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Social media offers better prospect for travellers to seek for travel information, choose a location and share their personal travel experiences. The current study aims to examine how tourists gather information from YouTube shorts and its influence on their intention to use it for selection of an ecotourism destination.

The conceptual model of the study is constructed on information adoption model (IAM). An adaptive questionnaire was utilised to gather 374 valid responses. Partial least square structural equational modelling (PLS-SEM) was utilised for data analysis.

The results showed a positive significant relationship between all the constructs of IAM. The findings also show significant mediating effect of attitude and moderating effect of involvement between information quality and adoption also between source credibility and information usefulness.

This study will help destination marketers by providing valuable insights to them to promote their destinations more effectively on social media platforms. This study will also help travel influencers in understanding what are the factors they should focus on while providing information about ecotourism destination. It will additionally help the local economy and conveys a message to travellers about responsible travel behaviour when selecting or visiting ecotourism destination.

This is the very first attempt to investigate the adoption of YouTube shorts information and formulating behavioural intentions to utilise it for ecotourism destination selection.

This study aims to investigate whether the changes in gender composition of bank board affects Vietnamese bank stability efficiency.

This research covers a panel of 27 commercial banks in Vietnam over a 14-year period from 2007 to 2020. The two-step system generalized method of moments is used to estimate the gender diversity–Vietnamese bank stability efficiency nexus.

The authors find that a greater degree of board gender diversification enhances bank stability efficiency and reduces bank risk-taking in Vietnam. The relationship between gender diversity and the stability efficiency of Vietnamese banks is still valid under the influence of regulatory capital sufficiency and during the financial crisis. These findings are robust to alternative proxies for risk indicators and consistent with the perspectives of stakeholder and behavior theory.

Although this research revisits the relationship between gender diversity and bank risk-taking, it is the first attempt to explore the role of women on board in enhancing the stability efficiency of banks, using the stochastic frontier approach. These findings shed light on the function of gender diversity as a governance instrument for mitigating risk in an emerging market context.

Informal migrant workers and street vendors have long been recognized as vulnerable groups in urban areas of Global South countries. However, limited studies exist on the economic challenges faced by migrant street vendors during crises. We aim to address this gap by shedding light on their livelihood and welfare losses during a public health crisis.

This research uses descriptive and qualitative analyzes to triangulate the results. Data are derived from surveys and in-depth interviews with migrant street vendors in the two biggest cities in Vietnam during the COVID-19 pandemic.

The street vendors experienced significant business loss and consumption reduction during social distancing as well as encountered difficulties in recovering their businesses in the “new normal.” These adverse consequences were also found to disproportionately affect women vendors. Additionally, despite adopting various strategies and mitigation mechanisms to sustain their businesses and consumption, these efforts proved insufficient.

This research underscores the importance of short-term and long-term urban policies aimed at supporting and promoting the social inclusion of street vendors, particularly migrant and women vendors.

This research represents one of the early attempts to explore the adverse effects of a public health crisis on migrant street vendors and to examine whether the crisis disproportionately affected vendors from different genders and educational backgrounds. It also examines their business recovery in the “new normal.”

The study examines the mediating mechanisms of job engagement (JE) and organizational engagement (OE) in the relationship between organizational career development (OCD) and retention of millennial employees.

Data from a total of 422 employees working in information technology organizations in India were collected through a structured questionnaire survey and subjected to analysis using structural equation modelling (SEM) with a confidence level of 95 percent. The convenience sampling technique for collecting data and descriptive research design was used in the study.

Results of SEM indicate that there is a positive relationship between OCD and employee retention (ER), which is mediated by JE and OE partially.

The study contributes by establishing the mediating role played by JE and OE in the relationship between OCD and ER.

This study draws on social influence and social comparison theories to investigate the effect of social media influencers on intention to visit with the mediating role of upward social comparison. It studies the reasons underlying people's intention to visit a destination from an emotional perspective.

PLS-SEM models were applied to a total of 527 responses.

