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Mental illness presents a huge individual, societal and economic challenges, currently accounting for 20% of the worldwide burden of disease. There is a gap between the need for and access to services. Digital technology has been proven effective in e-mental health for preventing and treating mental health problems. However, there is a need for cross-disciplinary efforts to increase the impact of e-mental health services. This paper aims to report key challenges and possible solutions for cross-disciplinary and cross-sectorial research teams within the domain of e-mental health.

The key challenges and possible solutions will be discussed in light of the literature on effective cross-disciplinary research teams.

Six topics have been key challenges in our cross-disciplinary and cross-sectorial research team: to develop a shared understanding of the domain; to establish a common understanding of key concepts among the project participants; to involve the end-users in the research and development process; to collaborate across sectors; to ensure privacy and security of health data; and to obtain the right timing of activities according to project dependencies.

This study focuses to increase knowledge and training in cross-disciplinary and cross-sectorial research, as this is often referred to as an important tool when developing sustainable solutions for major societal challenges.

This study needs to include theory and skills training in cross-disciplinary research in research training.

Cross-disciplinary teams have the potential to address major societal challenges, including more perspectives and more stakeholders than single disciplinary research teams.

Major societal challenges require complex and sustainable solutions. However, there is a lack of knowledge about how cross-disciplinary and cross-sectorial research teams may work productively to solve these challenges. This paper shares experiences regarding the challenges and possible solutions for productive collaboration in cross-disciplinary and cross-sectorial research teams within the domain of e-mental health services.

The purpose of this review paper is to address the need for mapping the thematic structure of fuzzy-set qualitative comparative analysis (fsQCA) in the context of tourism and hospitality research, in response to the growing interest in this methodology.

This study conducts a comprehensive systematic review using the SPAR-4-SLR procedure to produce a scientific map of top-tier research using the fsQCA technique in tourism and hospitality studies.

A major finding of this review investigation is the identification of six knowledge clusters: business competitiveness in the hospitality sector; psychoanalysis of tourist behaviour and satisfaction; entrepreneurship in the tourism and hospitality sector; tourism business ecosystem; sustainable tourism; and service quality in the tourism and hospitality sectors.

Although this review assessment relied heavily on articles published in prestigious journals, it does not rule out the idea that other sources, such as conference proceedings, can provide valuable insight.

Novel insights into the intellectual structure of tourism and hospitality research using the fsQCA technique, as well as ideas for future exploration in this domain, are presented in this review.

The purpose of this paper is to investigate the impact of COVID-19 pandemic on the changing relationship between technology and economic activity in MENA countries.

The generalized method of moments (GMM) was applied to explore the presence of dynamic causality between technology, inflation, unemployment, foreign direct investment, trade opening, gross fixed capital formation and economic growth for 14 MENA countries before and after COVID-19.

Empirical evidence shows that the economic predictor variables change signs and impact negatively the economic growth as a result of the adverse consequences of the MENA health crisis. More interestingly, there is a unique, positive, meaningful relationship between ICT and economic growth.

The results show that economic resilience in MENA is significantly affected by digital infrastructure during the epidemic crisis. The authors conclude that macroeconomic adjustment and innovation improve the predictive performance of the health news model. Countries could take strong measures to support new strategies to strengthen their innovation competitiveness.

The purpose of this paper is to propose an optimal energy management (OEM) method using intelligent optimization techniques applied to implement an optimally hybrid heat and power isolated microgrid. The microgrid investigated combines renewable and conventional power generation.

Five bio-inspired optimization methods include an advanced proposed multi-objective particle swarm optimization (MOPSO) approach which is comparatively applied for OEM of the implemented microgrid with other bio-inspired optimization approaches via their comparative simulation results.

Optimal multi-objective solutions through Pareto front demonstrate that the advanced proposed MOPSO method performs quite better in comparison with other meta-heuristic optimization methods. Moreover, the proposed MOPSO is successfully applied to perform 24-h OEM microgrid. The simulation results also display the merits of the real time optimization along with the arbitrary of users’ selection as to satisfy their power requirement.

