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This paper aims to develop bilayer woven fabrics with different picking sequences with enhanced comfort without any change in the constituent materials.

Six bilayer woven fabrics were produced on Dobby loom with 3/1 twill weave using micro-polyester yarn. Three different picking sequences, i.e. single pick insertion (SPI), double pick insertion (DPI) and three pick insertion (3PI), were used in both face and back layers. The effect of picking sequence on air permeability (AP), volume porosity, thermal resistance and overall moisture management capability (OMMC) of the samples were analyzed.

The results showed that 3PI–3PI picking sequence gives the highest OMMC, AP and thermal resistance in bilayer woven fabrics and the least results exhibited by SPI–SPI picking sequence.

This research uses a bilayer woven system that develops channels and trapes the air causing higher thermal resistance; therefore, applicable for winter sports clothing rather than for summer wear. Developed bilayer woven fabrics can be used in winter sportswear to improve the comfort of the wearer and reduce fatigue during activity.

Authors have developed bilayer fabrics by changing the picking sequences, i.e. SPI, DPI and 3PI of weft yarns in both layers and compared their thermo-physiological comfort properties.

This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.

This work includes the development of 36 woven samples with two weave designs (1/1 plain and 3/1 twill), three picking sequences (single, double and three pick insertion) and six different weft yarn materials (cotton, polyester having 48 filaments, polyester with 144 filaments, spun coolmax having Lycra in core and coolmax in sheath, filament coolmax and polypropylene). The thermal conductivity was measured using ALAMBETA tester.

The results showed that weft yarn material, weave design and picking sequence have a meaningful impact on the thermal conductivity of woven fabric. The value of thermal conductivity was lowest for the fabrics with three pick insertion and 3/1 twill weave in all weft yarn materials.

Plain woven fabric with single pick insertion is feasible for summer wear to enhance the comfort of wearer. By changing the warp yarn grouping and material, improved thermal conductivity/resistance can also be achieved.

The authors have studied the combined effect of different weft yarn materials with different picking sequences and different weave designs on thermal conductivity of the woven fabrics.

The study aims to examine the relationship between personality traits and investor risk behavior of the individuals trading in stock markets. Furthermore, this study establishes the association of financial literacy on the relationship between personality traits and investor risk behavior.

The authors analyze cross-sectional survey method data by using moderated multiple regression analysis, a standard method of determining the moderation effect. PROCESS Model method has been used in this study to check the robustness of the results.

The findings reveal that personality traits significantly influence investor risk behavior and financial literacy modifies the fundamental relationships between personality traits and investor risk behavior. The findings also conclude that behavioral impact was predetermined by individuals' genetic traits and is influenced by financial literacy.

The current study provides valuable insights for investors and adamant grounds for future research. The two-fold role of individuals' personalities in case of gains and losses can be of interest to the researchers in future.

Investors currently facing the complex financial choices which are far beyond the day-to-day financial advice. This study guides rational investment behavior for portfolio managers and investors for advanced investment options.

Most of the prior literature is based on developed markets, whereas the current study focuses on less literate society (i.e. Pakistan) to protect the investors from scams and fraud. The current study supports the vital role of investors in the socio-economic development of emerging markets.

The authors believe this study expands the boundaries of personality theories, especially in the context of risk behavior and financial literacy. The study also contributes to advancing the personality theory trimmed with financial literacy and investor behavior while making important theoretical inroads for future research.

This research examines the role of green, inclusive leadership, corporate social responsibility, and pro-environmental attitudes on proactive pro-environmental behaviour among hotel employees. It further examines the indirect effects of pro-environmental attitudes between green inclusive leadership, corporate social responsibility, and proactive pro-environmental behaviour, as well as the moderating role of psychological contract breach between pro-environmental attitudes and proactive pro-environmental behaviour.

The participants of this cross-sectional study were employees in the Malaysian hotel industry, and 374 usable questionnaires were used for data analysis. The data were analysed using Partial Least Squares – Structural Equation Modelling.

This study found that green, inclusive leadership, corporate social responsibility, and pro-environmental attitudes significantly influence proactive pro-environmental behaviour. For mediating effects, pro-environmental attitudes have been found to mediate the relationship between corporate social responsibility, green inclusive leadership and proactive pro-environmental behaviour.

The research proposes actionable measures to encourage environmentally friendly practices in the hotel sector. For companies to succeed, they must integrate green initiatives with their societal objectives. Pro-environmental mindsets are essential for implementing effective environmental policies, which in turn impact recruitment approaches. The advantages of fostering pro-environmental conduct encompass financial savings, enhanced standing, adherence to regulations, increased innovative thinking and improved workplace well-being.

