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This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

To evaluate some of the current discussions about the possible impacts of social networks on the development of gastronomy in the Republic of Serbia. There could be either positive and/or negative impacts and this viewpoint provides some reflection on what the future might hold for some if not many tourism destinations in Serbia and the region when the tourism industry restarts after the pandemic of Covid-19 virus.

The research was conducted in December 2021, on a total of 244 respondents in three cities in Serbia. SPSS software was used, version 26.00, and the obtained data were analyzed by descriptive statistics. Then, to determine the structure of the questionnaire and the percentage of variance, an exploratory factor analysis was performed together with a higher order factor analysis, in order to obtain the desired number of factors. Subsequently, the authors used multiple regression analysis to confirm the significance of the predictors. The goal of the research was to determine whether, and to what extent, social networks can predict the choice of restaurants and gastronomic offers in Serbia. Serbian gastronomy has a great influence on the development of tourism, so this research has a wide scientific and practical contribution.

This paper provides a context and viewpoint on the possible implications of impacts of social networks on the development of gastronomy in the Republic of Serbia in the future. It has been proven that social networks can have an impact on the development of gastronomy and tourism itself.

To examine the impact of social networks on the development of gastronomy, the authors conducted a survey online due to the current Covid-19 pandemic. The limitation of this research was precisely that the authors did not have the opportunity to conduct the research live due to the Covid-19 pandemic. It is recommended that such surveys be conducted live in direct contact with respondents in the future in order to obtain a larger sample with fully completed questionnaires.

The importance of social networks is increasingly a topic of study of world research, especially when it comes to gastronomy, which is becoming increasingly important as an activity in the tourism industry. The results indicate that the greatest importance in predicting the choice of restaurants and gastronomic offers has social networks and marketing. The importance of the work is reflected in the recognition of the importance of social networks, in order to better place Serbian gastronomy.

This paper offers a synthesis of views that fosters an understanding of the possibility of impacts of social networks on the development of gastronomy in the Republic of Serbia before and after the Covid-19 pandemic.

The viewpoint proffered in this paper provides scope for a rapid evaluation of the current status of gastronomy tourism in Serbia which can help practitioners and researchers in the faster and better development of gastronomy and tourism.

The central idea of this research article is to examine the characteristics of Clairaut submersions from Lorentzian trans-Sasakian manifolds of type (α, β) and also, to enhance this geometrical analysis with some specific cases, namely Clairaut submersion from Lorentzian α-Sasakian manifold, Lorentzian β-Kenmotsu manifold and Lorentzian cosymplectic manifold. Furthermore, the authors discuss some results about Clairaut Lagrangian submersions whose total space is a Lorentzian trans-Sasakian manifolds of type (α, β). Finally, the authors furnished some examples based on this study.

This research discourse based on classifications of submersion, mainly Clairaut submersions, whose total manifolds is Lorentzian trans-Sasakian manifolds and its all classes like Lorentzian Sasakian, Lorenztian Kenmotsu and Lorentzian cosymplectic manifolds. In addition, the authors have explored some axioms of Clairaut Lorentzian submersions and illustrates our findings with some non-trivial examples.

The major finding of this study is to exhibit a necessary and sufficient condition for a submersions to be a Clairaut submersions and also find a condition for Clairaut Lagrangian submersions from Lorentzian trans-Sasakian manifolds.

The results and examples of the present manuscript are original. In addition, more general results with fair value and supportive examples are provided.

The aims of this paper is to prove that every semisimple Jordan algebra bundle is locally trivial and establish the decomposition theorem for locally trivial Jordan algebra bundles using the decomposition theorem of Lie algebra bundles.

Using the decomposition theorem of Lie algebra bundles, this paper proves the decomposition theorem for locally trivial Jordan algebra bundles.

Findings of this paper establish the decomposition theorem for locally trivial Jordan algebra bundles.

To the best of the author’s knowledge, all the results are new and interesting to the field of Mathematics and Theoretical Physics community.

In this study, we investigate what drives the MAX effect in the South Korean stock market. We find that the MAX effect is significant only for overpriced stocks categorized by the composite mispricing index. Our results suggest that investors' demand for the lottery and the arbitrage risk effect of MAX may overlap and negate each other. Furthermore, MAX itself has independent information apart from idiosyncratic volatility (IVOL), which assures that the high positive correlation between IVOL and MAX does not directly cause our empirical findings. Finally, by analyzing the direct trading behavior of investors, our results suggest that investors' buying pressure for lottery-like stocks is concentrated among overpriced stocks.

The goal of this article is to provide an overview of healthcare entrepreneurship, both in terms of its current trends and future directions.

