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Subway systems are highly susceptible to external disturbances from emergencies, triggering a series of consequences such as the paralysis of the internal network transportation functions, causing significant economic and safety losses to cities. Therefore, it is necessary to analyze the factors affecting the resilience of the subway system to reduce the impact of disaster incidents.

Using the interval type-2 fuzzy linguistic term set and the K-medoids clustering algorithm, this paper improves the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to construct a subway resilience factor analysis model for emergencies. Through comparative analysis, this study confirms the superior performance of the proposed approach in enhancing the precision of the DEMATEL method.

The results indicate that the operation and management level of emergency command organizations is the key resilience factors of subway operations in China. Furthermore, based on real case analyses, the corresponding suggestions and measures are put forward to improve the overall operation resilience level of the subway.

This paper identifies four emergency scenarios and 15 resilience factors affecting subway operations through literature review and expert consultation. The improved fuzzy DEMATEL method is applied to explore the levels of influence and causal mechanisms among the resilience factors of the subway system under the four emergency scenarios.

While there was heightened awareness on the technologies of the fourth industrial revolution (IR 4.0) prior to COVID-19, studies have shown that the adoption of these advanced technologies (e.g. Big Data, robotics, Internet of Things, etc.) continues to remain low across global industries. This qualitative study sought to explore the reasons for the low rate of adoption of these technologies and appropriate measures to enhance their adoption at hotels, through the lens of hotel executives.

Based on interpretivist's ideals, this study follows a case study design and adopts a qualitative method of enquiry. The heterogenous purposive sampling technique was employed to gather data for the study, using semi-structured interviews.

Grounded on the technology-organisation-environment (TOE) framework, the thematic analysis revealed technology, organisation and environment-related reasons for the low rate of IR 4.0 technologies adoption at hotels in Malaysia. Also, the study uncovered some interesting measures that will enhance the adoption of these advanced technologies at hotels.

This study unearths technology, organisation and environment-related reasons for low adoption, and measures to enhance the adoption of IR 4.0 technologies in hotels. This study also enlightens hotel owners and technology providers about practical issues that will ensure the successful adoption of such technologies to enhance hotel business. In line with SDG 9, this study also seeks to promote sustainable innovation in the hospitality industry. Practical and theoretical implications have also been discussed in this study.

In the denim industry, enzyme washing and its combination with stone washing are generally used to get the desired worn-out look. However, these conventional methods include high water, energy and time consumption. Nowadays, laser fading, which is a computer-controlled, dry, ecological finishing method, is preferred in the denim fading process. The purpose of this study is to observe the effects of chemical pretreatment applications on laser-faded denim fabric in terms of color and mechanical properties. To eliminate the enzyme washing process in denim fading and to minimize the disadvantages of laser fading, such as decreased mechanical properties and increased fabric yellowness, various chemical pretreatment applications were applied to the denim fabric before laser fading, followed by simple rinsing instead of enzyme washing.

Two different indigo-dyed, organic cotton denim fabrics with different unit weights were exposed to pretreatment processes and then laser treatment, followed by simple rinsing. Polysilicic acid, boric acid, borax and bicarbonate were used for pretreatment processes, and laser treatment was carried out under optimized laser parameters (40 dpi resolution and 300 µs pixel time). Tensile strength was tested, and color values (CIE L*, a*, b*, ΔE*, C* and h), color yield (K/S), yellowness and whiteness indexes were measured to identify the color differences.

Before laser fading, 30 g/L and 40 g/L polysilicic acid pretreatments for sulfur-indigo-dyed fabric and a mixture of 10 g/L boric acid and 10 g/L borax pretreatments for the fabric only indigo-dyed were recommended for the laser fading with sufficient mechanical properties and good color values.

With the chemical pretreatments defined in this study, it was possible to reduce yellowness and maintain the mechanical properties after laser fading, thus minimizing the disadvantages of laser treatment and also eliminating enzyme washing.

The purpose of this paper is to improve the productivity and quality of the wire arc additive manufacturing process by benchmarking the strategies from the selected six strategies, namely, heat treatment process, inter pass cooling process, inter pass cold rolling process, peening process, friction stir processing and oscillation process.

