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Purpose: This study links SDG goal 9 of industry, innovation strategies and another infrastructural environment to branding relating to destination and interactive marketing. Digital marketing tools with various applications aim to offer hi-tech services to customers in interactive marketing services, namely multiple goods and services, data and innovative techniques in the tourism and travel sector. Exploring the study would add to the existing literature supporting interactive marketing procedures and destination branding. Branding relating to destinations fosters tourists around the globe facilitating economic growth and development and supporting the local economies.

Need for the Study: It is observed from the literature that very few studies have been identified across the globe from various researchers on the interactive marketing and destination branding that ensures brand loyalty and reassesses the intent of the tourists just before the epidemic pandemic in the form of COVID-19. Artificial Intelligence, as part of information technology, offers various interactive marketing services in the form of different social media marketing strategies, attractive websites for tourists and travel providers and image building on destination branding. This study would help fill the marketing gap, which results in branding relating to destination, brand loyalty and reassessing the intent of various tours and travel plans just before the pandemic.

Methodology: The study focused on the literature, demonstrating the stimulus organism methodology and examining the impact of potential marketing strategy, which is interactive focusing on the destination branding, loyalty relating to the brand and also procedures to revert with the intent that would motivate and facilitate the customer’s confidence showering the loyalty relating to the brand in the travel and tourism sector.

Findings and their Practical Implications: The study revealed that the marketing relating to interactive methodologies in the hi-tech digital approaches ought to be carried out to create opportunities for prospective tourists willing to get information about various tourists destinations with the help of various marketing techniques such as different social media applications, easy access of websites for accessing the tourist destinations and relevant information, accessing images pertinent to the tourism destinations with the ease of chat box and providing suitable audios and video sources to the potential customers.

The aim of the present paper is to investigate the homogeneous and heterogeneous reactions on Prandtl fluid flow at a stretching sheet with an induced magnetic field and slip boundary conditions.

The governing equations include the continuity, induced magnetic field, momentum, energy and homogeneous–heterogeneous equations. Initially, with suitable similarity variables, the governing partial differential equations and converted into a system of ordinary differential equations. Then, the nonlinear ordinary differential equations are solved by a shooting technique with the help of the BVC5C Matlab package.

The results of the present investigation are presented through graphs for different values of the various parameters. The authors observed that the large values of the stretching ratio and the induced magnetic parameters are moderate magnetic field, velocity and temperature primarily. Also, the authors found the more velocity and temperatures by boosting the slip parameters.

In addition, the values of the skin friction and the rate of heat transfer for various values of physical parameters are tabulated and deliberated in detail.

This study aims to analyze the impact of fractional derivatives on heat transfer and entropy generation during transient free convection inside various complex porous enclosures, such as triangle, L-shape and square-containing wavy surfaces. These porous enclosures are saturated with Cu-water nanofluid and subjected to the influence of a uniform magnetic field.

In the present study, Darcy’s model is used for the momentum transport equation in the porous matrix. Additionally, the Caputo time fractional derivative is introduced in the energy equation to assess the heat transfer phenomenon. Furthermore, the total entropy generation has been computed by combining the entropy generation due to fluid friction (S_ff), heat transfer (S_ht) and magnetic field (S_mf). The complete mathematical model is further simulated using the penalty finite element method, and the Caputo time derivative term is approximated using the L1 scheme. The study is conducted for various ranges of the Rayleigh number (102≤Ra≤104), Hartmann number (0≤Ha≤20) and fractional order parameter (0<α<1) with respect to time.

It has been observed that the fractional order parameter α governs the characteristics of entropy generation and heat transfer within the selected range of parameters. The Bejan number associated with heat transfer (Be_ht), fluid friction (Be_ff) and magnetic field (Be_mf) further demonstrate the dominance of flow irreversibilities. It becomes evident that the initial evolution state of streamlines, isotherms and local entropy varies according to the choice of α. Additionally, increasing Ra values from 10² to 10⁴ shows that the heat transfer rate increases by 123.8% for a square wavy enclosure, 7.4% for a triangle enclosure and 69.6% for an L-shape enclosure. Moreover, an increase in the value of Ha leads to a reduction in heat transfer rates and entropy generation. In this case, Bemf→1 shows the dominance of the magnetic field irreversibility in the total entropy generation.

