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Establishing and developing digital science and education evaluation platforms (DSEEPs) have several practical implications for the development of China's science, technology and education. Identifying and analyzing the key factors influencing DSEEP user experience (UX) can improve the users' willingness to use the platform and effectively promote its sustainable development.

First, a literature survey, a five-element model of UX and semi-structured interviews were used in this study to develop a DSEEP UX-influencing factor model, which included five dimensions and 22 influencing factors. Second, the model validity was verified using questionnaire data. Finally, the key influencing factors were identified and analyzed using a fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) method.

Fourteen influencing factors, including diverse information forms and comprehensive information content, are crucial for the DSEEP UX. Its optimization path is “‘Function Services’ → ‘Information Resources’ → ‘Interaction Design’ → ‘Interface Design’ and ‘Visual Design’.” In this regard, platform managers can take the following measures to optimize UX: strengthening functional services, improving information resources, enhancing the interactive experience and considering interface effects.

This study uses a combination of qualitative and quantitative research methods to determine the key influencing factors and optimization path of DSEEP UX. Optimization suggestions for UX are proposed from the perspective of platform managers, who provide an effective theoretical reference for innovating and developing a DSEEP.

Investors who can transfer their savings to investments in a well-regulated market benefit not only themselves but also economic development. Hence, it is crucial for fund owners to evaluate their stock market investment decisions. The goal of the study is to understand which model determines the asset returns most efficiently. In this regard, the validity of single and multi-index asset pricing models (capital asset pricing model-CAPM and Fama–French models) has been examined in the Turkish Stock Exchange for 2009–2020, with the quantile regression (QR) approach.

On 18 portfolios comprised of quoted stocks in the Istanbul Stock Exchange 100 (ISE-100/BIST-100), we test the CAPM, the Fama and French three factor model (FF3) and the Fama and French five factor model (FF5). Empirical analyses have been carried out via QR approach regressing the portfolios' average weekly excess returns on risk premium/market factor (Rm-Rf), firm size, book value/market value (B/M), profitability and investments factors. QR estimation has been employed since QR is more effective and provides a better definition of the distribution’s tails.

Our empirical findings have revealed that the average excess weekly returns can be explained more strongly via CAPM. Moreover, Fama and French models are expected to give more reliable result with more data, whereas the market premium would give robust results for the Turkish Capital Market.

Individuals investing in financial assets must find the price model that best fits the market. The return can be approximated in the most appropriate manner using the right variables.

The study differs from other research by comparing the asset pricing models via examining the assets' weekly returns with QR in the Istanbul Stock Exchange 100 (ISE-100).

This study aims to develop a model for readiness measurement and to study readiness levels for online testing of undergraduate students in Thailand’s distance education programs.

In total, 870 undergraduate students enrolled in the 2022 academic year of a Thai university were sampled for the study. The samples were divided into two groups: Group 1 comprised 432 students who underwent exploratory factor analysis (EFA) and Group 2 comprised 438 students who underwent second-order confirmatory factor analysis (CFA). Both were multi-stage random samples. Descriptive statistics, item-total correlations (ITCs), coefficient correlations, EFA and second-order CFA were used.

The readiness for the online testing model comprised 5 factors and 33 indicators. These included self-efficacy (SE) in utilizing technology (nine indicators), self-directed learning (SL) for readiness testing (six indicators), adequacy of technology (AT) for testing (five indicators), acceptance of online testing (AC) (seven indicators) and readiness training for testing (six indicators). The model was congruent with empirical data, and the survey results indicated that students were highly prepared at the “high” level.

This study disclosed several factors and indicators involved in the readiness for online testing. The university may use these findings in preparing its students for online testing for better achievement.

These findings may serve as a framework for the analysis of the readiness issues for online testing of undergraduate students and also offer guidance to the universities preparing to offer online testing.

The objective of this study was to investigate the impacts of personality traits and the ability to detect fake news on information avoidance behavior. It also examined the effect of personality traits on the ability to detect fake news.

The sample population included Shiraz University students who were studying in the second semester of academic year 2021 in different academic levels. It consisted of 242 students of Shiraz University. The Big Five theory was used as the theoretical background of the study. Moreover, the research instrument was an electronic questionnaire consisting of the three questionnaires of the ability to detect fake news (Esmaeili et al., 2019, inspired by IFLA, 2017), the Big Five personality traits (Goldberg, 1999) and information avoidance (Howell and Shepperd, 2016). The statistical methods used to analyze the data were Pearson correlation and stepwise regression, which were performed through SPSS software (version 26).

The results showed that from among the five main personality factors, only neuroticism had a positive and significant effect on information avoidance. In addition, the ability to detect fake news had a significant negative effect on information avoidance behavior. Further analyses also showed positive and significant effects of openness to experience and extraversion on the ability to detect fake news. In fact, the former had more predictive power.

Following the Big Five theory considering COVID-19 information avoidance and the ability to detect COVID-19 fake news, this study shifted the focus from environmental factors to personality factors and personality traits. Furthermore, this study introduced the ability to detect fake news as an influential factor in health information avoidance behaviors, which can be a prelude for new research studies.

