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This study examines the performance effect of working capital for a large sample of Indian manufacturing firms in light of supply chain disruption, i.e. the COVID-19 pandemic.

This study is based on secondary data collected from the Prowess database on Indian manufacturing firms listed on the Bombay Stock Exchange (BSE) 500. Panel data regression analyses are used to estimate all models. Moreover, this study has employed robust standard errors to consider for heteroscedasticity concerns.

The results challenge the current notion of working capital investment and reveal that higher working capital has a positive and significant impact on firm performance. Further, it highlights that Indian manufacturing firms suffered financially post-COVID-19 as they significantly lack the working capital to run day-to-day operations.

This research contributes to the scant literature by examining the association between working capital financing and firm performance in light of the COVID-19 pandemic, representing typical developing economies like India.

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 study aims to enhance the knowledge by offering perspectives from an emerging market by reviewing the existing literature on food tourism. This study applies a multimethod analysis, providing insights into the advancement of food tourism in India, the contributions, critical findings and emerging research themes.

The study adopted a multimethod analysis using descriptive, narrative and bibliometric analysis using VOSviewer to analyze research papers published on food tourism in India shortlisted from Scopus and Google Scholar.

Future research should focus on gauging the potential of food tourism in different regions of the country, applying theoretical frameworks that have not been used. “Culinary Diversity and Heritage,” “Sustainable and Responsible Food Tourism,” “Consumer Behavior and Food Tourism Experiences,” “Rural Development and Economic Impact,” “Technology and Digitalization,” “Stakeholder Collaboration,” “Food Safety and Hygiene” and “Policy and Regulation” were the identified future research themes. These findings are significant for emerging economies across the globe.

This study summarized the progress of food tourism research in India, the contributions and emerging themes, supplementing the need to study food tourism in India. This study contributed methodologically to the literature by adopting a multimethod review combining descriptive, narrative and bibliometric analysis. Finally, by proposing ideas and constructs for future research, this study provides directions for future food tourism research from an emerging market’s perspective.

Findings will assist managers and stakeholders in comprehending the factors influencing tourists, destination marketing and branding, aiding in effective planning and executing food tourism strategies to promote destinations. The identified themes and keywords can help academicians and researchers dwell upon the emerging research themes in food tourism.

To the best of the author’s knowledge, this is the first study analyzing food tourism research in India adopting a multimethod analysis. The study provides an in-depth analysis applying descriptive, narrative and bibliometric analysis, highlighting the critical trends and research themes. A framework for future studies was also proposed.

该研究旨在通过回顾有关美食旅游的现有文献, 提供来自新兴市场的观点, 从而强化现有的知识。本研究采用多方法分析, 深入了解印度美食旅游的发展、贡献、重要发现和新兴研究主题。

该研究采用了多种方法分析, 使用 VOSviewer 进行描述性、叙述性和文献计量分析, 以分析从 Scopus 和谷歌学术搜索中入围的关于印度美食旅游的研究论文。

未来的研究应侧重于衡量该国不同地区美食旅游的潜力, 应用尚未使用的理论框架。 “烹饪多样性和传统”、“可持续和负责任的美食旅游”、“消费者行为和美食旅游体验”、“农村发展和经济影响”、“技术和数字化”、“利益相关者协作”、“食品安全和卫生”, “政策与法规”是确定的未来研究主题。这些发现对全球新兴经济体具有重要意义。

本研究总结了印度美食旅游研究的进展、贡献和新兴主题, 补充了研究印度美食旅游的必要性。本研究采用结合描述性、叙述性和文献计量分析的多方法回顾, 在方法论上为文献做出了贡献。最后, 通过提出未来研究的思路和结构, 本研究从新兴市场的角度为未来的美食旅游研究提供了方向。

调查结果将帮助管理者和利益相关者理解影响游客、目的地营销和品牌的因素, 帮助有效规划和执行食品旅游战略以促进目的地。 确定的主题和关键词可以帮助院士和研究人员深入研究食品旅游中新兴的研究主题。

El estudio tiene como objetivo mejorar el conocimiento al ofrecer perspectivas de un mercado emergente mediante la revisión de la literatura existente sobre turismo gastronómico. Este estudio aplica un análisis de múltiples métodos, que proporciona información sobre el avance del turismo gastronómico en la India, las contribuciones, los hallazgos críticos y los temas de investigación emergentes.

El estudio adoptó un análisis multimétodo mediante un análisis descriptivo, narrativo y bibliométrico utilizando VOSviewer para analizar los artículos de investigación publicados sobre el turismo gastronómico en la India preseleccionados de Scopus y Google Scholar.

La investigación futura debería centrarse en calibrar el potencial del turismo gastronómico en las distintas regiones del país, aplicando marcos teóricos que no se han utilizado. “Diversidad culinaria y patrimonio”, “Turismo gastronómico sostenible y responsable”, “Comportamiento del consumidor y experiencias de turismo gastronómico”, “Desarrollo rural e impacto económico”, “Tecnología y digitalización”, “Colaboración de las partes interesadas”, “Seguridad e higiene alimentaria”, “Política y regulación” fueron los temas de investigación futura identificados. Estos hallazgos son significativos para las economías emergentes de todo el mundo.

