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This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

Purpose: The hospitality industry faces several contemporary issues and challenges that have the potential to impact its growth and development. This study aims to identify and analyse contemporary issues and challenges facing the hospitality industry, including trends, regulations, and Tech salutation.

Need for the study: The hospitality industry plays a significant role in the global economy with its diverse services, including accommodation, food and beverage, events, and tourism. However, the sector faces several contemporary issues and challenges that have the potential to impact its growth and development. This study will provide an overview of the most significant problems and challenges facing the hospitality industry today.

Methodology: The researchers used secondary data for the analysis of the chapter. The researchers reviewed journal papers, books, book chapters, government websites, handbooks, reports, internet, and official records for identification of issues and challenges in the hospitality industry.

Findings: The study identified several contemporary issues and challenges facing the hospitality industry, including the impact of technology and COVID-19 on operations and customer experience, changing consumer preferences for sustainable and ethical practices, labour shortages and retention issues, increasing competition, and changing regulatory environments.

Practical implications: The hospitality industry faces numerous contemporary issues and challenges that impact its sustainability and profitability. Industry stakeholders must understand and address these challenges to remain competitive and relevant in a rapidly changing global market. The findings of this study provide valuable insights into the contemporary issues and challenges facing the hospitality industry and suggest potential strategies for addressing these challenges.

In this paper, the standard Peridynamic Timoshenko beam model accounting for the shear deformation is chosen to describe the thick beam kinematics. Unfortunately, when applied to very thin beam structures, the standard Peridynamics (PD) encounters the shear locking phenomenon, leading to incorrect solutions.

PD differs from classical continuum mechanics and other nonlocal theories that do not involve spatial derivatives of the displacement field. PD is based on the integral equation instead of differential equations to handle discontinuities and other singularities.

The shear locking can be successfully alleviated using the developed selective integration method. In particular, this technique has been implemented in the standard PD, which allows an accurate result for a wide range of slenderness from very thin to thick (10 < L/t < 10³) structures. It can also accelerate the computational time for particular dynamic problems using fewer neighboring integration particles. Several numerical examples are solved to demonstrate the effectiveness of the proposed method for modeling beam structures.

The paper highlights the severe shear locking phenomenon in the Peridynamic Timoshenko beam available in the literature, especially for very thin structures. A new alternative for the alleviation of shear locking in the Peridynamic Timoshenko beam, using selective integration. Hence the developed Peridynamic Timoshenko beam model is effective for thin and thick structures. A new peridynamic formulation for the low-velocity impact beam models is presented and validated.

1. The paper highlights the severe shear locking phenomenon in the Peridynamic Timoshenko beam proposed in the literature, especially for very thin structures.

2. The developed Peridynamic Timoshenko beam model based on selective integration is effective for thin and thick structures.

3. A new peridynamic formulation for the low-velocity impact beam models is presented and validated.

The paper highlights the severe shear locking phenomenon in the Peridynamic Timoshenko beam proposed in the literature, especially for very thin structures.

The developed Peridynamic Timoshenko beam model based on selective integration is effective for thin and thick structures.

A new peridynamic formulation for the low-velocity impact beam models is presented and validated.

In an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance. Our study delves into this complex backdrop, focusing on the intricate interplay the between traditional and emerging energy sectors.

This study analyzes the interconnections among green financial assets, renewable energy markets, the geopolitical risk index and cryptocurrency carbon emissions from December 19, 2017 to February 15, 2023. We investigate these relationships using a novel time-frequency connectedness approach and machine learning methodology.

Our findings reveal that green energy stocks, except the PBW, exhibit the highest net transmission of volatility, followed by COAL. In contrast, CARBON emerges as the primary net recipient of volatility, followed by fuel energy assets. The frequency decomposition results also indicate that the long-term components serve as the primary source of directional volatility spillover, suggesting that volatility transmission among green stocks and energy assets tends to occur over a more extended period. The SHapley additive exPlanations (SHAP) results show that the green and fuel energy markets are negatively connected with geopolitical risks (GPRs). The results obtained through the SHAP analysis confirm the novel time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness findings. The CARBON and PBW markets consistently experience spillover shocks from other markets in short and long-term horizons. The role of crude oil as a receiver or transmitter of shocks varies over time.

Green financial assets and clean energy play significant roles in the financial markets and reduce geopolitical risk. Our study employs a time-frequency connectedness approach to assess the interconnections among four markets' families: fuel, renewable energy, green stocks and carbon markets. We utilize the novel TVP-VAR approach, which allows for flexibility and enables us to measure net pairwise connectedness in both short and long-term horizons.

The purpose of this paper is to provide a comprehensive review of a non-contact full-field optical measurement technique known as digital image correlation (DIC).