The present study applied the five main personality factors theory in the context of information avoidance behavior and the ability to detect fake news, and supported the effect of personality traits on these variables.

Influenced by factors such as fluctuations in market supply and demand and the rapid development of new technologies, manufacturing companies are facing greater challenges to transform and upgrade. The existing relevant studies about sustainable innovation capabilities mostly focus on classification of innovation or from a static resource-based view and less on quantitative measurement from a dynamic perspective and inter-organizational relationships. This paper takes a dynamic capabilities and social capital theory, explore the concept and dimensions of sustainable innovation capabilities and then makes development of a new scale.

This paper uses a combination of qualitative and quantitative research methodologies to develop a measure of sustainable innovation capabilities in two studies. Grounded theory methodology is used to explore the concept definition and dimensions of sustainable innovation capabilities. Exploratory factor analysis and confirmatory factor analysis are conducted to refine and validate the factor structure, and then the authors developed the sustainable innovation capabilities scale.

The results show that sustainable innovation capabilities composed of ideation capabilities, opportunity capture capabilities, agile learning, creative inheritance and networking capabilities. The sustainable innovation capabilities that firms should possess are reflected at the firm level and inter-organizational relationship level, and the culture-specific dimension of creative inheritance reflects the influence of national and organizational culture.

The research reveals the internal driving force of the manufacturer's sustainable innovation capabilities, as well as the role and uniqueness embodied in the specific culture, providing a new perspective for improving the manufacturer's sustainable innovation capabilities.

This paper aims to explore the dynamic relationship between ESG scores and REITS returns. The overarching goal is to provide a better understanding of how ESG considerations impact financial performance across different temporal contexts.

Using a sample of 175 European Equity REITs, this analysis combines numerical ESG scores with the Fama-French model, employing both random and fixed effects methods. It integrates individual REIT data and the HESGL (High ESG Scores Minus Low ESG Scores) factors to assess their impact on REIT returns.

The findings highlight divergent patterns between the numerical ESG score and the HESGL factor concerning REIT returns. While the numerical ESG score displays a negative impact in later periods, the HESGL factor demonstrates a positive effect during prosperous times but loses significance during crises.

This research contributes original insights by emphasizing the importance of temporal segmentation in understanding the nuanced and evolving nature of the relationship between ESG scores and REITs’ returns. The study provides a comprehensive analysis and highlights divergent outcomes that are essential for a better interpretation of ESG impacts on real estate investments.

This study aims to adapt and validate the Job Crafting Scale (JCS), a measure based on the conceptualization of job crafting of the job demands–resources theory, for a sample of Portuguese workers and to test its psychometric properties regarding validity (factor, convergent, discriminant, and criterion) and reliability.

Two subsamples (n1 = 315 and n2 = 329) of Portuguese workers aged 18 years old and over participated in this research. Exploratory factor analysis and confirmatory factor analysis were used to assess the factor structure.

The results indicated that the Portuguese version of the JCS, with 18 items, has a factor structure composed of four-correlated factors. Furthermore, the results demonstrated the existence of factor, discriminant, and criterion validity, as well as reliability.

This study provides a job crafting measure adapted to the Portuguese language that can serve as a diagnostic tool for workers and organizations.

Este estudio tuvo como objetivo adaptar y validar la Job Crafting Scale (JCS), una medida basada en la conceptualización de job crafting de la Teoría de Demandas-Recursos, para una muestra de trabajadores portugueses y probar sus propiedades psicométricas en cuanto a validez (factor, convergente, discriminante y de criterio) y confiabilidad.

En esta investigación participaron dos submuestras (n1 = 315 y n2 = 329) de trabajadores portugueses de 18 años o más. Se utilizó un análisis factorial exploratorio y un análisis factorial confirmatorio para evaluar la estructura factorial.

Los resultados indicaron que la versión portuguesa del JCS, con 18 ítems, tiene una estructura factorial compuesta por cuatro factores correlacionados. Además, los resultados demostraron la existencia de validez factorial, discriminante y de criterio, así como confiabilidad.

Este estudio proporciona una medida de job crafting adaptada a la lengua portuguesa que puede servir como herramienta de diagnóstico para trabajadores y organizaciones.

Este estudo teve como objetivo adaptar e validar a Job Crafting Scale (JCS), uma medida baseada na conceptualização de job crafting da Teoria das Exigências-Recursos, numa amostra de trabalhadores portugueses e testar as suas propriedades psicométricas quanto à validade (fatorial, convergente, discriminante e de critério) e fiabilidade.

Duas subamostras (n1 = 315 e n2 = 329) compostas por trabalhadores portugueses com 18 ou mais anos foram recolhidas. Foram utilizadas uma análise fatorial exploratória e uma análise fatorial confirmatória para analisar a estrutura fatorial.

Os resultados obtidos indicaram que a versão portuguesa da JCS, composta por 18 itens, possui uma estrutura fatorial composta por quatro fatores correlacionados. Além disso, os resultados demonstraram a existência de validade fatorial, discriminante e de critério, bem como de fiabilidade.

