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The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

Carpal tunnel syndrome (CTS) is a hand disease caused by the pressing of the median nerve present in the palmar side of the wrist. It causes severe pain in the wrist, triggering disturbance during sleep. Different products like splints, braces and gloves are available in the market to alleviate this disease but there was still a need to improve the wearability, comfort and cost of the product. This study was about designing a comfortable and cost-effective wearable system for mild-to-moderate CTS. Transcutaneous electrical nerve stimulation (TENS) therapy has been used to reduce the pain in the wrist.

After simulation by using Proteus software (which allowed the researchers to draw and simulate electrical circuits using ISIS, ARES and PCB design tools virtually), the circuit with optimum frequency, i.e. 33 Hz was selected, and the circuit was developed on a printed circuit board (PCB). The developed circuit was integrated successfully into the half glove structure.

The developed product had good thermophysiological comfort and hand properties as compared to the commercially available product of the same kind. In vivo testing (It involves the testing with living subjects like animals, plants or human beings) was performed which resulted in 85% confirmed viability of the product against CTS. A glove with an integrated circuit was developed successfully to accommodate various sizes without any sex specifications in a cost-effective way to mitigate the issue of CTS.

Industrial workers, individuals frequently using their hands or those diagnosed with CTS may wish to use this product as therapy. The attention could not be paid to the aesthetic or visual appeal of the developed product.

A very comfortable glove with integrated TENS electrodes was developed successfully to accommodate various sizes without any sex specifications in a cost-effective way to mitigate the issues of CTS.

This study aims to investigate the impact of corporate diversification and growth opportunities on the performance of real estate investment trusts (REIT) in Malaysia and Singapore before and during the pandemic.

The sample consists of 33 public-listed REITs across Singapore and Malaysia. A dynamic panel system generalized method of moments (DPS-GMM) estimation is used to account for unobservable factors and a relatively short sample period (2009–2022).

Results indicate that the impact of diversification is contingent on the market where the REIT is based and other institutional factors. The estimates also show that diversified REITs are better able to weather period of economic uncertainty.

We provided a definitive answer as to why corporate diversification leads to conflicting outcomes – market and institutional factors, strategic intent and the overall economic environment. We also show that the impact of typical firm controls (i.e. free cash, size) can differ. Future firm-level work should thus study similar phenomenon more contextually and carefully consider these varying effects.

The literature is divided on the impact of diversification on firm performance. By using a two-country sample, we show conclusive evidence that this contradictory outcome is due to market and institutional factors. We also show evidence that strategic intent is an important factor that influences the outcomes of diversification, regardless of market. We also infer that excess cash aids the resilience of the firm, contrary to the negative perception of excess cash during normal times. Firm size, in contrast, does not contribute to firm performance during a crisis.

This study aims to identify an automated machine learning algorithm with high accuracy that sport practitioners can use to identify the specific factors for predicting Major League Baseball (MLB) attendance. Furthermore, by predicting spectators for each league (American League and National League) and division in MLB, the authors will identify the specific factors that increase accuracy, discuss them and provide implications for marketing strategies for academics and practitioners in sport.

This study used six years of daily MLB game data (2014–2019). All data were collected as predictors, such as game performance, weather and unemployment rate. Also, the attendance rate was obtained as an observation variable. The Random Forest, Lasso regression models and XGBoost were used to build the prediction model, and the analysis was conducted using Python 3.7.

The RMSE value was 0.14, and the R2 was 0.62 as a consequence of fine-tuning the tuning parameters of the XGBoost model, which had the best performance in forecasting the attendance rate. The most influential variables in the model are “Rank” of 0.247 and “Day of the week”, “Home team” and “Day/Night game” were shown as influential variables in order. The result was shown that the “Unemployment rate”, as a macroeconomic factor, has a value of 0.06 and weather factors were a total value of 0.147.

This research highlights unemployment rate as a determinant affecting MLB game attendance rates. Beyond contextual elements such as climate, the findings of this study underscore the significance of economic factors, particularly unemployment rates, necessitating further investigation into these factors to gain a more comprehensive understanding of game attendance.

This study examines the relationship between multi-layer supply chain flexibility (MSCF) and Supply chain resilience (SCR). Further, it looks at the moderating effect of environmental dynamism (ED) and supply chain risks (SCRI) on the relationship between MSCF and SCR.

Executives from the pharmaceutical, agri-food, electronics, automobile and textile industries were invited to complete a self-administered questionnaire. We received feedback from a total of 302 participants. Prior to conducting the primary analysis, we addressed the potential for nonresponse bias and verified the assumptions of homoscedasticity and normal distribution of the data. The reliability and validity of the constructs were established through confirmatory factor analysis. Structural equation modelling is employed for the purpose of conducting hypothesis testing.

