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Creativity is nowadays seen as a desirable goal in higher education. In artistic disciplines, creative processes are frequently employed to assess or evaluate different students' skills. The purpose of this study is to identify potential pitfalls for students involved in artistic practices in which being creative is essential.

Three focus groups involving Education Faculty members from different artistic disciplines allowed for the identification of several constraints when creativity was invoked. This initial study used a quantitative approach and took place in the “Universitat de Vic” (Catalonia, Spain).

Findings suggest a correlation with existing literature and simultaneously point at some nuances that require consideration: emerging aspects embedded in creative processes that may help decrease some limiting effects that being creative can generate.

The main limitations of this research derive from the very nature of the methodological approach. Focus group has been the single used source. Other means of collecting data, such as the analysis of programs, could be used in the future.

This case study, while culturally specific, offers a useful insight into the potential of further work in non-artistic disciplines but crucially across disciplines. It has tremendous value for the development of intercultural understanding in the higher education sector, specifically in terms of assessment.

This paper elucidates the role of anger in error management (EM) and organizational learning behaviors. The study explores how anger can catalyze learning, emphasizing its strategic implications.

A double-layered moderated-mediated model was developed and tested using data from 744 Chinese CEOs. The psychometric properties of the survey instrument were rigorously examined through structural equation modeling, and hypotheses were tested using Hayes's PROCESS macros.

The findings reveal that anger is a precursor for recognizing the value of significant errors, leading to a positive association with learning behavior among top management team members. Additionally, the study uncovers a triple interaction effect of anger, EM culture and supply chain disruptions on the value of learning from errors. Extensive experience and positive grieving strengthen the relationship between recognizing value from errors and learning behavior.

This study uniquely integrates affect-cognitive theory and organizational learning theory, examining anger in EM and learning. The authors provide empirical evidence that anger can drive error value recognition and learning. The authors incorporate a more fine-grained approach to leadership when including executive anger as a trigger to learning behavior. Factors like experience and positive grieving are explored, deepening the understanding of emotions in learning. The authors consider both negative and positive emotions to contribute to the complexity of organizational learning.

(1) A concern often expressed in relation to cryptocurrencies is the environmental impact associated with increasing energy consumption and mining pollution. Controversy remains regarding how environmental attention and public concerns adversely affect cryptocurrency prices. Therefore, the paper aims to introduce the index of cryptocurrency environmental attention (ICEA), which aims to capture the relative extent of media discussions surrounding the environmental impact of cryptocurrencies. (2) The impacts of cryptocurrency environmental attention on long-term macro-financial markets and economic development remain part of undeveloped research fields. Based on these factors, the paper will further examine the effects of the ICEA on financial markets or economic developments.

(1) The paper introduces a new index to capture cryptocurrency environmental attention in terms of the cryptocurrency response to major related events through gathering a large amount of news stories around cryptocurrency environmental concerns – i.e. >778.2 million news items from the LexisNexis News & Business database, which can be considered as Big Data – and analysing that rich dataset using variety of quantitative techniques. (2) The vector error correction model (VECM) and structural VECM (SVECM) [impulse response function (IRF), forecast error variance decomposition (FEVD) and historical decomposition (HD)] are useful for characterising the dynamic relationships between ICEA and aggregate economic activities.

(1) The paper has developed a new measure of attention to sustainability concerns of cryptocurrency markets' growth, ICEA. (2) ICEA has a significantly positive relationship with the UCRY indices, volatility index (VIX), Brent crude oil (BCO) and Bitcoin. (3) ICEA has a significantly negative relationship with the global economic policy uncertainty (GlobalEPU) and global temperature uncertainty (GTU). Moreover, ICEA has a significantly positive relationship with the industrial production (IP) in the short term, whilst having a significantly negative relationship in the long term. (4) The HD of the ICEA displays higher linkages between environmental attention, Bitcoin and UCRY indices around key events that significantly change the prices of digital assets.

The ICEA is significant in the analysis of whether cryptocurrency markets are sustainable regarding energy consumption requirements and negative contributions to climate change. Understanding of the broader impacts of cryptocurrency environmental concerns on cryptocurrency market volatility, uncertainty and environmental sustainability should be considered and developed. Moreover, the paper aims to point out future research and policy legislation directions. Notably, the paper poses the question of how cryptocurrency can be made more sustainable and environmentally friendly and how governments' cryptocurrency policies can address the cryptocurrency markets.

