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A parabolic trough solar collector is an advanced concentrated solar power technology that significantly captures radiant energy. Solar power will help different sectors reach their energy needs in areas where traditional fuels are in use. This study aims to examine the sensitivity analysis for optimizing the heat transfer and entropy generation in the Jeffrey magnetohydrodynamic hybrid nanofluid flow under the influence of motile gyrotactic microorganisms with solar radiation in the parabolic trough solar collectors. The influences of viscous dissipation and Ohmic heating are also considered in this investigation.

Governing partial differential equations are derived via boundary layer assumptions and nondimensionalized with the help of suitable similarity transformations. The resulting higher-order coupled ordinary differential equations are numerically investigated using the Runga-Kutta fourth-order numerical approach with the shooting technique in the computational MATLAB tool.

The numerical outcomes of influential parameters are presented graphically for velocity, temperature, entropy generation, Bejan number, drag coefficient and Nusselt number. It is observed that escalating the values of melting heat parameter and the Prandl number enhances the Nusselt number, while reverse effect is observed with an enhancement in the magnetic field parameter and bioconvection Lewis number. Increasing the magnetic field and bioconvection diffusion parameter improves the entropy and Bejan number.

Nanotechnology has captured the interest of researchers due to its engrossing performance and wide range of applications in heat transfer and solar energy storage. There are numerous advantages of hybrid nanofluids over traditional heat transfer fluids. In addition, the upswing suspension of the motile gyrotactic microorganisms improves the hybrid nanofluid stability, enhancing the performance of the solar collector. The use of solar energy reduces the industry’s dependency on fossil fuels.

The adoption and usage of information and communication technology (ICT) has introduced transformation in the tourism arena with ICT applications extensively used in tourism industry. In addition to ICT, an advanced infrastructure is essential for the development of tourism industry. Thus, the goal of present research is to probe the impact of ICT and infrastructure on tourism development (TD) in 28 Asian economies using method of moments panel quantile regression (MM-QR) model introduced by Machado and Silva (2019) applied to a panel data from 2008 to 2020. Empirical findings demonstrate that there is an asymmetric non-linear effect of ICT and infrastructure through all quantile range. This indicates that ICT has negative effect on TD in poor countries while positive impact in rich countries. Negative impact in poor countries may be due to higher establishment cost and information technology (IT) productivity paradox. However, results confirm the importance of ICT and infrastructure in endorsing the development of tourism sector in Asian nations by lessening time and money costs and facilitating travelers.

The COVID-19 pandemic has led to major sales strategy and process changes as many interactions migrated from face-to-face to virtual environments. The nature of the interactions changed, and sales firms, the sales function and salespeople created new processes to excel in virtual environments. As sales processes evolve further, this paper aims to focus on understanding the enduring shifts in sales strategy and processes. In addition, this study seeks to understand the characteristics of enduring shifts and how they are distinct from temporary shifts.

This qualitative analysis provides a comprehensive overview of the sales organizations and salespeople over the period from the start of the pandemic to early 2022. The authors interviewed 66 sales professionals from different countries and industries to better understand the temporary and enduring shifts in sales strategy and processes, adopting ad inductive and narrative approach.

There are four major findings. First, four key themes emerged: increased digitalization, resistance to digitalization, sales process changes and sales organization transformation. Second, changes are classified as temporary, permanent and accelerated changes. Third, some proposed changes were not supported. Finally, five findings were found that were not discussed in previous literature.

This paper finds distinctive findings that offer additional valuable insights that connect to and extend existing literature. These include emerging themes, classification shifts, unsupported proposed changes and unique findings.

Climate change has been universally recognized as a major threat to human well-being, necessitating a comprehensive transformation of people's activities. Various measures have been proposed to contain climate change among which the green transformation grabs special attention, thanks to its desirable properties. Within the green transformation process, green tourism comes to prominence with huge potential. As one of the largest carbon emitters, the transition towards green tourism may offer substantial benefits not only for tourism companies but also for the whole economy. Yet, most studies tend to focus on the adverse effects of tourism on climate change while overlooking the potential impact of climate change on tourism. This chapter clarifies the feedback relationship between climate change and tourism and makes some recommendations.

This paper aims to present a study on stability analysis of Jeffrey fluids in the presence of emergent chemical gradients within microbial systems of anisotropic porous media.

This study uses an effective method that combines non-dimensionalization, normal mode analysis and linear stability analysis to examine the stability of Jeffrey fluids in the presence of emergent chemical gradients inside microbial systems in anisotropic porous media. The study focuses on determining critical values and understanding how temperature gradients, concentration gradients and chemical reactions influence the onset of bioconvection patterns. Mathematical transformations and analytical approaches are used to investigate the system’s complicated dynamics and the interaction of numerous characteristics that influence stability.

The analysis is performed using the Jeffrey-Darcy type and Boussinesq estimation. The process involves using non-dimensionalization, using the normal mode approach and conducting linear stability analysis to convert the field equations into ordinary differential equations. The conventional thermal Rayleigh Darcy number RDa,c is derived as a comprehensive function of various parameters, and it remains unaffected by the bio convection Lewis number Łe. Indeed, elevating the values of ζ and γ′ in the interval of 0 to 1 has been noted to expedite the formation of bioconvection patterns while concurrently expanding the dimensions of convective cells. The purpose of this investigation is to learn how the temperature gradient affects the concentration gradient and, in turn, the stability and initiation of bioconvection by taking the Soret effect into the equation. The results provide insightful understandings of the intricate dynamics of fluid systems affected by chemical and biological elements, providing possibilities for possible industrial and biological process applications. The findings illustrate that augmenting both microbe concentration and the bioconvection Péclet number results in an unstable system. In this study, the experimental Rayleigh number RDa,c was determined to be 4π2at the critical wave number ( δcˇ) of π.