This paper focuses on the OEM of a designed microgrid using a newly proposed modified MOPSO algorithm. Optimal multi-objective solutions through Pareto front demonstrate that the advanced proposed MOPSO method performs quite better in comparison with other meta-heuristic optimization approaches.

The paper aims to investigate the difference in total factor productivity (TFP) among those firms with and without outsourcing in a developing country like Vietnam. Also, it explores the effect of outsourcing activities on total factor productivity with a specified concentration on the Vietnamese small and medium-sized enterprises (SMEs).

The panel data set of SMEs used in this study was originated from biannual surveys conducted under the collaboration between educational organizations and government agencies: Stockholm School of Economics (SSE), Department of Economics – the University of Copenhagen, the Institution of Labor Studies and Social Affairs (ILSSA) in the Ministry of Labor, Invalids and Social Affairs (MOLISA). In this study, the model is developed based on the production function in accordance with the model of Girma and Görg (2004). The firms’ TFP is the difference between the actual and the predicted output as with the approach by Levinsohn and Petrin (2003).

This study finds out that firms with outsourcing have higher total factor productivity than those without outsourcing activities. In addition, the more firms spend on outsourcing, the higher total factor productivity they can gain. Outsourcing to SMEs in a developing country can significantly increase its TFP by means of either maintaining core competencies or searching external resources in conducting some internal activities.

Although outsourcing has been widely applied by large firms, the research studying its impact on productivity at firm level is limited. Especially, this study can shed light on the impact for the case of SMEs in a developing economy.

This research aims to specialise in the investigation of risk management for service-oriented manufacturing supply chains via two stages, highlighting its differences from manufacturing. The research article is commenced by executing an encyclopedic review of earlier research to ascertain the distinctive traits of service-oriented manufacturing supply chains and identify prevalent risks. Secondly, an empirical study in the construction field, amongst the industry hardest struck in the mist of the COVID-19 epidemic, is conducted to thoroughly inspect the resonant effect of these risks on service-oriented manufacturing supply chain performance.

In this study, to validate the resonant effect mechanism, a thorough assessment is undertaken by juxtaposing theoretical model to a newly constructed comparative model that encompasses the single effects of risks on supply chain performance.

63% variance of service-oriented manufacturing supply chain performance was showcased by the resonant effect model, compared with 46.3% in the comparative model. Moreover, each risk exerts a more glaringly significant impact on supply chain performance, asserting the mechanism of the resonant influence. Another noteworthy result involves the demand risk possessing a low effect on supply chain performance, thus emphasising the superiority of service-oriented manufacturing supply chains.

Future research endeavours should hinge on the optimal “resonant” model explosion, thereby foreseeing and alleviating worst-case scenarios to guarantee the robustness and resilience of supply chain networks.

Indubitably, reducing the intensity of the resonant effect revolves around lowering the coefficient of “a,” thereby restricting/eliminating the link among risks. Therefore, the suggested resonant impact model might thus serve as “a road map”. In light of the aforementioned considerations, it is advisable that supply chain executives employ supply chain management tactics namely avoidance, prediction, and postponement, but only after meticulous consideration the costs and benefits of adopting such strategies.

The service-oriented manufacturing supply chain features and advantages have been analysed and explained throughout the article. The data gathered during the COVID-19 pandemic is a captivating and topical point of this paper.

The purpose of this paper is to investigate the input- and output-specific technical inefficiency of Vietnamese prawn-rice rotational crops (PRRC) and to identify the impacts of the socio-economic characteristics of farmers and farms on these technical inefficiencies.

This study first used a Russell-type (input-output) directional distance function to estimate the input- and output-specific technical inefficiency. Second, it applied a bootstrap truncated regression to analyze the factors influencing these technical inefficiencies. Data were gathered through a survey among 94 farmers, from Ben Tre and Kien Giang provinces, the two popular PRRC areas in the Mekong Delta.

