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This study aims to identify the impact of intellectual capital (IC) on the bank’s performance using a cross-country approach with India and Gulf Cooperation Council (GCC) countries using the Skandia navigator model (SNM).

This study uses a mixed-methods research approach by taking financial and non-financial measures to assess the impact of the IC on the bank’s performance using the SNM. The study implies an analysis of the data from the top ten banks in India and twenty banks in GCC countries. The selection was done based on the volume of the bank’s business for three years (2019–2020, 2020–2021 and 2021–2022).

The research has three main findings: there is a positive impact of IC on the bank’s performance; amongst the factors of SNM, there is a direct impact of human capital and customer focus on the performance of the selected banks in both India and GCC countries; and the other factors of SNM such as structural capital and process focus, renewal and development focus also affect the selected banks.

The outcomes of the research may be useful for policymakers in India and GCC countries, as it identifies IC components that have a significant impact on the bank’s performance. This might enable them to develop policies that foster such factors, which, consequently, will improve the performance of the banks in the selected countries.

This study is an attempt to fill the gap in the existing literature on IC and bank’s performance for two different types of countries using the SNM.

This paper aims to examine the influence of environmental concerns and consumers’ knowledge of green brands on their purchasing decisions of green products, utilising green trust as a mediator.

Responses from 383 Indian consumers were collected, which was analysed using descriptive and inferential statistics. The causal relationships between latent variables and mediating effect of green trust were investigated by performing Structural Equation modelling.

Green trust served as a crucial factor in mediating the relationship between environmental concern and green purchase decision. Trust in eco-friendly products significantly influenced the consumers’ decisions to make green purchases. The study further validated that environmental concern significantly influences individuals’ decisions to make green purchases.

The study employed a cross-sectional research design to elucidate the relationship among the factors. However, a longitudinal research design is recommended for further study to ascertain the actual purchase decision and evaluate the reliability of the results.

Marketers can use the study findings to understand consumer knowledge better and trust in green and sustainable products. The proposed model will support marketers and policymakers in developing appropriate marketing strategies as well as facilitate educating consumers about the nuances of green products and the habit of buying eco-friendly products.

Study’s novel contribution is mediation between environmental concern and green purchase decision through green trust.

This study aimed to develop a mathematical model for delamination and surface roughness during end milling by using grey relational analysis (GRA) and to determine how the input parameters (cutting speed, depth of cut, helix angle and feed rate) influence the output response (delamination and surface roughness) in machining of hybrid glass fibre-reinforced plastic (GFRP) (abaca and glass) composite using solid carbide end mill cutter.

The Four factors, three levels Taguchi orthogonal array design in GRA is used to conduct the experimental investigation. The Shop Vision inspection system is used to measure the width of maximum damage of the machined hybrid GFRP composite. The Shop Handysurf E-35A surface roughness tester is used to measure the surface roughness of the machined hybrid GFRP composite. “Minitab 14” is used to analyse the data collected graphically. Analysis of variance is conducted to validate the model in determining the most significant parameter.

The GRA is used to predict the input factors influencing the delamination and surface roughness on the machined surfaces of the hybrid GFRP composite at different cutting conditions with the chosen range of 95 per cent confidence intervals. Analysis on the influences of the entire individual input machining parameters on the delamination and surface roughness has been conducted using GRA.

Effect of milling of the hybrid GFRP composite on delamination and surface roughness with various helix angle solid carbide end mill has not been analysed yet using the GRA technique.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

Implementing food safety measures (FSMs) have become a prerequisite for food firms looking to export internationally. Many exporters find it difficult to comply with multiple regulations, and their consignments are often rejected at borders due to food safety concerns. Hence, harmonization in food safety standards is arguably the most contentious topic regarding the export market since it affects international trade. Accordingly, the paper uses the case of Indian seafood exporters to identify key FSMs, investigate stringency associated with them and rank international markets based on degree of stringency for selected FSMs.

First, the authors identify the key FSMs by using the Delphi method. Then, the authors apply the Fuzzy analytical hierarchical process (FAHP) method to calculate weights of the FSMs as criteria. Lastly, the authors apply the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach to rank markets. To compute fuzzy TOPSIS, weights are derived from fuzzy AHP.

This study’s findings suggest that product and process standards, traceability requirements and tolerance limits for residues are the most stringent FSMs, among others. Besides, the overall ranking of markets reveal that the European Union (EU), the USA and Japan ranked lowest and perceived to have the most stringent food safety requirements.

The paper offers guidance to firms and policymakers to manage their efforts and resources during food safety implementation by focussing on critical FSMs. Researchers will get insights about FSMs for further empirical investigation. To the authors’ knowledge, no study examined the stringency associated with various FSMs in the seafood industry.