This study provides empirical evidence supporting the Source Credibility Model's elements within the context of influencer marketing and travel intentions. Furthermore, it expands the current knowledge of upward social comparison emotions by reporting that upward contrastive emotions would partially mediate the relationship between expertise and intention to visit, and that upward assimilative emotions would fully mediate the relationship between attractiveness and intention to visit while partially mediating the relationship between trustworthiness and expertise and intention to visit.

The article adds new insights to tourism marketing as well as helps both destination marketers and travel influencers. For marketers, it is advised to collaborate with credible influencers known for expertise and trustworthiness, leveraging their perspectives to rebuild travel confidence and reassure tourists about safety measures. Travel influencers are recommended to convey their intrinsic passion and enthusiasm through their posts to create an inspiring connection with the audiences.

This paper is the first to address the relationship between travel influencers and intention to visit with the mediation role of both positive and negative emotions.

The aim of this paper was to examine the interrelationships between Maslow’s motivated needs in relation to employees’ personal and workplace spirituality experiences.

Regression analysis using a cross-sectional, convenience sampling approach of 158 US employees responding to survey questions using a Qualtrics survey related to their demographics, motivated needs, daily spirituality experiences, workplace spirituality, work spirituality experiences and work-related flow.

Correlation analyses provided support for Maslow’s hierarchy of needs in relation to employees’ daily spiritual experiences, workplace spirituality, work spirituality experiences and work-related flow. Regression analyses also identified the specific Maslow needs that served as predictive factors in relation to employees’ personal and workplace spirituality. Findings and conclusions are also discussed in relation to employees and organizations.

Currently, there are no correlation studies that have examined workplace spirituality as an ethical behavior in the workplace and Maslow’s hierarchy of needs. This correlation gap is notable because further examination of Maslow’s hierarchy of needs as a theoretical framework in relation to employees’ spirituality can be particularly valuable for contemporary work settings. Consider that today’s work environment is faced with dynamic and unique factors, and each of these factors not only changes the work environment but also they significantly drive or minimize employee motivation. Three such factors include new generations of employees with unique values entering the workforce and the great resignation and quiet quitting.

The study identifies that Maslow’s belonging, esteem and self-transcendence are related positively to employees’ spiritual experiences in the workplace. When these needs are fulfilled in the work environment, employees may be more likely to engage in spiritual practices at work, such as participating in yoga, prayer and meditation and in fulfilling one’s motivated needs and spirituality, employees are able to pursue their true purpose in the workplace.

This study extends the literature regarding understanding the value of workplace spirituality as a positive outcome for the employees and organizations.

This study aims to examine the plane wave reflection problem in micropolar orthotropic magneto-thermoelastic half space, considering the influence of impedance as a boundary in a nonlocal elasticity.

This study presents the novel formulation of governing partial differential equations for micropolar orthotropic medium with impact of nonlocal thermo-elasticity under magnetic field.

This study provides the numerical results validation for a particular numerical data and expression for the amplitude ratios of reflected waves and identifies the existence of four different waves, namely, quasi longitudinal displacement qCLD-wave, quasi thermal wave qCT-wave, quasi transverse displacement qCTD-wave and quasi-transverse micro-rotational qCTM-wave. The study derives the velocity equation giving the speed and phase velocity of these waves. The study also shows that the small-scale size effect gives significant impact on phase velocity.

The graphical analysis examines the variation of speeds and coefficients of attenuation of these waves due to frequency, magnetic field and nonlocal parameters. Also, significant conclusions on the variation of reflection coefficient against nonlocal parameter, frequency, impedance parameter and angle of incidence are provided graphically.

The creation of more effective micropolar orthotropic anisotropic materials which are very useful in the daily life and their applications in earth science are greatly impacted by the findings of this study.

The authors of the submitted document initiated and produced it collectively, with equal contributions from all members.

This study is the maiden attempt to understand the effect of specific human resource practices (HRPs) on employee retention (ER) with the mediation of job satisfaction (JS) and moderation of work experience (WE) and job hopping (JH) in the context of the textile industry.