The study’s novelty originated from its investigation of a novel and complicated system incorporating Jeffrey fluids, emergent chemical gradients and anisotropic porous media, as well as the use of mathematical and analytical approaches to explore the system’s stability and dynamics.

COVID-19 has been the subject of a number of inquiries recently. All country's capital market practices have been affected by the COVID-19 outbreak. Economic woes, along with the stock market crash, have hit emerging markets and developing economies in a variety of directions.

This study is an attempt to focus on the Indian economy to provide the gist of the situation and recovery mode of an economy with the help of growth indicators of the economy.

This study is based on secondary data. The researchers applied some econometric tools, viz, unit root test Augmented Dickey-Fuller (ADF), Panel Granger Causality, and Panel ARDL Bound Test were applied to examine the relationship of economic indicators and stock market benchmark in two periods: March 2020–June 2021 (during period) and July 2021 to March 2022 (post period).

The findings of this study explored the different causal relationships for the selected variables in both periods. The study discussed the reasons for ARDL (Auto Regressive Distributed Lag) bound for all selected factors. The study revealed the story of crude oil prices and Gold as trusted investment avenues during the crises.

As we know, the capital market's backlash is reflected in movements in stock prices and stock exchange volume, which are concerned with the economic effects of the pandemic and urged the segment to react. Investors can use the information in the event to make investment decisions.

Organizations’ culture and environment create a remarkable influence on the minds of the employees. Employees spend a lot of time at the workplace; hence, it is essential to take care of their happiness. Stressful workplace environment reduces the job satisfaction of employees which eventually leads to mental health issues. The study focuses on mapping the publication trends on happiness of employees at their workplace over the years. The mapping was done with the help of Scopus and VOSviewer. The study takes into consideration the research publication on workplace happiness since 2013 from Scopus database using ‘Employee Happiness at Workplace’ which showed around 104 publications related to happiness till Sept 2022. The database was refined and further analyzed by VOSviewer version 1.6.16. Though much research has been done on employee happiness and lot many scales are developed on the happiness index, but bibliometric analysis is yet to be carried out on workplace happiness, it's development, forms and factors. This analysis will bridge the gap of researchers and provide them directions to carry on the research for future.

Small business enterprises (SBEs) are a very critical element of the micro, small and medium enterprises (MSME) sector especially in the underdeveloped locations of the country. SBEs not only provide employment but also support the local economy by way of their products and services. In modern times, their presence on the digital platform is becoming essential and thus, these types of studies are required to bring to the table the issues and practices from the less represented sections of the sector. This study attempts to understand the responsiveness of the SBEs in Sikkim, India, and Bhutan in terms of their frequency of digital marketing (DM) usage. This study also attempts to understand the relationship between the factors affecting the practice or adoption of DM among the SBEs of Bhutan and Sikkim, India. For this purpose, empirical data were gathered from 320 SBEs from Sikkim and Bhutan representing the various sectors as defined by the national governments of the two countries. The SBEs of Bhutan and Sikkim are not found to be very active on the front of DM. The SBEs in these two locations need to become more active in using the digital platforms and tools to promote their products and services. The industry trends and government support in the form of infrastructural development are expected to play a vital role in orienting the SBEs into the adoption of DM in a better way. This study is crucial for the MSME sector, the government, telecom services providers, and local entrepreneurs.

After COVID-19, the tourism industry has been reshaped through a cycle of intertwined crises. So, the tourism industry has been the scene of discussions on how to proceed against vulnerabilities and uncertainties in recent years. Destinations have begun to think differently in terms of competitive advantage in order to survive. Therefore, the success of the tourism industry needs a change in mindset in order to keep up with the transformation accelerated by COVID-19. Regenerative tourism has triggered the search for a different mindset beyond sustainable tourism efforts by addressing responsibility and creativity together. As a result of these searches, regenerative tourism reveals a philosophical perspective as a mindset. Most of the studies on regenerative tourism contain conceptual clarification efforts. However, there is a need for a macro evaluation of regenerative tourism management on a destination basis. This chapter discusses the design of an appropriate policy and planning for the management of regenerative tourism. Regenerative tourism emphasizes a conscious intervention in the tourism industry with its creativity and innovative and responsible characteristics. This intervention can be evaluated within the scope of destination policy and planning for solving the problems about standardization and commercialization. Thus, it will conceptually be tried to put forward a planning and policymaking process that is suitable for regenerative tourism.

Adsorption parameters (e.g. Langmuir constant, mass transfer coefficient and Thomas rate constant) are involved in the design of aqueous-media adsorption treatment units. However, the classic approach to estimating such parameters is perceived to be imprecise. Herein, the essential features and performances of the ant colony, bee colony and elephant herd optimisation approaches are introduced to the experimental chemist and chemical engineer engaged in adsorption research for aqueous systems. Key research and development directions, believed to harness these algorithms for real-scale water treatment (which falls within the wide-ranging coverage of the Sustainable Development Goal 6 (SDG 6) ‘Clean Water and Sanitation for All’), are also proposed. The ant colony, bee colony and elephant herd optimisations have higher precision and accuracy, and are particularly efficient in finding the global optimum solution. It is hoped that the discussions can stimulate both the experimental chemist and chemical engineer to delineate the progress achieved so far and collaborate further to devise strategies for integrating these intelligent optimisations in the design and operation of real multicomponent multi-complexity adsorption systems for water purification.