(1) The paper develops a cryptocurrency environmental attention index based on news coverage that captures the extent to which environmental sustainability concerns are discussed in conjunction with cryptocurrencies. (2) The paper empirically investigates the impacts of cryptocurrency environmental attention on other financial or economic variables [cryptocurrency uncertainty (UCRY) indices, Bitcoin, VIX, GlobalEPU, BCO, GTU index and the Organisation for Economic Co-operation and Development IP index]. (3) The paper provides insights into making the most effective use of online databases in the development of new indices for financial research.

Whilst blockchain technology has a number of useful implications and has great potential to transform several industries, issues of high-energy consumption and CO2 pollution regarding cryptocurrency have become some of the main areas of criticism, raising questions about the sustainability of cryptocurrencies. These results are essential for both policy-makers and for academics, since the results highlight an urgent need for research addressing the key issues, such as the growth of carbon produced in the creation of this new digital currency. The results also are important for investors concerned with the ethical implications and environmental impacts of their investment choices.

(1) The paper provides an efficient new proxy for cryptocurrency and robust empirical evidence for future research concerning the impact of environmental issues on cryptocurrency markets. (2) The study successfully links cryptocurrency environmental attention to the financial markets, economic developments and other volatility and uncertainty measures, which has certain novel implications for the cryptocurrency literature. (3) The empirical findings of the paper offer useful and up-to-date insights for investors, guiding policy-makers, regulators and media, enabling the ICEA to evolve into a barometer in the cryptocurrency era and play a role in, for example, environmental policy development and investment portfolio optimisation.

In large parts of the world, income inequality has been rising in recent decades. Other regions have experienced declining trends in income inequality. This raises the question of which mechanisms underlie contrasting observed trends in income inequality around the globe. To address this research question in an empirical analysis at the aggregate level, we examine a global sample of 73 countries between 1981 and 2010, studying a broad set of drivers to investigate their interaction and influence on income inequality. Within this broad approach, we are interested in the heterogeneity of income inequality determinants across world regions and along the income distribution. Our findings indicate the existence of a small set of systematic drivers across the global sample of countries. Declining labour income shares and increasing imports from high-income countries significantly contribute to increasing income inequality, while taxation and imports from low-income countries exert countervailing effects. Our study reveals the region-specific impacts of technological change, financial globalisation, domestic financial deepening and public social spending. Most importantly, we do not find systematic evidence of education’s equalising effect across high- and low-income countries. Our results are largely robust to changing the underlying sources of income Ginis, but looking at different segments of income distribution reveals heterogeneous effects.

The paper proposes an efficient and insightful approach for solving neutral delay differential equations (NDDE) with high-frequency inputs. This paper aims to overcome the need to use a very small time step when high frequencies are present. High-frequency signals abound in communication circuits when modulated signals are involved.

The method involves an asymptotic expansion of the solution and each term in the expansion can be determined either from NDDE without oscillatory inputs or recursive equations. Such an approach leads to an efficient algorithm with a performance that improves as the input frequency increases.

An example shall indicate the salient features of the method. Its improved performance shall be shown when the input frequency increases. The example is chosen as it is similar to that in literature concerned with partial element equivalent circuit (PEEC) circuits (Bellen et al., 1999). Its structure shall also be shown to enable insights into the behaviour of the system governed by the differential equation.

The method is novel in its application to NDDE as arises in engineering applications such as those involving PEEC circuits. In addition, the focus of the method is on a technique suitable for high-frequency signals.

Background: Geostatistics focuses on spatial or spatiotemporal datasets. Geostatistics was initially developed to generate probability distribution predictions of ore grade in the mining industry; however, it has been successfully applied in diverse scientific disciplines. This technique includes univariate, multivariate, and simulations. Kriging geostatistical methods, simple, ordinary, and universal Kriging, are not multivariate models in the usual statistical function. Notwithstanding, simple, ordinary, and universal kriging techniques utilize random function models that include unlimited random variables while modeling one attribute. The coKriging technique is a multivariate estimation method that simultaneously models two or more attributes defined with the same domains as coregionalization.

Objective: This study investigates the impact of populations on traffic volumes as a variable. The additional variable determines the strength or accuracy obtained when data integration is adopted. In addition, this is to help improve the estimation of annual average daily traffic (AADT).