Este estudo fornece uma medida de job crafting adaptada para a língua portuguesa que pode servir como ferramenta de diagnóstico para trabalhadores e organizações.

This study aims to examine the relationship between investor gambling preferences and stock returns, using data for all firms listed in Shanghai A-share market during 2016 and 2021.

This study employs price and trading volume data to capture the behavioral characteristics and gambling preferences of investors. Using the Fama-French three-factor and five-factor models to estimate benchmark returns, this study investigates whether investing in gambling stocks can yield positive excess returns.

The study reveals that stocks identified as gambling stocks generate high returns in the month they are identified as such but subsequently experience a significant drop in excess returns compared to non-gambling stocks over the following one to six months. These results are found to be consistent across different methods used to classify gambling stocks and across various industry sectors.

This research provides insights into the risk-return tradeoff of different stock types and the factors that fuel irrational investment behavior. This research underscores the importance of considering the behavioral elements of investment, particularly in emerging markets where individual investors have a significant impact.

This study advises investors to avoid adopting a gambler or speculative mindset and instead make well-informed and calculated investment decisions that are in line with investors financial objectives and risk appetite. This approach can help create a more stable and sustainable financial market.

This study provides new evidence on the relationship between gambling preferences and future stock returns in financial markets and sheds new light on the important role of irrational factors in investment decisions.

After considering the price reversal among countries' indices as a global, coordinated and generalized phenomenon, this paper aims to examine the profitability of the reversal strategy internationally and find an economically essential and predictive reversal effect. Indices' portfolios form based on the prior 48 months; prior losers outperform prior winners by 8.86% per year during the subsequent 48 months. Interestingly, the reversal effect is substantially stronger for emerging countries, yielding 14.04% annually. It remains profitable post-globalization, countering the concern of whether the integration of equity markets synchronized the price reversal worldwide. Returns' differences consistent with portfolio formation approaches are also observed.

This study follows the methodology De Bondt and Thaler (1985) set out and uses the same methodological framework Wouassom et al. (2022) put forward. Nevertheless, this study does not focus on stocks. Still, it employs global equity indices from the viewpoint of an international investor who can switch between worldwide equity indices using a contrarian trading strategy.

My findings indicate that reversal strategies with overlapping portfolios are profitable over the entire sample period and every formation and holding period. These returns are highly statistically significant and vary considerably from one horizon to another. More importantly, the reversal strategies remain, on average, profitable and significant in the period post-1994 but are not particularly distinctive, which implies that the reversal effect survives the globalization impact and indicates that the integration of equity markets together with the international correlation among markets do not synchronize the prices reversal effect around the world given that.

Further work would be recommended to study a more extended period dating back to the nineteenth century or the Victorian Era, characterised by rapid economic development in almost every domain, to verify if reversal is historically compensation for carrying risks exclusively during contraction.

My analysis takes on particular significance given the association between lagged market movement in share prices and investors’ optimism that appears among traders, generating an increasing reversal effect (Siganos and Chelley-Steley, 2006) and has direct implications for predicting and controlling trading costs associated with asset allocation strategies.

The difficulty with using the reversal strategy to uncover the long-term return reversal effects in the equity markets today resides in the fact that the globalization of the economy has fuelled the concentration of assets within institutional investors. The critical insight is that the concentration of equity in the hands of institutional investors activated international equity trading. These institutional investors seek to maximize their shareholder value from the opportunity by simultaneously dealing in many markets while constructing and holding portfolios that include assets from various countries using highly profitable investment strategies such as reversal.

To the best of the authors’ knowledge, this is the first paper to show an easily implemented contrarian strategy that switches back and forth between country indices and generates extraordinarily high abnormal returns of more than 8.86% per annum. We also show that these returns compensate for global risks and for investors ready to take them during contraction.

The drone food delivery service (DFDS) is a revolutionary technology owing to its ability to reduce delivery costs, alleviate traffic congestion, and offer a more environmentally friendly alternative compared to traditional delivery methods. While studies have been conducted to understand consumers’ intentions towards DFDS, very few of them considered internal factors such as personality traits. Considering the aforementioned factors, this research employs the belief-desire-intention (BDI) model and the big five personalities (BFP) traits to explore how personality traits (neuroticism, extraversion, agreeableness, conscientiousness, and openness) moderate the associations between the desire for DFDS and consumers’ intention to use DFDS (ITU).

Survey questionnaires were distributed online via Facebook and WhatsApp. A total of 359 responses were considered valid, and the study employed the partial least squares structural equation modelling approach to test the hypotheses.

The study revealed a positive impact of the desire for DFDS on ITU. Additionally, extraversion and agreeableness were found to moderate the effect of the desire for DFDS on ITU.

This study is the first in DFDS literature to employ the BDI model, showcasing its effective application in understanding the desire-to-intention relationship. Also, this is the first study that explores the moderating role of the BFP traits in the context of DFDS usage intention. The results provide insights for developing marketing strategies to encourage DFDS usage intention based on consumers' personality traits.