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The purpose of this research paper is to explore the determinants of patients' service choices between telephone consultation and text consultation in online health communities (OHCs).

This study utilized an empirical model based on the elaboration likelihood model and examined the effect of information, regarding service quality (the central route) and service price (the peripheral route), using online health consultation data from one of the largest OHCs in China.

The logistic regression results indicated that both physician- and patient-generated information can influence the patients' service choices; service price signals will lead patients to cheaper options. However, individual motivations, disease risk and consulting experience change a patients' information processing regarding central and peripheral cues.

Previous researchers have investigated the mechanism of patient behavior in OHCs; however, the researchers have not focused on the patients' choices regarding the multiple health services provided in OHCs. The findings of this study have theoretical and practical implications for future researchers, OHC designers and physicians.

Effectively predicting research and development project portfolio benefit (R&D PPB) could assist organizations in monitoring the execution of research and development project portfolio (R&D PP). However, due to the uncertainty and complexity of R&D PPB, current research remains lacking a valid R&D PPB prediction tool. Therefore, an R&D PPB prediction model is proposed via a backpropagation neural network (BPNN).

The R&D PPB prediction model is constructed via a refined immune genetic algorithm coupling backpropagation neural network (RIGA-BPNN). Firstly, considering the characteristics of R&D PP, benefit evaluation criteria are identified. Secondly, the benefit criteria values are derived as input variables to the model via trapezoidal fuzzy numbers, and then the R&D PPB value is determined as the output variable through the CRITIC method. Thirdly, a refined immune genetic algorithm (RIGA) is designed to optimize BPNN by enhancing polyfitness, crossover and mutation probabilities. Lastly, the R&D PPB prediction model is constructed via the RIGA-BPNN, followed by training and testing.

The accuracy of the R&D PPB prediction model stands at 99.26%. In addition, the comparative experiment results indicate that the proposed model surpasses BPNN and the immune genetic algorithm coupling backpropagation neural network (IGA-BPNN) in both convergence speed and accuracy, showcasing superior performance in R&D PPB prediction. This study enriches the R&D PPB predicting methodology by providing managers with an effective benefits management tool.

The research implications of this study encompass three aspects. First, this study provides a profound insight into R&D PPB prediction and enriches the research in PP fields. Secondly, during the construction of the R&D PPB prediction model, the utilization of the composite system synergy model for quantifying synergy contributes to a comprehensive understanding of intricate interactions among benefits. Lastly, in this research, a RIGA is proposed for optimizing the BPNN to efficiently predict R&D PPB.

This study carries threefold implications for the practice of R&D PPM. To begin with, the approach proposed serves as an effective tool for managers to predict R&D PPB. Then, the model excels in efficiency and flexibility. Furthermore, the proposed model could be used to tackle additional challenges in R&D PPM, such as gauging the potential risk level of R&D PP.

Effective predicting of R&D PPB enables organizations to allocate their limited resources more strategically, ensuring optimal use of capital, manpower and time. By accurately predicting benefit, an organization can prioritize high-potential initiatives, thereby improving innovation efficiency and reducing the risk of failed investments. This approach not only strengthens market competitiveness but also positions organizations to adapt more effectively to changing market conditions, fostering long-term growth and sustainability in a competitive business environment.

Incorporating the characteristics of R&D PP and quantifying the synergy between benefits, this study facilitates a more insightful R&D PPB prediction. Additionally, improvements to the polyfitness, crossover and mutation probabilities of IGA are made, and the aforementioned RIGA is applied to optimize the BPNN. It significantly enhances the prediction accuracy and convergence speed of the neural network, improving the effectiveness of the R&D PPB prediction model.

This work aims to integrate the concepts generated by a systematic literature review on patient flows in emergency departments (ED) to serve as a basis for developing a generic process model for ED.

A systematic literature review was conducted using PRISMA guidelines, considering Lean Healthcare interventions describing ED patients’ flows. The initial search found 141 articles and 18 were included in the systematic analysis. The literature analysis served as the basis for developing a generic process model for ED.