Este estudio resumió el progreso de la investigación sobre turismo alimentario en la India, las contribuciones y los temas emergentes, complementando la necesidad de estudiar el turismo alimentario en la India. Este estudio contribuyó metodológicamente a la bibliografía al adoptar una revisión multimétodo que combina el análisis descriptivo, narrativo y bibliométrico. Por último, al proponer ideas y constructos para futuras investigaciones, este estudio proporciona orientaciones para futuras investigaciones sobre el turismo gastronómico desde la perspectiva de un mercado emergente.

Los resultados ayudarán a los gestores y a las partes interesadas a comprender los factores que influyen en los turistas, el marketing de los destinos y la creación de marcas, contribuyendo a una planificación y ejecución eficaces de las estrategias de turismo gastronómico para promocionar los destinos. Los temas y palabras clave identificados pueden ayudar a los académicos e investigadores a profundizar en los temas de investigación emergentes en el turismo gastronómico.

Se trata del primer estudio que analiza la investigación sobre turismo gastronómico en la India adoptando un análisis multimétodo. El estudio proporciona un análisis en profundidad aplicando un análisis descriptivo, narrativo y bibliométrico, destacando las tendencias críticas y los temas de investigación. También se propone un marco para futuros estudios.

Delays in utility shifting during road construction have broad ramifications. These delays not only lengthen the project's timeline but also raise expenses and cause problems with resource allocation. Thus, this study investigates the influence of delay in utility shifting for extension of time claims in road construction projects (RCPs) in Sri Lanka.

The study used a quantitative approach with three rounds of Delphi surveys to gather empirical data. Further, the probability impact assessment was used to carefully analyse the data and appraise the information gathered.

The findings initially revealed 33 causes of delays in utility shifting for extension of time claims in RCPs in Sri Lanka. Ultimately, 11 severe causes were identified based on their high probability and impact, concluding with 45 strategies that were assigned to overcoming those most severe causes of delay.

This study will contribute to the industry and theory by providing solutions to handle utility-shifting delays with the linkage of preventing time extension claims for RCPs in Sri Lanka. Further, there is a dearth of literature in the research area, both locally and globally. Thus, the findings of this research will provide a benchmark for further detailed studies in other countries as well.

Communities representing groups of agents with similar interests or functions are one of the essential features of complex networks. Finding communities in real-world networks is critical for analyzing complex systems in various areas ranging from collaborative information to political systems. Given the different characteristics of networks and the capability of community detection in handling a plethora of societal problems, community detection methods represent an emerging area of research. Contributing to this field, the authors propose a new community detection algorithm based on the hybridization of node and link granulation.

The proposed algorithm utilizes a rough set-theoretic concept called closure on networks. Initial sets are constructed by using neighborhood topology around the nodes as well as links and represented as two different categories of granules. Subsequently, the authors iteratively obtain the constrained closure of these sets. The authors use node mutuality and link mutuality as merging criteria for node and link granules, respectively, during the iterations. Finally, the constrained closure subsets of nodes and links are combined and refined using the Jaccard similarity coefficient and a local density function to obtain communities in a binary network.

Extensive experiments conducted on twelve real-world networks followed by a comparison with state-of-the-art methods demonstrate the viability and effectiveness of the proposed algorithm.

The study also contributes to the ongoing effort related to the application of soft computing techniques to model complex systems. The extant literature has integrated a rough set-theoretic approach with a fuzzy granular model (Kundu and Pal, 2015) and spectral clustering (Huang and Xiao, 2012) for node-centric community detection in complex networks. In contributing to this stream of work, the proposed algorithm leverages the unexplored synergy between rough set theory, node granulation and link granulation in the context of complex networks. Combined with experiments of network datasets from various domains, the results indicate that the proposed algorithm can effectively reveal co-occurring disjoint, overlapping and nested communities without necessarily assigning each node to a community.

This study carries important practical implications for complex adaptive systems in business and management sciences, in which entities are increasingly getting organized into communities (Jacucci et al., 2006). The proposed community detection method can be used for network-based fraud detection by enabling experts to understand the formation and development of fraudulent setups with an active exchange of information and resources between the firms (Van Vlasselaer et al., 2017). Products and services are getting connected and mapped in every walk of life due to the emergence of a variety of interconnected devices, social networks and software applications.

The proposed algorithm could be extended for community detection on customer trajectory patterns and design recommendation systems for online products and services (Ghose et al., 2019; Liu and Wang, 2017). In line with prior research, the proposed algorithm can aid companies in investigating the characteristics of implicit communities of bloggers or social media users for their services and products so as to identify peer influencers and conduct targeted marketing (Chau and Xu, 2012; De Matos et al., 2014; Zhang et al., 2016). The proposed algorithm can be used to understand the behavior of each group and the appropriate communication strategy for that group. For instance, a group using a specific language or following a specific account might benefit more from a particular piece of content than another group. The proposed algorithm can thus help in exploring the factors defining communities and confronting many real-life challenges.