The article engages in a systematic review of extant research on healthcare entrepreneurship using the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) as the review protocol and bibliometrics or scientometrics analysis as the review method.

Healthcare entrepreneurship research has fared reasonably well in terms of publication productivity and impact, with diverse contributions coming from authors, institutions and countries, as well as a range of monetary and non-monetary support from funders and journals. The (eight) major themes of healthcare entrepreneurship research revolve around innovation and leadership, disruption and technology, entrepreneurship models, education and empowerment, systems and services, orientations and opportunities, choices and freedom and policy and impact.

The article establishes healthcare entrepreneurship as a promising field of academic research and professional practice that leverages the power of entrepreneurship to advance the state of healthcare.

The article offers a seminal state of the art of healthcare entrepreneurship research.

This paper aims to identify, examine, and present an empirical research design of behavioral finance of potential investors during Covid-19.

A well-structured questionnaire was designed; a survey was conducted among potential investors using convenience sampling, and 200 valid responses were collected. The research work uses multiple regression and discriminant function analysis to evaluate the influence of cognitive factors on the financial decision-making of investors.

Recency and familiarity bias are proven to have the highest significant impact on the financial decisions of investors followed by confirmation bias. Overconfidence bias had a negligible effect on the decision-making process of the respondents and found insignificant.

Covid-19 is a temporary phase that may lead to changes in financial behavior and investors’ decisions in the near future.

The paper will help academicians, scholars, analysts, practitioners, policymakers and firms dealing with capital markets to execute their job responsibilities with respect to the cognitive bias in terms of taking financial decisions.

The present investigation attempts to fill the gap in the literature on the intended topic because it is evident from literature on the chosen subject that no study has been undertaken to evaluate the impact of cognitive biases on financial behavior of investors during Covid-19.

This study aims to assess the effect of water variation on bioethanol production from cassava peels (CP) using Saccharomyces cerevisiae yeast as the ethanologenic agent.

The milled CP was divided into three treatment groups in a small-scale flask experiment where each 20 g CP was subjected to two-stage hydrolysis. Different amount of water was added to the fermentation process of CP. The fermented samples were collected every 24 h for various analyses.

The results of the fermentation revealed that the highest ethanol productivity and fermentation efficiency was obtained at 17.38 ± 0.30% and 0.139 ± 0.003 gL⁻¹ h⁻¹. The study affirmed that ethanol production was increased for the addition of water up to 35% for the CP hydrolysate process.

The finding of this study demonstrates that S. cerevisiae is the key player in industrial ethanol production among a variety of yeasts that produce ethanol through sugar fermentation. In order to design truly sustainable processes, it should be expanded to include a thorough analysis and the gradual scaling-up of this process to an industrial level.

This paper is an original research work dealing with bioethanol production from CP using S. cerevisiae microbe.

1. Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

2. Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

3. Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

4. Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

Hydrolysis of cassava peels using 13.1 M H₂SO₄ at 100 ^oC for 110 min gave high Glucose productivity

Highest ethanol production was obtained at 72 h of fermentation using Saccharomyces cerevisiae

Optimal bioethanol concentration and yield were obtained at a hydration level of 35% agitation

Highest ethanol productivity and fermentation efficiency were 17.3%, 0.139 g.L⁻¹.h⁻¹

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

This study aims to measure impact of several firm-specific factors on alternative measures of leverage. The authors also aim to study impact of the subprime crisis on such associations.

The authors utilized an unbalanced panel data of 973 firm-year observations on 47 UK listed non-financial firms for the years 1990–2019. Book-based and market-based long-term and total leverage measures have been used as explained variables. The explanatory variables are profitability, size, two measures of growth, asset tangibility, non-debt tax shields, firm age and product uniqueness. Fixed effect and random effect models with clustered robust standard errors have been utilized for data analysis. To find the effect of subprime crisis, original dataset was split to create pre-crisis and post-crisis datasets.

The authors find that profitability significantly reduces leverage while firms having more tangible assets use significantly more debt in capital structure. Firm size and non-debt tax shield have statistically insignificant positive impact on leverage. Having more unique products reduces use of external debt, albeit insignificantly. Growth, when measured as market-to-book ratio, has inconsistent impact, whereas capital expenditure insignificantly reduces leverage. Age is found to be an insignificant predictor of leverage. After the subprime crisis, firms started relying more on internal fund instead of external debt, more particularly short-term debt. Having more collateral is gradually becoming more important for availing external debt.

Data limitations restrict generalization of the findings.

This is one of the pioneering attempts to show how subprime crisis altered the theoretical domain of capital structure research in the UK.