Over time, environmental degradation has been contributed by individual behaviours and the combined actions of businesses and organisations. This study significantly contributed to a new model underpinned by the Self-determination Theory by including new constructs influencing proactive pro-environmental behaviour.

The purpose of this study is to examine the role of knowledge management practices, organisational commitment and capacity building on employee performance in the hotel industry. This study also investigated the mediating role of organisational commitment and capacity building between knowledge management practices and employee performance.

A quantitative approach and questionnaire survey were used to collect data from hotel employees from Malaysia. Self-administered questionnaires were distributed to collect data from 291 participants, and partial least squares structural equation modelling was used to analyse the hypotheses.

The results of this study confirm that knowledge management practices positively and significantly affect knowledge-employee performance. Employees achieve this performance through the mediating influence of organisational commitment and capacity building culture.

This study offers several implications for Malaysian practitioners and policymakers regarding learning and knowledge management practices in the hospitality industry. The results suggest that organisations can manage knowledge assets and key processes of the organisational environment to create and use knowledge to improve sustainable employee performance through knowledge management practices.

This study sheds light on the knowledge management literature by examining the effect of knowledge management practices on organisational commitment, particularly in the hospitality industry in Malaysia.

This study aims to explore the impact of the chief executive officer’s (CEO) age on adopting global reporting initiative (GRI) framework for corporate social responsibility (CSR) reporting. It also underlines how board social capital moderates the relationship between CEO age and the adoption of the GRI framework.

Chinese A-listed companies during 2010–2018 were used. The authors applied a logistic regression model due to the binary nature of the dependent variable. For robustness, two-step generalized method of moments (GMM) and lagged independent variables are used.

The study finds that CEO age negatively impacts the firm’s choice of GRI reporting framework. The social capital of the board positively moderates this relationship. This finding is based on the notion that as a CEO grows older or headed toward retirement age, his/her interest in CSR diminishes due to a shorter career horizon. Boards with external links provide better advice on CSR issues and mitigate the negative impact of CEO age.

The study results are important for understanding the GRI framework’s development and implementation, particularly in China.

To the best of the authors’ knowledge, this is the first study that deeply examines how CEO age affects GRI adoption in the Chinese context and how the board’s social capital moderates this relationship.

This study aims to explore how organisations use institutional language in Green Bond reports to explain and justify their activities using language that describes and reflects narratives while simultaneously constructing and shaping ideology. The paper mobilises Wodak and Meyer’s critical discourse analysis (CDA) to examine reports and related documentation relating to Green Bonds issued in France.

The study uses three legitimating discourses: technocratic, environmental and social and business performance to develop a linguistic perspective that permits contributions to existing knowledge in the area.

The analysis attempts to identify the discursive strategies used to legitimise Green Bond issuance via claims linked to environmental management improvements and business activities’ social impact.

The study contributes to the critical literature on organisational legitimation and responsibility, investigations of Green Bond narratives and an understanding of broader environmental reporting in the financial sector.

The purpose of this study, thermal radiation and viscous dissipation impacts on double diffusive convection on peristaltic transport of Williamson nanofluid due to induced magnetic field in a tapered channel is examined. The study of propulsion system is on the rise in aerospace research. In spacecraft technology, the propulsion system uses high-temperature heat transmission governed through thermal radiation process. This study will help in assessment of chyme movement in the gastrointestinal tract and also in regulating the intensity of magnetic field of the blood flow during surgery.

The brief mathematical modelling, along with induced magnetic field, of Williamson nanofluid is given. The governing equations are reduced to dimensionless form by using appropriate transformations. Numerical technique is manipulated to solve the highly nonlinear differential equations. The roll of different variables is graphically analyzed in terms of concentration, temperature, volume fraction of nanoparticles, axial-induced magnetic field, magnetic force function, stream functions, pressure rise and pressure gradient.

The key finding from the analysis above can be summed up as follows: the temperature profile decreases and concentration profile increases due to the rising impact of thermal radiation. Brownian motion parameter has a reducing influence on nanoparticle concentration due to massive transfer of nanoparticles from a hot zone to a cool region, which causes a decrease in concentration profile· The pressure rise enhances due to rising values of thermophoresis and thermal Grashof number in retrograde pumping, free pumping and copumping region.

To the best of the authors’ knowledge, a study that integrates double-diffusion convection with thermal radiation, viscous dissipation and induced magnetic field on peristaltic flow of Williamson nanofluid with a channel that is asymmetric has not been carried out so far.

Identifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.

A numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.

The results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.

This workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.

This paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.