Methods procedures, process: The investigation adopts the coKriging technique with AADT data from 2009 to 2016 from Montana, Minnesota, and Washington as primary attributes and population as a controlling factor (second variable). CK is implemented for this study after reviewing the literature and work completed by comparing it with other geostatistical methods.

Results, observations, and conclusions: The Investigation employed two variables. The data integration methods employed in CK yield more reliable models because their strength is drawn from multiple variables. The cross-validation results of the model types explored with the CK technique successfully evaluate the interpolation technique's performance and help select optimal models for each state. The results from Montana and Minnesota models accurately represent the states' traffic and population density. The Washington model had a few exceptions. However, the secondary attribute helped yield an accurate interpretation. Consequently, the impact of tourism, shopping, recreation centers, and possible transiting patterns throughout the state is worth exploring.

A global trend of type 2 diabetes prevalence is rising. Preventing and managing of systemic and dental complications is crucial to decrease negative effects on glycemic control. The purpose of this paper is to estimate the efficacy of Brief Lifestyle Change in conjunction with Dental Care (Brief-LCDC) Programs to decrease glycemic level and improve periodontal status in patients with type 2 diabetes.

Health Center 54 conducted randomized controlled trial among 192 patients (96 intervention and 96 control) from February to August 2018. Group education for lifestyle modification, individual oral hygiene instruction and lifestyle counseling by motivational interviewing was provided to the intervention group at baseline. Motivation of lifestyle modification every month by multimedia was also provided to the intervention group. The usual program was provided to the control group. At baseline and a six-month follow-up, glycemic level and periodontal status were assessed from participants. Data were analyzed by descriptive statistic, t-test, χ² test, Fisher’s exact test, Repeated measure ANOVA and multiple linear regression.

Glycemic level and periodontal status were lower in the intervention group than the control group at the sixth-month followed up with statistical significances. Glycemic level and periodontal status had negatively correlated to intervention group with statistically significant.

Brief-LCDC Program which incorporated lifestyle modification and oral health care had efficacious to decrease glycemic level and improve periodontal status in patients with type 2 diabetes. Early prevention program by Brief-LCDC Program is crucial to prevent dental complications.

The aim of this paper is to demonstrate the use of historical building performance data to identify potential issues with the build quality and operation of a building, as a means of narrowing the scope of in-depth further review.

The response of a room to the difference between internal and external temperatures is used to demonstrate patterns in thermal response across monitored rooms in a single building, to clearly show where rooms are under-performing in terms of their ability to retain heat during unconditioned hours. This procedure is applied to three buildings of different types, identifying the scope and limitation of this method and indicating areas of building performance deficiency.

The response of a single space to changing internal and external temperatures can be used to determine whether it responds differently to other monitored buildings. Spaces where thermal bridging and changes in use from design were encountered exhibit noticeably different responses.

Application of this methodology is limited to buildings where temperature monitoring is undertaken both internally for a variety of spaces, and externally, and where knowledge of the uses of monitored spaces is available. Naturally ventilated buildings would be more suitable for analysis using this method.

This paper contributes to the understanding of building energy performance from a data-driven perspective, to the knowledge on the disparity between building design intent and reality, and to the use of basic commonly recorded performance metrics for analysis of potentially detrimental building performance issues.

This study aims to measure the relationship between demand and exchange rate shocks in the tourism industry.

A panel data set is constructed covering the period between 1995 and 2017, and the data set includes the top 26 countries that host 10 million tourists and above in the world as of 2017. The standard errors of the series are used as an indicator of shocks. First, the cross-sectional dependency, stationarity and the homogeneity of the series are examined; second, a panel cointegration analysis is implemented; third, long-term panel cointegration coefficients are analyzed with Dynamic Common Correlated Effects (DCCE) approach; and, finally, Dumitrescu and Hurlin’s (2012) Granger non-causality test is used to detect the causality.

The preliminary analyses show that the variables are cross-sectional dependent and heterogeneous and are stationary in their first difference; hence, the effects of the shocks are temporary. On the other hand, as a result of the panel cointegration analysis, it is found that both series are cointegrated over the long-term. However, the long-term coefficients estimated with the DCCE approach are found not to be statistically significant. Finally, as a result of the Dumitrescu and Hurlin’s (2012) Granger non-causality test, it is concluded that there is a causality running from exchange rate shocks to demand shocks.

To the best of the authors’ knowledge, the cointegration between the tourism demand shocks and exchange rates shocks has not been investigated before, and therefore, this study is considered to be a pioneering study that will contribute to the literature.