ED processes have been represented using different notations, such as value stream mapping and workflows. The main alternatives for starting events are arrival by ambulance or walk-in. The Manchester Triage Scale (MTS) was the most common protocol referred to in the literature. The most common end events are admission to a hospital, transfer to other facilities or admission to an ambulatory care system. The literature analysis allowed the development of a generic process model for emergency departments. Nevertheless, considering that several factors influence the process of an emergency department, such as pathologies, infrastructure, available teams and local regulations, modelling alternatives and challenges in each step of the process should be analysed according to the local context.

A generic business process model was developed using BPMN that can be used by practitioners and researchers to reduce the effort in the initial stages of design or improvement projects. Moreover, it’s a first step toward the development of generalizable and replicable solutions for emergency departments.

The purpose of this paper was to compare the electrochemical homogeneity of AZ91D after various heat treatment processes, and its influence on the growth, composition, microstructure and corrosion resistance of phosphate conversion coatings.

The electrochemical activity of different heat-treated Mg alloys was evaluated via scanning vibrational electrode technique; the characterization of the microstructure and phase composition of coatings was conducted using a scanning electron microscope and X-ray diffraction. The corrosion resistance was evaluated by electrochemical tests and accelerated neutral salt spray tests.

T6 treatment increased the electrochemical homogeneity, while T4 treatment decreased the microstructure homogeneity of AZ91D magnesium alloy, due to the existence of residual Al-Mn impurity phase. The phosphate conversion coating (PCC) on T6 heat-treated Mg alloys showed the most compact microstructure and the best corrosion resistance, while the coating on the T4 heat-treated Mg alloy exhibited the worst microstructure and corrosion resistance.

The microstructure and protectiveness of coatings are related to the homogeneousness of Mg alloy: an Mg substrate with a more heterogeneous electrochemical reactivity yields a PCC with less protectiveness, which could be explained by the difference of precipitation kinetics at the metal/electrolyte interface.

The purpose of this study is to provide new insights into the relationship between fiscal policy and total factor productivity (TFP) while accounting for several economic and econometric issues of the phenomenon like non-stationarity, fiscal feedback effects, persistence in productivity, country heterogeneity and unobserved global shocks and local spillovers affecting heterogeneously the countries in the sample.

The paper is empirical. It builds an Error Correction Model (ECM) specification within a dynamic heterogeneous framework with common correlated effects and models both reverse causality and feedback effects.

The results of this study highlight some new findings relative to the existing related literature. The outcomes suggest some relevant evidence at both the academic and policy levels: (1) the causal effects going from fiscal deficit/surplus to TFP are heterogeneous across countries; (2) the effects depend on the time horizon considered; (3) the long-run dynamics of TFP are positively impacted by improvements in fiscal budget, but only if the austerity measures do not exert slowdowns in aggregate growth.

The main originality of this study is methodological, with possible extensions to related phenomena. Relative to the existing literature, the gains of this study rely on the way econometric techniques, recently proposed in the literature, are adapted to the economic relationship of interest. The endogeneity due to the existence of reverse causality is modelled without implying relevant performance losses of the models. Moreover, this is the first article that questions whether the effects of fiscal budget on productivity depend on the impact of the former on aggregate output growth, thus emphasising the importance of the quality of fiscal adjustments.

Prioritising economic, environmental and social requirements of society has become imperative for attaining a competitive edge in the global marketplace. This study examines how internal and external factors influence sustainable strategic orientations of Chinese small technology enterprises. It uses an initial framework grounded in institutional theory and resource-based view (RBV).

The study surveyed small technology enterprises using quantitative techniques. A combination of partial least squares structural equation modelling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) was used to analyse 402 valid samples with statistical significance.

The PLS-SEM results show that absorptive capacity, innovation culture and coercive pressure positively influence small enterprises’ sustainability orientation. Additionally, the fsQCA method identifies five complex combinations of causal antecedents that can facilitate small enterprises’ adoption of sustainability orientation.

The findings reaffirm the importance of maintaining ideal environmental cognition and external institutional pressure. Specifically, enterprises need to strategically allocate their limited resources to optimal levels and combinations to achieve sustainability orientation.