The results demonstrate a notable influence of MSCF on SCR, particularly in settings characterized by high levels of ED and SCRI. The study highlights the importance of flexibility in multiple aspects of the supply chain to build resilience against a range of disruptions and uncertainties.

The study presents the fundamental role of Multi-Layer Flexibility in building up SCR. The results of this study reinforce the existing literature and offers empirical evidence for how ED, SCRI moderates the influence between MSCF to SCR. These results offer valuable information to both supply chain specialists and researchers for building comprehensive strategy to bring resilience in supply chains.

Drawing on social capital theory, this study aims to explore the effect of corporate social responsibility (CSR) on organizational resilience. The research investigates the mediating role of relationship quality in the association of CSR with organizational resilience, and the moderating role of data-driven culture in the association between CSR and relationship quality.

Data were collected from Chinese agricultural firms with a sample of 241 senior or middle executives and structural equation modeling was used to test the research model and hypotheses.

The results indicate that CSR positively affects the relationship quality between agribusinesses and farmers, which in turn positively affects both proactive resilience and reactive resilience. Relationship quality has a partial mediating role in the association of CSR with proactive resilience and reactive resilience. Data-driven culture has a positive moderating effect on the relationship between CSR and relationship quality.

By arguing for CSR toward organizational resilience and analyzing its underlying mechanism, this study enriches the literature on CSR and organizational resilience and expands the existing knowledge on the roles of relationship quality and data-driven culture. This study also provides practical insights into how to improve organizational resilience.

This study empirically examines the impact of climate change and agricultural research and development (R&D) as well as their interaction on agricultural productivity in 12 selected Asian and Pacific countries over the period of 1990–2018.

Various estimation methods for panel data, including Fixed Effects (FE), the Feasible Generalized Least Squares (FGLS) and two-step System Generalized Method of Moments (SGMM) were used.

Results show that both proxies of climate change – temperature and precipitation – have negative impacts on agricultural productivity. Notably, agricultural R&D investments not only increase agricultural productivity but also mitigate the detrimental impact of climate change proxied by temperature on agricultural productivity. Interestingly, climate change proxied by precipitation initially reduces agricultural productivity until a threshold of agricultural R&D beyond which precipitation increases agricultural productivity.

The findings imply useful policies to boost agricultural productivity by using R&D in the context of rising climate change in the vulnerable continent.

This study contributes to the literature in two ways. First, this study examines how climate change affects agricultural productivity in Asian and Pacific countries – those are most vulnerable to climate change. Second, this study assesses the role of R&D in improving agricultural productivity as well as its moderating effect in reducing the harmful impact of climate change on agricultural productivity.

Proenvironmental hotels and hotels with green initiatives are emerging as a method to address environmental issues and respond to tourists’ environmental concerns. To better understand what can encourage reservations in proenvironmental hotels, this study aims to investigate the connection between the performing arts watching experience and the preference for such a hotel.

Five scenario-based experiments were conducted. A total of 1,024 participants for the five studies were recruited with the help of Credamo, a commonly used Chinese data collection platform.

The results indicated that viewing performing arts could increase tourists’ preferences for proenvironmental hotels. This phenomenon occurred due to the fact that performing arts watching experience can induce a psychological state of self-transcendence in individuals, which, in turn, can raise their levels of altruism, and ultimately lead to proenvironmental hotel choices. This effect will not occur, however, when people watch performing arts with either an extrinsic motivation or in an analytical state.

The findings of this study provide hotel managers with a novel approach to market the proenvironmental attributes of their hotels and to promote tourists’ proenvironmental behaviors.

This study proposes performing arts viewing experiences as a novel way to encourage proenvironmental hotel choice. To the best of the authors’ knowledge, this is the first study to explore the impact of the performing arts watching experience on tourist behavior.

This study aims to explore the heterogeneity of the tourist market for people with a physical disability (PwPD) based on travel barriers, to serve them better, from a tourism marketing perspective.

A market segmentation analysis was conducted on a sample of 480 PwPD in Sichuan Province, China, based on their perceived travel barriers. Data were obtained through three on-site and four online surveys. A four-step factor-item mixed segmentation, including factor analysis, cluster analysis, discriminant analysis and chi-square tests, was applied to examine the differences among PwPD tourist market segments in terms of various demographic characteristics, disability conditions (e.g. duration of disabilities and causes of impairment) and travel features (e.g. travel frequency and tourist destinations).

