitation to adopt innovation, lack of capacity and expertise and lack of support from top-level managers. Through factor analysis, the barriers identified were categorized into four principal clusters namely, industry, human, economic and technical-related barriers.

This study provided a good theoretical and empirical foundation that can be useful to construction industry stakeholders, decision-makers, policymakers and the government in mapping out strategies to promote the incorporation and deployment of automation and robotics into the construction industry to attain the safety benefits they offer.

By identifying and evaluating the challenges that hinder the implementation of robotics and automation systems in the Nigerian construction industry, this study makes a significant contribution to knowledge in an area where limited studies exist.

Health care systems aspire to adopt integration strategies shifting the focus from acute care to a broader focus on community-based health and social services. Real-world examples demonstrating effective delivery of integrated care are essential.

In this article, we introduce UHN Connected Care Hub, an innovative model of care comprising an interdisciplinary team designing sustainable, shareable practices across the continuum of care alongside community and health organization partnerships.

We describe UHN Connected Care Hub’s ability to identify patients from high-risk population and collaborate to delivery timely care, in detailing the real world experience of this model of care in the organization of a centralized system of micro-clinics to administer a therapeutic for pre-exposure prophylaxis against COVID-19 (Tixagevimab/cilgavimab [Evusheld]) in a population of immunocompromised patients.

Having a centralized system of micro-clinics for care delivery presents opportunities for increased adaptability, patient accessibility, enhanced community partnerships and integratedness. Expansion in the scope of services could also create new opportunities in preventative therapies for optimizing the cost effectiveness and quality of health care provided at the population level.

There is limited evidence on how to efficiently deliver integrated care, particularly to vulnerable and co-morbid patients. We discuss how dynamic organizations with proper infrastructure and a network of healthcare partnerships may allow a more fluid response to rapidly changing policies and procedures and facilitate preparedness for future health care crises or pandemics.

An AI concierge is a technologically advanced, intelligent and personalized assistant that is designated to an individual customer, proactively taking care of that customer’s needs throughout the service journey. This article envisions the idea of AI concierges and discusses how to leverage AI concierges in the customer journey.

This article takes a conceptual approach and draws insights from literature in service management, marketing, psychology, human-computer interaction and ethics.

This article delineates the fundamental forms of AI concierges: dialog interface (no embodiment), virtual avatar (embodiment in the virtual world), holographic projection (projection in the physical world) and tangible service robot (embodiment in the physical world). Key attributes of AI concierges are the ability to exhibit semantic understanding of auditory and visual inputs, maintain an emotional connection with the customer, demonstrate proactivity in refining the customer’s experience and ensure omnipresence through continuous availability in various forms to attend to service throughout the customer journey. Furthermore, the article explores the multifaceted roles that AI concierges can play across the pre-encounter, encounter and post-encounter stages of the customer journey and explores the opportunities and challenges associated with AI concierges.

This paper provides insights for professionals in hospitality, retail, travel, and healthcare on leveraging AI concierges to enhance the customer experience. By broadening AI concierge services, organizations can deliver personalized assistance and refined services across the entire customer journey.

This article is the first to introduce the concept of the AI concierge. It offers a novel perspective by defining AI concierges’ fundamental forms, key attributes and exploring their diverse roles in the customer journey. Additionally, it lays out a research agenda aimed at further advancing this domain.