This study enhances the understanding of sustainability orientation by integrating the RBV and institutional theory, highlighting various factors that promote sustainability at the firm level. Furthermore, asymmetric research perspectives show the triggers of sustainability orientation from both symmetrical and asymmetrical perspectives. Set theory approaches represent a pioneering approach that captures the intricacies of sustainability orientation, advancing beyond previous variance-based findings by providing optimal mix solutions.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

The objective of this study was to measure the prevalence and severity of food insecurity in the United Arab Emirates (UAE) during May 2021 to June 2022, and to assess the impact of the COVID-19 pandemic on household food insecurity.

This study measured the prevalence of household food insecurity in UAE during May 2021 to June 2022 by employing FAO’s Food Insecurity Experience Scale (FIES). The impact of the COVID-19 pandemic on household food security was evaluated by employing a truncated regression model, using survey data from 504 respondents.

About 34% of the households were found to be food secure. About 22% of them experienced moderate or severe food insecurity (i.e. have eaten less than they thought should have) whereas almost none have experienced severe food insecurity during the sample period. The truncated model results show that households’ region of residence, livelihood source, education level, income and number of elderlies have a significant association with the probability of experiencing food insecurity. The pandemic-induced unemployment and disruptions in physical access to food positively associated with the probability of experiencing food insecurity.

It is critical to regularly monitor households’ food security status, and design strategies that explicitly consider the food security status of UAE’s significant expat population; most of whom are migrant manual labourers earning low wages, are less job-secured and have poorer access to health care.

Although several studies assessed the impact of the pandemic on food security in different countries, there is a lack of studies assessing the impact of the pandemic on food security in the import-dependent Gulf Cooperation Council (GCC) countries, whose food security might be severely impacted due to the COVID-19-induced global food supply chain disruptions. Our application of the truncated regression model also contributes to the food security literature.

Apples have always been considered a healthy product able to provide curative properties to consumers. In Italy, there is a long tradition of apple consumption and production both as a fresh product and as processed food. However, as with many other products, the consumption of fruits and vegetables and, more specifically apples, has been drastically affected by the first lockdown in 2020. In this project, the authors investigate whether the change in consumption habits had long-lasting consequences beyond 2020 and what are the main eating motivations, food-related behavior and socio-demographic affecting the consumption of fruits and vegetables after the pandemic.

The authors ran two online surveys with 1,000 Italian consumers across a year (from October 2021 to December 2022). In the study, participants answered questions about their consumption habits and their eating motives. Out of 1,000 consumers, the authors included in the final analysis only the participants who answered both surveys, leaving a final sample of 651 consumers.

The results show that participants have allocated more budget to fruit and vegetables after the lockdown than before it. Moreover, consumers reported an average increase in the consumption of apples. However, the increase was more pronounced for people aged between 30 and 50 years old and identified as female. After showing the difference across time, a cluster analysis identified three main segments that differ in their eating motives, place of purchase and area of residence.

Overall, the results contribute to a better understanding of how the global pandemic is still affecting people's daily life. Moreover, the findings can be used to guide the marketing and communication strategies of companies in the food sector.

To the best of the authors' knowledge, this is the first study that investigates changes in the consumption of fruits and vegetables, and, more specifically, apples, in Italy more than one year after the beginning of the COVID-19 pandemic. Moreover, the study proposes a classification of consumers based on their habits in a time frame during which the COVID-19 wave was at its bottom which is not currently present in the literature.

The main purpose of the paper is to identify the most important directions of research to date and to indicate new, emerging areas of research concerned with application of financial technology (FinTech) solutions in microfinance companies.

This paper systematically reviews the literature on FinTech in microfinance, highlighting its role in enhancing operational efficiency, customer experience and financial inclusion through technologies like blockchain and AI. Despite these advancements, significant gaps remain in understanding the key drivers of FinTech as a digital innovation, most important direction of research to date and emerging areas for future research in microfinance literature. This paper has attempted to systematise the results of the research carried out so far, based on the publications indexed in the Web of Science and Scopus databases, using selected multidimensional statistical methods.

The findings identify key themes, gaps and future research directions, shedding light on the strategic implications of digital technology in microfinance. This comprehensive analysis significantly advances the understanding of how FinTech enhances microfinance management operations and objectives, contributing to both academic discourse and practical applications.

The research’s novelty lies in its focussed exploration of digital innovation within microfinance, an area that remains relatively underexplored. No similar paper was found during the literature review.