This study revealed that the PwPD tourist market is heterogeneous due to individual perceived travel barriers. Three market segments were identified, namely, the Explorer Moderates group, the Explorer Minimals group and the Explorer Intensives group. Additionally, the three market segments were found to have significant differences in terms of travel barriers, demographic characteristics, travel features and disability conditions.

This research provides suggestions for authorities and private entities to optimize the layout of accessible facilities in public areas for the benefit of all. It also offers crucial implications for tourism marketers to determine the key facets of marketing, for travel organizers to evolve the organization of travel groups for PwPD, and for practitioners to provide personalized tourism services.

To the best of the authors’ knowledge, this study is the first to apply perceived travel barriers as a market segmentation criterion in understanding PwPD as a heterogeneous travel market. The findings of this study initially expand the scope of application of the travel barrier model and deepen understanding of the Chinese PwPD tourist market from a marketing perspective. The study results elucidated the heterogeneity and characteristics of this market through a four-step factor-item mixed segmentation approach, offering new insights into the behaviors and experiences of travelers with disabilities.

本研究旨在探索肢体残障人士旅游市场的异质性, 以便从旅游营销的角度更好地为他们服务。

基于对中国四川480名肢残人士出游障碍感知的问卷调查, 探索了肢残人士的旅游市场细分。数据是通过七次现场和在线调查获得; 采用四步因子-项目混合细分法, 根据残障状况、人口统计特征和旅游特征, 识别出肢残群体旅游细分市场之间的差异。

研究发现, 基于个体感知的出游障碍, 肢残群体旅游市场是异质的, 研究确定了三个细分市场, 即低度、中度和高度受限群体。三个细分市场在出行障碍、人口特征、出游特征和残障状况方面存在显著差异。

这项研究有助于政府管理部门优化公共区域无障碍设施布局; 旅游营销者确定营销的重点, 并为旅游组织者设计肢残旅游团体成员构成, 以及从业者提供个性化旅游服务提供重要的启示。

论文首次将感知出游障碍作为市场细分标准, 用以理解肢残群体作为异质游客市场。本研究的发现拓展了出游障碍模型的应用范围, 并从市场营销的角度加深了对中国肢残游客市场的理解。研究结果通过四步因子-项目混合细分方法阐明了该市场的异质性和特点, 为肢残游客的行为和体验研究提供了新见解。

Este estudio explora la heterogeneidad del mercado turístico de las personas con discapacidad física (PcDF) en función de las barreras percibidas para viajar, con el fin de prestarles un mejor servicio desde una perspectiva de marketing turístico.

Se realizó un análisis de segmentación de mercado en una muestra de 480 PcDF en Sichuan, China, en función de las barreras que percibían para viajar. Los datos se obtuvieron a través de tres encuestas in situ y cuatro encuestas en línea. Se aplicó una segmentación mixta factor-ítem de cuatro pasos que incluye análisis factorial, análisis de conglomerados, análisis discriminante y pruebas de chi-cuadrado para examinar las diferencias entre los segmentos del mercado turístico de PcDF, en términos de diversas características demográficas, condiciones de discapacidad (por ejemplo, duración de la discapacidad, causas de la discapacidad) y características de los viajes (por ejemplo, frecuencia de viaje, destinos turísticos).

Este estudio reveló que el mercado turístico de las PcDF es heterogéneo debido a las barreras de viaje percibidas por cada individuo. Se identificaron tres segmentos de mercado, a saber, el grupo de Exploradores Moderados, el grupo de Exploradores Mínimos y el grupo de Exploradores Intensivos. Los tres segmentos de mercado presentaban diferencias significativas en cuanto a las barreras para viajar, las características demográficas, las características del viaje y las condiciones de discapacidad.

Este estudio es el primero en aplicar las barreras percibidas para viajar como criterio de segmentación de mercado para comprender a las PcDF como un mercado turístico heterogéneo. Los hallazgos de este estudio amplían inicialmente el ámbito de aplicación del modelo de barreras para viajar y profundizan en la comprensión del mercado turístico chino de PcDF desde una perspectiva de marketing. Los resultados de nuestro estudio explicaron la heterogeneidad y las características de este mercado a través de un enfoque de segmentación mixta factor-ítem de cuatro pasos, contribuyendo a la literatura sobre el comportamiento y las experiencias de los viajeros con discapacidad.

Esta investigación proporciona sugerencias para que las autoridades y las entidades privadas puedan optimizar la disposición de instalaciones accesibles en zonas públicas en beneficio de todos. También ofrece implicaciones importantes a los comercializadores turísticos para que determinen aspectos clave del marketing, a los organizadores de viajes para que evolucionen en la organización de grupos de viaje para PcDF y a los profesionales para que presten servicios turísticos personalizados.