The approach of this review paper is to introduce the research pertaining to DIC. It comprehensively covers crucial facets including its principles, historical development, core challenges, current research status and practical applications. Additionally, it delves into unresolved issues and outlines future research objectives.

The findings of this review encompass essential aspects of DIC, including core issues like the subpixel registration algorithm, camera calibration, measurement of surface deformation in 3D complex structures and applications in ultra-high-temperature settings. Additionally, the review presents the prevailing strategies for addressing these challenges, the most recent advancements in DIC applications across quasi-static, dynamic, ultra-high-temperature, large-scale and micro-scale engineering domains, along with key directions for future research endeavors.

This review holds a substantial value as it furnishes a comprehensive and in-depth introduction to DIC, while also spotlighting its prospective applications.

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.

The ballooning health misinformation on social media raises grave concerns. Drawing upon the S-O-R (Stimulus-Organism-Response) model and the information processing literature, this study aims to explore (1) how social media health information seeking (S) affects health misinformation sharing intention (R) through the channel of health misperceptions (O) and (2) whether the mediation process would be contingent upon different information processing predispositions.

Data were collected from a survey comprising 388 respondents from the Chinese middle-aged or above group, one of China's most susceptible populations to health misinformation. Standard multiple linear regression models and the PROCESS Macro were adopted to examine the direct effect and the moderated mediation model.

Results bolstered the S-O-R-based mechanism, in which health misperceptions mediated social media health information seeking's effect on health misinformation sharing intention. As an indicator of analytical information processing, need for cognition (NFC) failed to moderate the mediation process. Contrarily, faith in intuition (FI), an indicator reflecting intuitive information processing, served as a significant moderator. The positive association between social media health information seeking and misperceptions was stronger among respondents with low FI.

This study sheds light on health misinformation sharing research by bridging health information seeking, information internalization and information sharing. Moreover, the authors extended the S-O-R model by integrating information processing predispositions, which differs this study from previous literature and advances the extant understanding of how information processing styles work in the face of online health misinformation. The particular age group and the Chinese context further inform context-specific implications regarding online health misinformation regulation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0157.

The study aims to identify, analyse and develop a model for measuring the inter-relationship and interaction among the inter-partner factors. International joint ventures (IJVs) literature has scantly studied the interactions and inter-relationships among the inter-partner factors of IJVs performance. To address this gap, this research creates a hierarchical relationship framework among the inter-partner factors of IJVs performance.

The comprehensive literature review is used to identify the factors and possible relationships between the factors and IJVs performance. M-TISM (modified total interpretive structural modelling) methodology is used to examine the relationship among the factors of IJVs performance.

This study highlights 12 inter-partner factors that affect IJVs performance. The results suggest that size asymmetry, commitment, goal incongruency, competitive overlap, trust, control, the interdependency of resources, cooperation, economic distance, cultural distance, geographical distance and administrative distance significantly impact IJVs performance. Commitment is found to be a linkage variable as it has high dependence and driving power. Goal incongruency and competitive overlap have high driving power.

This study gives a proposed list of critical inter-partner factors for policymakers and practitioners to consider when developing rules or recommendations to improve IJVs performance. The focus of policymakers should be on economic and geographical distance, followed by cultural distance, competitive overlap, goal incongruency, size asymmetry and administrative distance to improve inter-relationship among the partners in IJVs. The work contributes to the academician by presenting a modified TISM model that highlights the significance of ambidexterity in driving the performance of IJVs.

This study fills a gap in the literature by analysing the interactions among the inter-partner parameters that influence the performance of IJVs. It offers insights into the variables, such as driver dependence and the relationships between the variables.

The COVID-19 pandemic has transformed consumer buying behavior across the world. COVID-19 crisis brought a behavioral change in consumers' attitudes toward health, financial and social well-being. The current research work highlights the factors influencing consumer buying behavior during the COVID-19 pandemic considering saving and safety perspectives.

This study attempts to understand the gap in buying behavior with reference to saving and safety. Survey-based study was conducted during the second phase of COVID-19, and the respondents were those who lived in highly affected COVID cities in India. Exploratory factor analysis and multiple regression analysis were carried out for testing the hypotheses.

Seven factors became the prominent factors in consumer buying patterns during the pandemic. Consumers in the times of COVID-19 pandemic spend only on essential items as compared to nice-to-have and non-essential items.

Respondents considered in the research were millennials aged 25–40. The current research is limited to specific geographic location.

The study assessed how savings and safety influence consumer buying behavior. The 2S framework model for consumer buying behavior during pandemic has been developed. The findings of the study provides a road map to the companies, policy makers, managers and consumers in understanding the consumer buying behavior during pandemic.

The current research work observe the changes in the behavioral patterns of consumers in the context of 2S framework, i.e. saving and safety. This study offer novel contribution as there is no available literature that examined the saving and safety aspects together for consumer buying behavior during crisis.