Recently, fractional-order models have been widely used to express numerous physical phenomena, such as anomalous diffusion and dispersion in complex viscoelastic porous media. These models offer a more accurate representation of physical reality that classical models fail to capture; this is why they find a broad range of applications in science and engineering.

The fractional derivative model is used to illustrate the flow pattern, heat transfer and entropy-generating characteristics under the influence of a magnetic field. Furthermore, to the best of the author’s knowledge, a fractional-derivative-based mathematical model for the entropy generation phenomenon in complex porous enclosures has not been previously developed or studied.

Thermo-magnetic convective flow analysis under the impact of thermal radiation for heat and entropy generation phenomena is an active research field for understanding the efficiency of thermodynamic systems in various engineering sectors. This study aims to examine the characteristics of convective heat transport and entropy generation within an inverted T-shaped porous enclosure saturated with a hybrid nanofluid under the influence of thermal radiation and magnetic field.

The mathematical model incorporates the Darcy-Forchheimer-Brinkmann model and considers thermal radiation in the energy balance equation. The complete mathematical model has been numerically simulated through the penalty finite element approach at varying values of flow parameters, such as Rayleigh number (Ra), Hartmann number (Ha), Darcy number (Da), radiation parameter (Rd) and porosity value (e). Furthermore, the graphical results for energy variation have been monitored through the energy-flux vector, whereas the entropy generation along with its individual components, namely, entropy generation due to heat transfer, fluid friction and magnetic field, are also presented. Furthermore, the results of the Bejan number for each component are also discussed in detail. Additionally, the concept of ecological coefficient of performance (ECOP) has also been included to analyse the thermal efficiency of the model.

The graphical analysis of results indicates that higher values of Ra, Da, e and Rd enhance the convective heat transport and entropy generation phenomena more rapidly. However, increasing Ha values have a detrimental effect due to the increasing impact of magnetic forces. Furthermore, the ECOP result suggests that the rising value of Da, e and Rd at smaller Ra show a maximum thermal efficiency of the mathematical model, which further declines as the Ra increases. Conversely, the thermal efficiency of the model improves with increasing Ha value, showing an opposite trend in ECOP.

Such complex porous enclosures have practical applications in engineering and science, including areas like solar power collectors, heat exchangers and electronic equipment. Furthermore, the present study of entropy generation would play a vital role in optimizing system performance, improving energy efficiency and promoting sustainable engineering practices during the natural convection process.

To the best of the authors’ knowledge, this study is the first ever attempted detailed investigation of heat transfer and entropy generation phenomena flow parameter ranges in an inverted T-shaped porous enclosure under a uniform magnetic field and thermal radiation.

This paper aims to investigate the factors that determine the performance of small business units using a field survey conducted in a small jewellery cluster in Mangalore district of Karnataka state (India).

The estimates of the median-based quantile regression model are used to analyse how a change in small firm output is determined by seven key factors such as year of establishment, the source of finance, the source of design, lack of demand, design done by the staff, the number of skilled workers, and constraints.

The study finds that the factors such as sources of finance, design, customer relation and skilled manpower are the major determinants of the growth of jewellery business. Based on the findings, the study suggests that the invigoration of business performance by high degree of competitiveness, coupled with technological advancement and hiring of skilled labour, is essential for the sustainability of jewellery units.

The study pinpoints the problems and prospects of traditional business units located in an industrial cluster. Further, it suggests the different ways of strengthening the performance of small business units in India.

Due to the recent disruptions caused by COVID-19, global supply chains are stress tested. The affected supply chains have interfered with market tonnage prices for the yield of perishable products like mangoes that are highly dependent on their quality. This research, through empirical findings, thus determines and comprehends the factors influencing mango quality (size).

A framework is developed for finding the potential factors of quality building on the previous literature and studies on the available topic. The data collection included face-to-face interviews comprising 240 farmers, hired managers and preharvest contractors in India's Jangaon, Rangareddy and Yadadri Bhuvanagiri districts of Telangana state. The data analysis is done using multiple regression, and the outcomes form the basis of the design of the experiments model.

The empirical insights support that the quality of mango is affected by factors such as the number of picking cycles, the cost of fertilizer, the variety of fertilizers used, the variety of pesticides used and pesticide application frequency. The direct implications are the benefit to farmers in improving mango quality and maximizing profit per yield cycle.

To the best of the authors’ knowledge, the first research that has specifically focused on holistically improving the quality(size) of mangoes.

