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The aim of the study is to determine the benefits of transforming a destination into smart destination (SD) to restart tourism after the COVID-19 outbreak, to match the dimensions of SD with restarting strategies, and to make conceptual inferences to serve this. For this purpose, two reports published by the World Tourism Organization (WTO) in 2020 were examined: Priorities for Tourism Recovery and Global Guidelines to Restart Tourism. Then, the contents of these reports and the dimensions of SDs were matched and a guiding model for tourism decision-makers was developed.

Are major and frequent disruptions transforming global supply chains? This study aims to investigate how multinational companies (MNCs) are responding to the phenomenon of accumulated major disruptions in recent years and plausible new paradigm of unstable conditions and environmental uncertainty from a supply chain resilience (SCRES) perspective.

Following an inductive interpretivist approach based on interpretive phenomenology, this study gathers insights from ten MNCs supply chain managers and international consultants who participated as key informants via semi-structured interviews, sharing their experience of the phenomenon. Additionally, secondary sources such as press releases, media articles and industry reports were used for data collection.

Findings include five categories of recovery actions, i.e. levelling, rationing, buffering, bridging and boundary redefining, key strategic changes in competitive priorities, internal organisation and coordination structures, and a hierarchy between SCRES characteristics, integrated in an empirically derived conceptual framework connecting these constructs. This contributes to middle-range theories within SCRES body of knowledge. The authors also identify a set of areas for future SCRES research.

Findings can support MNCs’ supply chain professionals in designing and managing resilient global supply chains, based on learnings from the recent highly disruptive environment, particularly, regarding recovery actions and resilience-building strategic changes contributing to agility and robustness in global supply chains.

Non-positivist interpretive and inductive works are scarce in SCRES research. By adopting this novel approach for this field, the authors broadened the categorisation of responses used in previous works and identified prominent strategic changes and SCRES characteristics and relations among constructs, thus bringing conceptual clarity to SCRES research within the context of the study.

This paper aims to develop a crisis readiness framework for road traffic crisis response for law enforcement agencies in the United Arab Emirates (UAE).

A Delphi method was used that combined questionnaire-based survey and the analytical hierarchy process to collect quantitative and qualitative data from an expert panel of crisis readiness professionals on how they prioritise and weigh the different strategic criteria, sub-criteria and performance indicators in the context of law enforcement agencies’ traffic response.

The findings of this paper resulted in the identification, ranking and validation of ten key dimensions of crisis readiness clustered into three distinct sets of priority rankings: response planning, resources, training and coordination; information management and communication and risk and hazard assessment; and early warning, legal and institutional frameworks, recovery initiation and property protection. The results additionally established the relative priority of sub-criteria for each criterion and validated a broad set of key performance indicators (KPIs) for the top six ranked criteria.

The findings are based on a single case study focused on a specific area of operation within crisis response and one group of organisations of the UAE police sector. This potentially places a constraint on the wider generalisation of the findings to different operational areas and agencies, as they may have different priorities or organisational conditions that have implications for the framework application and the relative importance of certain criteria and sub-criteria.

This paper provides strategic guidance in the form of a prioritised list of criteria, sub-criteria and KPIs that can direct efforts to optimise different dimensions of crisis readiness at a strategic and operational level.

This paper makes an original contribution in identifying the key criteria and performance indicators of crisis readiness for road traffic situations. The findings contribute a comprehensive strategic readiness framework that supports planning and decision-making for the development of organisational capacities that can enhance response times of police to road traffic crises. This framework ranks dimensions of crisis readiness and key sub-criteria in order of priority and validates the key components of crisis readiness that can support practitioners to structure, standardise and benchmark key processes and elements of crisis response.

Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

This paper aims to explore the roles of psychologists in seclusion in adult mental health services in Ireland, their perspectives on seclusion and its use in recovery-oriented practice and related professional practice issues.

A qualitative hermeneutic phenomenological study was conducted from a social constructivist perspective. Semi-structured interviews with 17 psychologists were analysed using reflexive thematic analysis.

Twenty-four themes were identified, which were clustered into four overarching themes. Participants viewed themselves and psychology in Ireland more broadly as peripheral to seclusion. They believed that seclusion possessed no inherent therapeutic value but viewed it as an uncomfortable and multi-faceted reality. Participants regarded seclusion and recovery as largely inconsistent and difficult to reconcile, and they perceived systemic factors, which had a pervasive negative impact on seclusion and recovery in practice.

The findings highlight the perceived complexity of seclusion and its interface with recovery, and the need to conscientiously balance conflicting priorities that cannot be easily reconciled to ensure ethical practice. The findings suggest psychologists are well-suited to participate in local and national discussions on using seclusion in recovery-oriented practice.