To overcome the lack of certainty associated with correlations and relationships in quality functional deployment, fuzzy numbers have been integrated with the quality functional deployment framework. Twenty performance measures have been identified from the literature under five groups, namely, mechanical properties, physical properties, geometrical properties, cost and material properties. Using house of quality weights are allocated to performance measures and groups, relationships are established between performance measures and strategies, and correlations are assigned between strategies. Finally, for each strategy, relative importance, score and crisp values are calculated.

Inter pass cold rolling process strategy is computed with the highest crisp value of 15.80 which is followed by peening process, heat treatment process, friction stir processing, inter pass cooling process,] and oscillation process strategy.

To the best of the authors’ knowledge, there has been no research in the literature that analyzes the strategies to improve the quality and productivity of the wire arc additive manufacturing process.

This paper aims to investigate the influence of the regional business environment on local firm innovation, considering various dimensions such as administrative, financial and legal environments.

Multiple regression analysis is employed to analyze archival data for firms listed on Chinese stock markets.

We find that the optimizations of the administrative and financial environments positively affect firm innovation, whereas the legal environment does not exert a similar impact. Our analysis also reveals that the business environment’s optimization significantly influences innovation in firms that are small, non-state-owned and operating in high-tech industries. Furthermore, the business environment acts as a moderating variable in the relationship between firm innovation and firm value.

This study contributes to a more comprehensive understanding of institutional-level determinants of firm innovation, highlighting the nuances of the legal environment and the importance of context-specific analysis, especially in emerging markets like China.

Developing countries can significantly enhance firm innovation by improving the business environment, including the optimization of administrative and financial systems, reducing transaction costs and ensuring capital supply. Tailored legal frameworks and alternative institutional strategies may also be explored.

This study explicitly emphasizes the governmental role in promoting firm innovation, shedding light on policy formulation and strategic alignment with local administrative policies.

To the best of our knowledge, this paper is the first to explore the relationship between the business environment and firm innovation using World Bank indicators in an emerging market context, providing novel insights into the unique dynamics of legal, financial and administrative sub-environments.

This research investigates the impact of strategic research and development (R&D) (one led by a firm’s innovation orientation) on stock market performance during the economic disruption caused by the 2016 demonetization of high-value currency notes in India. It shows how firms’ strategic focus on innovation and integrated R&D initiatives can help mitigate shareholders’ losses and protect market value during negative macroeconomic shocks.

We analyzed financial and administrative data from firms listed in the Bombay Stock Exchange (BSE) 500 index and used the Fama French market model with appropriate instruments accounting for possible endogeneity to identify the impact. To ensure the reliability of our findings, we conducted robustness checks with alternate event windows, estimation methods, and variable measurements.

Strategic R&D plays a crucial role in building resilience against macroeconomic shocks. It effectively mitigated shareholders’ losses in the immediate aftermath of the shock, with an elasticity of abnormal returns of 7.65% on day zero, 13.1% during the first five days and 10.5% after the first fortnight. We also find that firms that are business-to-business (B2B), as well as those that are older and less leveraged, are better able to combat such a shock.

The study looked at one shock, namely demonetization. Future research is needed to demonstrate the generalizability of results during other macroeconomic shocks, like the COVID-19 pandemic. The study focuses on relatively near-term impacts, leaving the long-term value-creation effects of strategic R&D unexplored.

Innovation orientation acts as a structural enabler, allowing firms to make strategic R&D investments that mitigate losses during macroeconomic shocks. It explains that managers should avoid myopically managing R&D investments and align them with the firm’s innovation focus to enhance value creation.

While the currency demonetization was widely considered to be detrimental for firms as an unannounced negative monetary shock, our research shows that firms with high levels of strategic R&D were successfully able to counteract such a shock.

This is the first study to examine the short-term loss mitigation impact of firms’ focus on innovation and strategic R&D. It emphasizes the role of innovation-focused strategies during economic crises.

Sustainable development goals and the climate change agenda are becoming widely promoted topics of research for the 21st century. The role of cities is increasingly recognised as central to investigating these topics. Yet, the field of informal sector entrepreneurship which so many urban entrepreneurs in developing countries depend upon is seldom considered. To redress this imbalance, this study aims to develop a decision model in accordance with institutional theory (IT) and resource dependency theory (RDT) for city managers to deploy. The model identifies and prioritises optimal strategies to address the three areas of sustainability requirements environment society and economy within the study context of Bangladesh.