The findings contribute to the perishable supply chain literature, specifically to the mango study, to comprehensively showcase the factors impacting the quality of mangoes and provide guidance to farmers regarding orchard practices.

The purpose of this paper is to explore leadership styles and patterns in India, Indonesia, Pakistan, and the USA in order to contribute to a greater understanding of global leadership.

The paper uses cultural mythologies as a lens (Kessler and Wong-MingJi, 2009a) to extract the most favored leadership traits within selected countries. In doing so, the paper explores historical trajectories and core values of each country to identify their distinctive characteristics. Additionally, leadership styles of well-known business leaders in each culture are examined to develop a comparative discussion of global leadership patterns and styles.

The paper finds that leaders may share same characteristics across countries, however, their behavioral expressions tend to unfold differently within each context. The paper argues that without context, meanings embedded in cultural mythologies and behaviors often become lost. The paper concludes that a comparative analysis of selected countries reveals a more complex and rich array of cultural meanings, thus offering support to a contextual view of leadership.

Examination of cultural mythologies on leadership makes important theoretical contributions by illustrating that cultural mythologies indeed shape the values, behaviors, and attitudes of global leaders, and provide three important functions that are identified as: cultural bridging, meaning making, and contextual nuancing.

Understanding comparative leadership patterns is critical in international business. The paper offers cultural mythologies as a tool for leaders who seek to cross-cultural boundaries in developing long term and high-quality productive international business relationships.

The value of the study lies in developing a comparative analysis of leadership patterns in three Southeast Asian countries and the USA with the help of cultural mythologies. The paper urges that scholars to move beyond quantification of cultural dimensions to a more contextualized understanding of leadership.

A growing response in the development of hybrid composites to conquer the deficiency of neat composites has provoked doing this work. Thermoplastic Polycarbonate material offers better impact toughness with low structural weight. There is a little/no information available over the selected sandwich hybrid composite prepared from woven E-Glass and polycarbonate sheet. The purpose of this paper is to understand the response of the novel hybrid structure under tensile, flexural, interlaminar shear and impact loading conditions.

The hand-layup technique is used for fabricating the hybrid composites in the laminate configuration. The hybrid composites are prepared with a total fiber content of 70 percent weight fractions. The effect of the percentage of reinforcement on mechanical properties is evaluated experimentally as per American society for testing materials standard test methods. The damaged mechanisms of failed samples and fractured surfaces are well analyzed using vision measuring system and scanning electron microscopy.

A decline in densities of hybrid composites up to 22.5 percent is noticed with reference to neat composite. An increase in impact toughness up to 40.73 percent is marked for hybrid laminates owing to the ductile nature of PC. Delamination is identified to be the major mode of failure apart from fiber fracture/pull-out, matrix cracking in all the static loading conditions.

The response of novel hybrid composite reported has been explored for the first time in this paper. The outcome of experimental work revealed that hybridization offered lightweight structures with improved transverse impact toughness as compared to conventional composite.

In cultivation, early harvest offers farmers an opportunity to increase production while decreasing the chances of lower crop production rates, ensuring that the economy remains balanced. The significant reason is to predict the disease in plants and distinguish the type of syndrome with the help of segmentation and random forest optimization classification. In this investigation, the accurate prior phase of crop imagery has been collected from different datasets like cropscience, yesmodes and nelsonwisc . In the current study, the real-time earlier state of crop images has been gathered from numerous data sources similar to crop_science, yes_modes, nelson_wisc dataset.

In this research work, random forest machine learning-based persuasive plants healthcare computing is provided. If proper ecological care is not applied to early harvesting, it can cause diseases in plants, decrease the cropping rate and less production. Until now different methods have been developed for crop analysis at an earlier stage, but it is necessary to implement methods to advanced techniques. So, the detection of plant diseases with the help of threshold segmentation and random forest classification has been involved in this investigation. This implemented design is verified on Python 3.7.8 software for simulation analysis.

In this work, different methods are developed for crops at an earlier stage, but more methods are needed to implement methods with prior stage crop harvesting. Because of this, a disease-finding system has been implemented. The methodologies like “Threshold segmentation” and RFO classifier lends 97.8% identification precision with 99.3% real optimistic rate, and 59.823 peak signal-to-noise (PSNR), 0.99894 structure similarity index (SSIM), 0.00812 machine squared error (MSE) values are attained.

The implemented machine learning design is outperformance methodology, and they are proving good application detection rate.