Results show that Vietnamese PRRC farmers could reduce the water surface area by 3%, the use of seedlings by 15%, labor by 16%, fertilizers by 26%, and the use of others by 24%, while simultaneously increasing the revenue of farming system by 57% relative to the variable returns to scale (VRS) frontier. Farmers with more years of experience are generally better in managing the use of seedlings and in improvement of revenue. Farmers in Kien Giang province are more efficient in achieving revenue of the PRRC farming system than farmers in Ben Tre province.

Outcomes of this study are useful to identify strategies in minimizing the use of inputs while simultaneously maximizing PRRC production.

This paper relates to the comparison of two mostly different ecological zones, being the dominant production areas of PRRC, in which, Kien Giang represents the western part, while Ben Tre is in the eastern part of the Vietnam’s Mekong Delta. The findings not only expand the current understanding but also suggest various meaningful research questions regarding the development of Vietnamese PRRC under the impacts of climate change. The study also contributes to the literature on examining the input- and output-specific technical inefficiencies and influencing factors.

The present study is performed to identify the propagation mechanism of the ripple effect as well as examine the simultaneous impact of risks on supply chain (SC) performance.

A theoretical framework with many hypotheses regarding the relationships between SC risk types and performance is established. The data are collected from a large-scale survey supported by a project of the Japanese government to promote sustainable socioeconomic development for the Association of Southeast Asian Nations (ASEAN) region, with the participation of 207 firms. Structural equation modeling (SEM) is used to test the hypotheses of the theoretical framework.

It is indicated that human-made risk causes operational risk, while natural risk causes both supply risk and operational risk. Furthermore, the impacts of human-made risk and natural risk on performance are amplified through operational risk.

This study is one of the first attempts that identifies the propagation mechanism of the ripple effect and examines the simultaneous impact of risks on performance in construction SCs.

Although many studies on risk management in construction SCs have been carried out, they mainly focus on risk identification or quantification of risk impact. It is observed that research on the ripple effect of disruptions has been very scarce.

Proactive risk assessment suggests that risk assessment should emphasize the consequences that it might cause and the opportunities it might create for firms. Hence, this study aims to validate risk impact on supply chain performance in the context of the Vietnamese construction sector. Also, a complex network, in which multiple risk factors mutually affect, impede or promote each other, is developed to assist managers in tackling unpredictable risks proactively. In particular, the authors investigate whether certain risks could be considered either challenges or opportunities for businesses in turbulent times to improve SC performance.

The construction industry is the focal study context as it is one of the most essential industries in charge of providing accommodations, infrastructures and employment for society. 289 valid responses used in this research are from a large-scale survey result, supported by a Japanese government project promoting sustainable socio-economic development in Vietnam.

From the study findings, the authors find that external risk brings opportunities for supply chain performance. Meanwhile, demand risk, when it occurs, can reduce the danger level of operational risk, which is an interesting finding of this research. It is evident that when multiple risk factors mutually affect, impede or promote each other, it provides a more meaningful examination of mutually interconnected supply chain risks.

Practitioners should perceive risks as an opportunity than a threat. This study contributes to preventing risks and guaranteeing an effective and efficient supply chain by tackling unpredictable risks in a disruptive period. Moreover, data on validating research models collected during the Covid-19 pandemic and Ukraine and Russia conflicts reflect the topicality of this study.

This paper aims mainly at introducing applied statisticians and econometricians to the current research methodology with non-Euclidean data sets. Specifically, it provides the basis and rationale for statistics in Wasserstein space, where the metric on probability measures is taken as a Wasserstein metric arising from optimal transport theory.

The authors spell out the basis and rationale for using Wasserstein metrics on the data space of (random) probability measures.

In elaborating the new statistical analysis of non-Euclidean data sets, the paper illustrates the generalization of traditional aspects of statistical inference following Frechet's program.

Besides the elaboration of research methodology for a new data analysis, the paper discusses the applications of Wasserstein metrics to the robustness of financial risk measures.