This study offers a unique insight into psychologists’ perceptions of seclusion and considers the implications of these views. Participants’ nuanced views suggest that psychologists can make valuable contributions to local and national discussions on these topics.

This study aims to set out to identify and evaluate potential obstacles to successfully implementing lean construction (LC) as a result.

Several indicators were recognized as major obstacles following an exhaustive assessment of the literature and a multicriteria decision analysis based on the analytic hierarchy process (AHP) of information obtained from a questionnaire survey that was directed to practitioners in the Indian construction industry.

The results of this AHP model suggest that “Managerial” and “Inadequate resources” categories with a priority weight of “0.361” and “0.309” have the highest levels of influence, respectively, while “Inadequate knowledge” and “just in time (JIT)” categories with a priority weight of “0.053” and “0.034” have the lowest levels of influence, respectively.

Construction companies can use the study’s findings as a guide to determine whether they are ready to embrace LC, learn more about the components needed for implementation or investigate any challenges that may arise. These businesses can then create plans to promote the adoption and application of the lean philosophy.

The Indian construction industry may see great success with LC management initiatives. LC concepts have been adopted by many nations, but during the past 20 years, there has only appeared to be a limited amount of lean implementation in the Indian construction industry. It seems that several structural and cultural barriers are preventing its effective implementation. Organizations will not be able to determine what improvement efforts are required, where these efforts should be directed or which initiatives could provide the best outcomes if they are unaware of the elements that influence the effective implementation of LC.

Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate, this paper presents a simulation framework that enables an examination of the effects of applying smart manufacturing principles to conventional production systems, intending to transition to digital platforms.

To investigate the extent to which conventional production systems can be transformed into novel data-driven environments, the well-known constant work-in-process (CONWIP) production systems and considered production sequencing assignments in flowshops were studied. As a result, a novel data-driven priority heuristic, Net-CONWIP was designed and studied, based on the ability to collect real-time information about customer demand and work-in-process inventory, which was applied as part of a distributed and decentralised production sequencing analysis. Application of heuristics like the Net-CONWIP is only possible through the ability to collect and use real-time data offered by a data-driven system. A four-stage application framework to assist practitioners in applying the proposed model was created.

To assess the robustness of the Net-CONWIP heuristic under the simultaneous effects of different levels of demand, its different levels of variability and the presence of bottlenecks, the performance of Net-CONWIP with conventional CONWIP systems that use first come, first served priority rule was compared. The results show that the Net-CONWIP priority rule significantly reduced customer wait time in all cases relative to FCFS.

Previous research suggests there is considerable value in creating data-driven environments. This study provides a simulation framework that guides the construction of a digital transformation environment. The suggested framework facilitates the inclusion and analysis of relevant smart manufacturing principles in production systems and enables the design and testing of new heuristics that employ real-time data to improve operational performance. An approach that can guide the structuring of data-driven environments in production systems is currently lacking. This paper bridges this gap by proposing a framework to facilitate the design of digital transformation activities, explore their impact on production systems and improve their operational performance.

The COVID-19 pandemic severely impacted tourism, and the hotel and restaurant industry was the most affected sector, which faced issues related to business uncertainty and unemployment during the crisis. The analysis of recovery time and the influence factors is significant to support policymakers in developing an effective response and mitigating the risks associated with the tourism crisis. This study aims to investigate numerous factors affecting the recovery time of the hotel and restaurant sector after the COVID-19 crisis by using survival analysis.

This study uses the quarterly value added with the observation time from quarter 1 in 2020 to quarter 1 in 2023 to measure the recovery status. The recovery time refers to the number of quarters needed for the hotel and restaurant sector to get value added equal to or exceed the value added before the crisis. This study applies survival models, including lognormal regression, Weibull regression, and Cox regression, to investigate the effect of numerous factors on the hazard ratio of recovery time of hotels and restaurants after the COVID-19 crisis. This model accommodates all cases, including “recovered” and “not recovered yet” areas.

The empirical findings represented that the Cox regression model stratified by the area type fit the data well. The priority tourism areas had a longer recovery time than the non-priority areas, but they had a higher probability of recovery from a crisis of the same magnitude. The size of the regional gross domestic product, decentralization funds, multiplier effect, recovery time of transportation, and recovery time of the service sector had a significant impact on the probability of recovery.

This study contributes to the literature by examining the recovery time of the hotel and restaurant sector across Indonesian provinces after the COVID-19 crisis. Employing survival analysis, this study identifies the pivotal factors affecting the probability of recovery. Moreover, this study stands as a pioneer in investigating the multiplier effect of the regional tourism and its impact on the speed of recovery.