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Introduction: Skills are vital for the survival of an organisation to meet its objectives through producing goods and services. Due to their importance, they are among the sought-after aspects of employment. However, organisations need more skilled employees to bridge the gaps due to disruptions, shifts in consumer demands and needs, and transformations in the global world.

Purpose of the Study: This study aims to identify various skill gap in talent, competencies, and experience emerging in the hospitality sector. It will also present some challenges to the hospitality sector that faces due to the skill gap identified.

Industrial and Academic Justification of the Study: The study examines the needs and challenges from academic and industry perspectives. Hence, it provides significance for academics and industry to apply the findings to address skill gap.

Research Gap: Previous research has focused on different aspects of skills in other countries. This study will look at the issue globally and the recent trends emerging from disruptions and shifts in consumer behaviour.

Results and Findings: Though the study is ongoing, the findings show that specific skill gap exist, particularly in emerging technologies, digitisation, data, robotics, and various job openings from different countries’ perspectives, hospitality, and the tourism industry.

Practical Implications: The findings have implications for the tourism and hospitality industry as a whole, as well as individual organisations. The tourism and hospitality industry should apply these suggestions, such as operational skills, digital skills, and interpersonal skills in various sections of tourism and hospitality organisations

Purpose: The study aims to explore the wider acceptance of blockchain technology and growing faith in this technology among all business domains to mitigate the chances of fraud in various sectors.

Design/Methodology/Approach: The authors focus on studies conducted during 2015–2022 using keywords such as blockchain, fraud detection and financial domain for Systematic Literature Review (SLR). The SLR approach entails two databases, namely, Scopus and IEEE Xplore, to seek relevant articles covering the effectiveness of blockchain technology in controlling financial fraud.

Findings: The findings of the research explored different types of business domains using blockchains in detecting fraud. They examined their effectiveness in other sectors such as insurance, banks, online transactions, real estate, credit card usage, etc.

Practical Implications: The results of this research highlight (1) the real-life applications of blockchain technology to secure the gateway for online transactions; (2) people from diverse backgrounds with different business objectives can strongly rely on blockchains to prevent fraud.

Originality/Value: The SLR conducted in this study assists in the identification of future avenues with practical implications, making researchers aware of the work so far carried out for checking the effectiveness of blockchain; however, it does not ignore the possibility of zero to less effectiveness in some businesses which is yet to be explored.

The purpose of this paper is to investigate the mediating roles of tacit and explicit knowledge sharing (KS) in linking the relationship between knowledge-based HRM practices and innovation competence of firms. This study also explores the potential moderating role of market turbulence in fostering the influence of KS behaviors on two forms of innovation competence namely radical innovation and incremental innovation.

The paper applied the quantitative approach and structural equation modeling to examine the correlation among the latent constructs based on the survey data collected from 293 participants in 115 firms.

The empirical findings of this study support the mediating role of KS behaviors in the relationship between knowledge-based HRM practices and aspects of innovation competence. It highlights the important role of market turbulence in stimulating the influence of KS behaviors on innovation capabilities.

Future research should investigate the impact of knowledge-based HRM practices on innovation capability via the mediating effects of knowledge management processes to bring better understanding of the importance of knowledge resources in organizations.

The paper significantly contributes to increasing knowledge and insights into the antecedent role of knowledge-based HRM practices, the mediating role of KS behaviors as well as the moderating role of market turbulence in fostering radical and incremental innovation, thereby advancing the body of comprehension of knowledge-based resources and innovation theory.

The purpose of the present article is to obtain the similarity solution for the shock wave generated by a piston propagating in a self-gravitating nonideal gas under the impact of azimuthal magnetic field for adiabatic and isothermal flows.

The Lie group theoretic method given by Sophus Lie is used to obtain the similarity solution in the present article.

Similarity solution with exponential law shock path is obtained for both ideal and nonideal gas cases. The effects on the flow variables, density ratio at the shock front and shock strength by the variation of the shock Cowling number, adiabatic index of the gas, gravitational parameter and nonidealness parameter are investigated. The shock strength decreases with an increase in the shock Cowling number, nonidealness parameter and adiabatic index, whereas the strength of the shock wave increases with an increase in gravitational parameter.

Propagation of shock wave with spherical geometry in a self-gravitating nonideal gas under the impact of azimuthal magnetic field for adiabatic and isothermal flows has not been studied by any author using the Lie group theoretic method.

In the present work, we focus on developing an in-house parallel meshless local Petrov-Galerkin (MLPG) code for the analysis of heat conduction in two-dimensional and three-dimensional regular as well as complex geometries.

The parallel MLPG code has been implemented using open multi-processing (OpenMP) application programming interface (API) on the shared memory multicore CPU architecture. Numerical simulations have been performed to find the critical regions of the serial code, and an OpenMP-based parallel MLPG code is developed, considering the critical regions of the sequential code.

Based on performance parameters such as speed-up and parallel efficiency, the credibility of the parallelization procedure has been established. Maximum speed-up and parallel efficiency are 10.94 and 0.92 for regular three-dimensional geometry (343,000 nodes). Results demonstrate the suitability of parallelization for larger nodes as parallel efficiency and speed-up are more for the larger nodes.

Few attempts have been made in parallel implementation of the MLPG method for solving large-scale industrial problems. Although the literature suggests that message-passing interface (MPI) based parallel MLPG codes have been developed, the OpenMP model has rarely been touched. This work is an attempt at the development of OpenMP-based parallel MLPG code for the very first time.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

This study aims to identify service quality dimensions for logistics service providers (LSPs) and to examine their relationships with customer satisfaction and customer loyalty.

Service quality dimensions are identified from vast literature review. Customers who take services from LSPs were surveyed to collect data on basis of developed survey instrument. Structural Equation Modelling (SEM) is applied to test the proposed research hypotheses.

The study shows that all the five service quality constructs, i.e. “Operational Quality”, “Resource Quality”, “Information Quality”, “Personnel Contact Quality” and “Customization and Innovation Quality” have direct relationship with customer satisfaction. They also have indirect relationship with customer loyalty, implying the full mediation of customer satisfaction.

The results of the study suggest that the logistics service quality (LSQ) can be measured multi-dimensionally. It provides clear implications to LSPs for improvement of service quality. The present research work is expected to be useful for both, logistics service providers and the customer organizations, which take services from LSPs. LSPs can develop strategies to improve their service quality on basis of findings from this study.

The present research will help in extending the existing literature on service quality in context to LSPs.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

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.

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.