This work is based on a theoretical argument that communities in networks are not only based on compatibility among nodes but also on the compatibility among links. Building up on the aforementioned argument, the authors propose a community detection method that considers the relationship among both the entities in a network (nodes and links) as opposed to traditional methods, which are predominantly based on relationships among nodes only.

A porous cavity flow field generates entropy owing to energy and momentum exchange within the fluid and at solid barriers. The heat transport and viscosity effects on fluid and solid walls irreversibly generate entropy. This numerical study aims to investigate convective heat transfer together with entropy generation in a partially heated wavy porous cavity filled with a hybrid nanofluid.

The governing equations are nondimensionalized and the domain is transformed into a unit square. A second-order finite difference method is used to have numerical solutions to nondimensional unknowns such as stream function and temperature. This numerical computation is conducted to explore a wide range of regulating parameters, e.g. hybrid nano-particle volume fraction (σ = 0.1%, 0.33%, 0.75%, 1%, 2%), Rayleigh–Darcy number (Ra = 10, 10², 10³), dimensionless length of the heat source (ϵ = 0.25, 0.50,1.0) and amplitude of the wave (a = 0.05, 0.10, 0.15) for a number of undulations (N = 1, 3) per unit length.

A thorough analysis is conducted to analyze the effect of multiple factors such as thermal convective forces, heat source, surface corrugation factors, nanofluid volume fraction and other parameters on entropy generation. The flow and temperature fields are studied through streamlines and isotherms. The average Bejan number suggested that entropy generation is entirely dominated by irreversibility due to heat transport at Ra = 10, and the irreversibility due to the viscosity effect is severe at Ra = 10³, but the increment in s augments irreversibility due to the viscosity effect over the heat transport at Ra = 10².

To the best of the authors’ knowledge, this numerical study, for the first time, analyzes the influence of surface corrugation on the entropy generation related to the cooling of a partial heat source by the convection of a hybrid nanofluid.

Customer experience is increasingly recognized as a source of competitive advantage. Customer experience refers to customers' responses and reactions to cues within touchpoints along customer journeys. Nowadays, customers often interact with online touchpoints – such as social media, websites, or e-commerce – in their customer journeys. Given that customer experience is multidimensional, this chapter addresses the following question: How can sensorial experiences be triggered in online touchpoints? Based on a review of the literature on customer experience and sensory marketing, four challenges in triggering sensorial experiences in online touchpoints are identified: (1) limited sensorial cues, (2) lack of thematic congruence between online and offline touchpoints, (3) sensory overload, and (4) lesser control over sensorial cues. Then, two routes through which organizations can trigger sensorial experiences in online touchpoints are proposed: (1) directly influencing sensations through sensory-enabling technologies, and (2) indirectly influencing sensorial perceptions through the use of sensory and nonsensory cues. The chapter closes with a presentation of a model that describes the process of triggering sensorial experiences in online touchpoints as well as a checklist of relevant questions for practitioners who wish to do so.

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.

The purpose of this study is to extensively explore the vehicular network paradigm, challenges faced by them and provide a reasonable solution for securing these vulnerable networks. Vehicle-to-everything (V2X) communication has brought the long-anticipated goal of safe, convenient and sustainable transportation closer to reality. The connected vehicle (CV) paradigm is critical to the intelligent transportation systems vision. It imagines a society free of a troublesome transportation system burdened by gridlock, fatal accidents and a polluted environment. The authors cannot overstate the importance of CVs in solving long-standing mobility issues and making travel safer and more convenient. It is high time to explore vehicular networks in detail to suggest solutions to the challenges encountered by these highly dynamic networks.

This paper compiles research on various V2X topics, from a comprehensive overview of V2X networks to their unique characteristics and challenges. In doing so, the authors identify multiple issues encountered by V2X communication networks due to their open communication nature and high mobility, especially from a security perspective. Thus, this paper proposes a trust-based model to secure vehicular networks. The proposed approach uses the communicating nodes’ behavior to establish trustworthy relationships. The proposed model only allows trusted nodes to communicate among themselves while isolating malicious nodes to achieve secure communication.

Despite the benefits offered by V2X networks, they have associated challenges. As the number of CVs on the roads increase, so does the attack surface. Connected cars provide numerous safety-critical applications that, if compromised, can result in fatal consequences. While cryptographic mechanisms effectively prevent external attacks, various studies propose trust-based models to complement cryptographic solutions for dealing with internal attacks. While numerous trust-based models have been proposed, there is room for improvement in malicious node detection and complexity. Optimizing the number of nodes considered in trust calculation can reduce the complexity of state-of-the-art solutions. The theoretical analysis of the proposed model exhibits an improvement in trust calculation, better malicious node detection and fewer computations.

The proposed model is the first to add another dimension to trust calculation by incorporating opinions about recommender nodes. The added dimension improves the trust calculation resulting in better performance in thwarting attacks and enhancing security while also reducing the trust calculation complexity.