In recent years, the retail landscape has undergone a seismic shift, transforming into a dynamic, interconnected ecosystem where consumers seamlessly traverse physical and digital realms. This shift has given rise to the omnipresent force known as Omni-channel retailing. This chapter aims to delve into the intricacies of Omni-channel retail strategies, exploring how businesses can leverage this paradigm to enhance customer experience, streamline operations, and drive sustainable growth. Omni-channel retail strategies encompass a range of approaches aimed at providing customers with a seamless and integrated shopping experience across various channels. These strategies can be categorized into several key areas, each involving specific modern technologies to enhance customer engagement and satisfaction.

The purpose of this paper is to identify the ideal process parameters to be set for the drilling of hybrid fibre-reinforced polymer (FRP) (kenaf and banana) composite using High-Speed Steel drill bits (5, 10, 15 mm) coated with tungsten carbide by means of statistical reproduction of the delamination factor and machining force using Taguchi–Grey Relational Analysis.

The contemplated process parameters are Feed, Speed and Drill Diameter. The trials were carried out by taking advantage of the L-27 factorial design by Taguchi. Three factors, the three level Taguchi Orthogonal Array design in Grey Relational Analysis was used to carry out the trial study. Video Measuring System was used to identify the damage around the drill region. “Minitab 18” was used to examine the data collected by taking advantage of the various statistical and graphical tools available. Examination of variance is used to legitimize the model in identifying the most notable parameter.

The optimised set of input parameters were found out successfully which are as follows: Feed Rate: 450 mm/min, Cutting Speed: 3,000 rpm and Drill Diameter of 5 mm. When these values are fed in as input the optimised output is being obtained. From ANOVA analysis, it is apparent that the Speed (contribution of 92.6%) is the most influencing parameter on the delamination factor and machining force of the FRP material.

Optimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using Taguchi–Grey Relational Analysis has not been previously explored.

Banking sector is an important subset of any economy and plays a very crucial and significant part in its growth and development. The expansion and credibility of banking sector is attributed to the fact that it caters to the financial needs and accordingly provides customised solutions for the people at large. The new millennium has witnessed metamorphosis in the banking sector. The pace and trend of transformation is all set to accelerate in the coming decade. The process of Liberalisation, Privatisation and Globalisation Model (LPG Model) banking practices which being unleashed a few decades back will reach to greater heights as we step into the next decade. The innovative technology has brought about a paradigm shift in all aspects of banking like routine operations, transactions, products and processes, delivery of services in terms of various e-channels, credit administration and credit management, audit and compliance and Fin-Techs partnership. Digital transformations in the banking sector have received much needed thrust because of ‘The Digital India Moment’. The current study attempts to highlight the role of technology in banking and how technology-led innovations and initiatives will determine the business of banking as a whole. The significance of these technology-driven innovations and transformations is that they put both banker and customer in a win-win situation as drawn from existing literature related to financial institutions. The focus is on investigating the digital innovations adopted by the different banks both public and private to understand the economic structural changes resulted out of it.

Present work deals with the partial substitution of cement by waste demolished concrete powder (WDP) for reducing the carbon footprints of concrete.

Control specimens and the specimens with 20% WDP as fractional substitute of cement were prepared. The waste powder was thermally activated at 825 °C prior to its use in the mix. The prepared specimens were evaluated in terms of density, workability, mechanical strength, Ultrasonic pulse velocity (UPV) and rebound hammer (RH).

The results showed that with the substitution, the workability of the mix increased, while the density decreased. A decrement within a 20% limit was found in compressive strength. The UPV and RH results were closely linked to the other results as mentioned above.

The study deals with only M15 concrete and the substitution level of only 20% as a baseline.

The concrete containing 20% WDP is lightweight and more workable. Moreover, its strength at 28 days is 14 MPa, only 1 MPa lesser than the characteristic strength.

The WDP can be recycled and the dumping in landfills can be reduced. This is an important effort towards the decarbonation of concrete.

Previous literature indicates that the WDP has been frequently used as a partial replacement of aggregates. However, some traces of secondary hydration were also reported. This work considers the effect of partial substitution of cement by the WDP.

In the last years, the use of free-online instructional videos has gained popularity among educators and students. Its success is mainly based on the provision of fast and inexpensive access to educational contents which can be consulted at the own convenience of students, all over the world. Free-online platforms as YouTube offer access to more than ten million instructional videos. The purpose of this paper is to assess and rank the educational quality of free-online instructional videos from a multidimensional perspective.

In this paper, the authors propose a MCDM approach based on a compromise ranking method, VIKOR. The approach integrates a normalization process which is especially suitable for situations where the nature of the different decision-making criteria is such that it does not allow homogeneous aggregation.

With the proposed normalization approach, the initial valuations of the alternatives with respect to the criteria are transformed in order to reflect their similarity with a given reference point (ideal solution). The normalized data are then integrated in a VIKOR-based framework in order to obtain those mathematical videos closer to the ideal video from the instructors’ perspective.

The ranking of instructional videos based on their quality from an educational multidimensional perspective is a good example of a real decision-making problem where the nature of the criteria, qualitative and quantitative, implies heterogeneous data. The proposed IS-VIKOR approach overcomes some of the problems inherent to this real decision-making problem.