This study used a mixed methods research design. In the qualitative part, the authors identified the three areas of sustainability requirements (i.e. environment, society and economy) and their corresponding strategies involving the informal sector that operates within the urban environment. In the quantitative part, the authors applied fuzzy quality function deployment (QFD) integrated with the 0-1 non-linear optimisation technique to identify optimal strategies.

The findings show that strategies such as legitimate frameworks, waste management, allocation of urban public space and training programs contribute in important ways to the three areas of sustainability requirements.

The proposed decision model will assist policy-makers and city managers to prioritise sustainability requirements and implement optimal strategies to address those requirements.

Through the integration of IT and RDT, the decision model developed in this study is unique in its application to urban-based informal entrepreneurship in the context of developing countries. The effective application of the fuzzy QFD approach and the optimisation model in the context of urban-based informal entrepreneurship also offers unique contributions to the field of study.

In an effort to position higher education institutions to survive in this fiercely competitive environment, the paper aims to identify the direct and indirect relationships between higher education institutional positioning and exogenous factors (student engagement, employability, technology adaptation, teaching quality, and moral values).

A cross-sectional data was collected from 1,015 students studying in the pre-final year of graduation or post-graduate course/program from various educational institutions that were shortlisted based on the Indian NAAC and NIRF rankings. Thereafter, robust assessment criteria of PLS-SEM were used for model assessment and computation of results.

The findings revealed that to develop the greatest platform for upcoming young talent, higher educational institutional positioning ought to be addressed as a priority, which in turn will result in better living standards for upcoming generations.

Framing strategies for urban students can never match those living in rural areas, as they are deprived of money due to their level of upbringing from childhood, which creates a high difference in the psychological mindset of students while choosing a career path.

The higher positioning of educational institutions clearly reflects the authentic learning environment, with professionalism leading to better student engagement with best industry practice.

Research novelty is highlighted as a more focused and streamlined approach to students’ career development and institution branding by reanalyzing and grouping various concepts of institutional positioning into a single model.

This study aims to conduct an empirical investigation to assess the hedge, diversifier and safe-haven properties of different environmental, social and governance (ESG) assets (i.e. green bonds and ESG equity index) vis-à-vis conventional investments (namely, equity index, gold and commodities).

The authors examine the sample period 2007–2021 using the bivariate cross-quantilogram (CQG) analysis and a dynamic conditional correlation (DCC) multivariate generalized autoregressive conditional heteroskedasticity (GARCH) experiment with several extensions.

The evidence shows that the analyzed ESG investments exhibit mainly diversifying features depending on the asset class taken as a reference, with some potential hedging/safe-haven qualities (for the green bond) in peculiar timespans. Therefore, the results suggest that investors might consider sustainable investing as a new measure of risk reduction, which has interesting implications for both portfolio allocation and policy design.

To the best of the authors’ knowledge, this study is the first that empirically investigates at once the dependence between different ESG investments (i.e. equity and green bond) with different conventional investments such as gold, equity and commodity market indices over a large sample period (2007–2021). Well-suited methodologies like the bivariate CQG and the DCC multivariate GARCH are used to capture the spillover effect and the hedging/diversifying nature, even in temporary contexts. Finally, a global perspective is used.

The aim of this mixed methods study sought to investigate the preferences and challenges towards fourth industrial revolution (FIR) technologies adoption at hotels in Malaysia.

The study adopted partially-mixed concurrent quantitative-dominant mixed methods. The quantitative part of the study examined the preferred FIR technologies for hotels; whiles the qualitative part explored the challenges towards their adoption.

The results revealed that Internet of things, big data, cloud computing, artificial intelligence and cyber physical systems were the preferred FIR technologies for hotels. The findings revealed significant relationships between respondents' socio-demographic characteristics (age, gender, working experience, etc.) and preferred FIR technologies. Penultimately, challenges that affect the adoption of FIR technologies including investment cost, migration cost, trust, etc., were discussed.

In effect, findings from this study provide valuable information for policy makers (i.e. hotel owners, management, technology providers and future researchers). Most especially, the study unearths specific FIR technologies preferred by the hospitality and tourism industry. Also, the significant interplay of these preferences vis a vis respondents' socio-demographic characteristics, as well as challenges influencing their adoption also have major implications for policy makers. Another valuable contribution of this study lies in the research method utilised, since most studies on technology adoption either use quantitative or qualitative. These contributions for theory and practice have been thoroughly discussed.