This study adopted a quantitative methodology and applied quota sampling to gather data from employees (n = 365) of leading textile companies in India. The conceptual model and hypotheses were tested with the help of Partial Least Squares-Structural Equation Modelling (PLS-SEM).

The findings of a path analysis revealed that compensation and performance appraisal (CPA) have the highest impact on JS followed by employee work participation (EWP). On the other hand, EWP had the highest impact on ER followed by grievance handling (GRH). The study revealed that JS significantly mediates between HRPs like CPA and ER. During Multi-group analysis (MGA) it was found that the importance of EWP and health and safety (HAS) was more in employee groups with higher WE, but it was the opposite in the case of CPA. In the case of JH behavior, the study observed that EWP leads to JS in loyal employees. Similarly, JS led to ER, and the effect was more pronounced for loyal employees.

In the context of the Indian textile industry, this work is the first attempt to comprehend how HRPs affect ER. Secondly, it confirmed that JS is not a guaranteed mediator between HRPs and ER, it could act as an insignificant, partial or full mediator. Additionally, this study establishes the moderating effects of WE and JH in the model through multigroup analysis.

Natural calamities like earthquakes, floods and epidemics/pandemics like COVID-19 significantly disrupt almost all the supply networks, ranging from medicines to numerous daily/emergency use items. Supply Chain Resilience is one such option to overcome the impact of the disruption, which is achieved by developing supply chain factors with Artificial Intelligence (AI) and Big Data Analytics (BDA).

This research examines how organizations using AI and BDA can bring resilience to supply chains. To achieve the objective, the authors developed the methodology to gather useful information from the literature studied and developed the Total Interpretive Structural Modeling (TISM) by consulting 44 supply chain professionals. The authors developed a quantitative questionnaire to collect 229 responses and further test the model. With the analysis, a conceptual and comprehensive framework is developed.

A major finding, this research advocates that supply chain resilience is contingent upon utilizing supply chain analytics. An empirical study provides further evidence that the utilization of supply chain analytics has a positive and favorable effect on the flexibility of demand forecasting to inventory management, resulting in increased efficiency.

Few studies demonstrate the impact of advanced technology in building resilient supply chains by enhancing their factors. To the best of the authors' knowledge, no earlier researcher has attempted to infuse AI and BDA into supply chain factors to make them resilient.

The study aims to determine the the optimal value of output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The performance parameters like brake thermal efficiency (BTE) and brake specific energy consumption (BSEC), whereas CO emission, HC emission, CO₂ emission, NO_x emission, exhaust gas temperature (EGT) and opacity are the emission parameters measured during the test. Tests are conducted for 2, 6 and 10 kg of load, 16.5 and 17.5 of CR.

In this investigation, the first engine was fueled with 100% diesel and 100% Calophyllum inophyllum oil in single-fuel mode. Then Calophyllum inophyllum oil with producer gas was fed to the engine. Calophyllum inophyllum oil offers lower BTE, CO and HC emissions, opacity and higher EGT, BSEC, CO₂ emission and NO_x emissions compared to diesel fuel in both fuel modes of operation observed. The performance optimization using the Taguchi approach is carried out to determine the optimal input parameters for maximum performance and minimum emissions for the test engine. The optimized value of the input parameters is then fed into the prediction techniques, such as the artificial neural network (ANN).

From multiple response optimization, the minimum emissions of 0.58% of CO, 42% of HC, 191 ppm NO_x and maximum BTE of 21.56% for 16.5 CR, 10 kg load and dual fuel mode of operation are determined. Based on generated errors, the ANN is also ranked for precision. The proposed ANN model provides better prediction with minimum experimental data sets. The values of the R² correlation coefficient are 1, 0.95552, 0.94367 and 0.97789 for training, validation, testing and all, respectively. The said biodiesel may be used as a substitute for conventional diesel fuel.

The blend of Calophyllum inophyllum oil-producer gas is used to run the diesel engine. Performance and emission analysis has been carried out, compared, optimized and validated.