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This paper aims to explore financial anxiety and generalized anxiety as the serial mediators linking perceived organizational support (POS) to career commitment.

Data were collected from 388 managerial and nonmanagerial employees in diverse service areas, such as restaurants, airlines and hotels in Turkey. The direct and mediating effects were tested via the PROCESS macro.

Financial anxiety partly mediates the impact of POS on career commitment. The findings further reveal that financial anxiety and generalized anxiety serially mediate the effect of POS on career commitment.

Management should work with mentors to provide employees with psychosocial support during the COVID-19 pandemic. When employees perceive that the firm really cares about them and values their contribution during these challenging days, they display lower anxiety and higher career commitment. Management should also retain employees who are high on career commitment because such employees possess a sense of calling and are unlikely to quit. These implications may not be considered new. However, management would need such employees concerning the firm’s performance recovery after COVID-19.

Workers in the service industries suffer from financial and generalized anxieties and display reduced career commitment during COVID-19. However, little is known about the antecedents and outcomes of financial anxiety among hospitality and tourism workers. More importantly, no empirical piece has tested these anxiety variables as the mediators linking POS to career commitment in the pertinent literature so far.

The purpose of this paper is to propose an innovative and integrated approach based on service quality measurement (SERVQUAL), quality function deployment (QFD) and failure modes and effects analysis (FMEA) for service quality improvement.

The SERVQUAL scale is used for service quality measurement, QFD is used for service design and FMEA is used to prevent possible failures during service delivery.

A case study in a public hospital in Turkey is performed to show how the proposed approach works in practice. The results of the study show that the proposed approach can be used effectively to assess service quality in practice.

Service quality has become an important issue for service enterprises facing a fiercely competitive environment to provide sustainability. This is the first study that applies an integrated methodology based on SERVQUAL scale, QFD and FMEA to service quality improvement.

Given the importance of spatial effects in improving the accuracy of hotel demand forecasting, this study aims to introduce price and online rating, two critical factors influencing hotel demand, as external variables into the model, and capture the spatial and temporal correlation of hotel demand within the region.

For high practical implications, the authors conduct the case study in Xiamen, China, where the hotel industry is prosperous. Based on the daily demand data of 118 hotels before and during the COVID-19 period (from January to June 2019 and from January to June 2021), the authors evaluate the prediction performance of the proposed innovative model, that is, a deep learning-based model, incorporating graph convolutional networks (GCN) and gated recurrent units.

The proposed model simultaneously predicts the daily demand of multiple hotels. It effectively captures the spatial-temporal characteristics of hotel demand. In addition, the features, price and online rating of competing hotels can further improve predictive performance. Meanwhile, the robustness of the model is verified by comparing the forecasting results for different periods (during and before the COVID-19 period).

From a long-term management perspective, long-term observation of market competitors’ rankings and price changes can facilitate timely adjustment of corresponding management measures, especially attention to extremely critical factors affecting forecast demand, such as price. While from a short-term operational perspective, short-term demand forecasting can greatly improve hotel operational efficiency, such as optimizing resource allocation and dynamically adjusting prices. The proposed model not only achieves short-term demand forecasting, but also greatly improves the forecasting accuracy by considering factors related to competitors in the same region.

The originalities of the study are as follows. First, this study represents a pioneering attempt to incorporate demand, price and online rating of other hotels into the forecasting model. Second, integrated deep learning models based on GCN and gated recurrent unit complement existing predictive models using historical data in a methodological sense.

The purpose of this paper is to discuss published research in rotorcraft which has taken place in India during the last ten years. The helicopter research is divided into the following parts: health monitoring, smart rotor, design optimization, control, helicopter rotor dynamics, active control of structural response (ACSR) and helicopter design and development. Aspects of health monitoring and smart rotor are discussed in detail. Further work needed and areas for international collaboration are pointed out.

The archival journal papers on helicopter engineering published from India are obtained from databases and are studied and discussed. The contribution of the basic research to the state‐of‐the‐art in helicopter engineering science is brought out.

It is found that strong research capabilities have developed in rotor system health and usage monitoring, rotor blade design optimization, ACSR, composite rotor blades and smart rotor development. Furthermore, rotorcraft modeling and analysis aspects are highly developed with considerable manpower available and being generated in these areas.

Two helicopter projects leading to the “advanced light helicopter” and “light combat helicopter” have been completed by Hindustan Aeronautics Ltd These helicopter programs have benefited from the basic research and also provide platforms for further basic research and deeper industry academic collaborations. The development of well‐trained helicopter engineers is also attractive for international helicopter design and manufacturing companies. The basic research done needs to be further developed for practical and commercial applications.

This is the first comprehensive research on rotorcraft research in India, an important emerging market, manufacturing and sourcing destination for the industry.

Although intellectual capital (IC) and human dynamic capabilities (HDCs) play a significant role in decarbonization processes, their measurement and reporting is under-researched. Hence, this study aims to identify the link between HDCs, carbon accounting and integrated reporting (IR) in the transition processes, investigating IC and HDCs in decarbonization processes to achieve net-zero business models (n-ZBMs).

A systematic literature review with a concise bibliometric analysis is conducted on 229 articles, published from 1990 to 2023 in Scopus database and Google Scholar. Reviewing data on publications, journals, authors and citations and analysing the article content, this study identifies the main search trends, providing a new conceptual model and future research propositions.

The results reveal that the literature has rarely focussed on carbon accounting in terms of IC and HDCs. Additionally, firms face pressure from institutions and stakeholders regarding legitimacy and transparency, necessitating a response considering IR and requiring n-ZBMs to be developed through IC and HDCs to meet social and environmental requirements.

Not only does this study link IC with HDCs to address carbon emissions through decarbonization practices, which has never been addressed in the literature to date, but also provides novel recommendations and propositions through which firms can sustainably transition to being net-zero emission firms, thereby gaining competitive advantage and contributing to the nation’s sustainability goals.