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Self-regulation is the level of learning where the learner becomes an active agent in their learning process in terms of activity and aspects of motivation and metacognition. The current paper mostly deals with the metacognitive aspect. The purpose of this study is to gain insight into self-regulation of learning in the context of modern technology in higher education. This study also aims to highlight the direction, tendencies and trends toward which self-regulation of learning is moving in relation to modern technologies.

The review study was compiled via searches in three databases: Scopus, Web of Science and ERIC. A filter was used to search for empirical studies solely in English, published over the past decade on the topics of self-regulation of learning and technology in higher education.

The findings clearly show a correlation between self-regulation of learning and modern technology, especially after a significant event such as the Covid-19 pandemic. However, in the wake of this change, the field of education has seen the emergence of methods and new platforms that can provide support for the development of self-regulated learning strategies.

The originality of the study lies in the fact that it focuses on the link between self-regulation of learning and modern technologies in higher education, including some predictions of the future direction of self-regulation of learning in this context.

This study examines the impact of China’s mixed-ownership reform on the innovation of non-state-owned acquirers, with a particular focus on the impact on firms with high financing constraints, low-quality accounting information or less tangible assets.

We use a proprietary dataset of firms listed on the Shanghai and Shenzhen Stock Exchanges to investigate the impact of mixed ownership reform on non-state-owned enterprise (non-SOE) innovation. We employ regression analysis to examine the association between mixed ownership reform and firm innovation.

The study finds that non-state-owned firms can improve innovation by acquiring equity in state-owned enterprises (SOEs) under the reform. Eased financing constraints, lowered financing costs, better access to tax incentives or government subsidies, lowered agency costs, better accounting information quality and more credit loans are underlying the impact. Additionally, cross-ownership connections amongst non-SOE executives and government intervention strengthen the impact, whilst regional marketisation weakens it.

This study adds to the literature on the association between mixed ownership reform and firm innovation by focussing on the conditions under which this impact is stronger. It also sheds light on the policy implications for SOE reforms in emerging economies.

Research about tourism impacts is abundant. However, existing studies often investigate tourism impacts from residents’ and tourists’ perspectives. The study targeting students is absent. The students’ perception and evaluation of tourism impact must be investigated independently to have more insights into improving the current education curriculum, which covertly addresses the impacts. Therefore, this study aims to examine university students’ perception of tourism impacts as young tourists to provide implications for better teaching of such content in the future.

Vietnam was chosen as the context, and a mixed method was employed. First, free elicitation with 118 university students was carried out to identify the students’ perceived impacts (109 items, four categories). Second, structured surveys using the previously generated content with 243 and 224 university students were implemented to identify the latent structures of the impacts (3-4 factors per impact category).

Tourism impacts can be dually perceived. In other words, they can come in positive or negative forms or are directed toward the destinations or the residents. However, being positive or negative, or affecting the place or the people, tourism impacts have some general and universal elements concerning the economic, sociocultural and environmental ones. In addition, they have some specific and contextual aspects, such as cross-border marriages, child labor and economic autonomy loss.

Tourism impacts seen from the perspective of university students are relatable and valuable for tourism education. Educators in Vietnam should consider revising the current curriculum to address all the tourism impacts overtly.

The proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM), meta-heuristic algorithms, particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).

In addition, among the developed algorithms, the most effective one is chosen to determine probable sell and buy signals. Moreover, the authors have proposed comparative results to validate the designed model in this study with the same basic models of three articles in the past. Hence, PSO is used as a classification method to search the solution space absolutelyand with the high speed of running. In terms of the second model, SVM and ICA are examined by the time. Where the ICA is an improver for the SVM parameters. Finally, in the third model, SVM and GA are studied, where GA acts as optimizer and feature selection agent.

Results have been indicated that, the prediction accuracy of all new models are high for only six days, however, with respect to the confusion matrixes results, it is understood that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the authors to analyze the data the long length of time between the years 2013–2021, makes the input data analysis challenging. They must be changed with respect to the conditions.

In this study, two methods have been developed in a candlestick model, they are raw based and signal-based approaches which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

Being involved at work advances accountants' contribution to organizational success. However, scholars are not consistent in discussing involvement's implications on work–life balance (WLB). The article aims to address this issue, investigating involvement's effects on the accountants' ability to manage the work–life interplay.

Secondary data on a sample of 538 accountants were collected from the sixth European Working Condition Survey (EWCS). A serial mediation analysis was designed to obtain evidence of involvement's implications on WLB through the mediating role of work engagement and work satisfaction.

Involvement negatively affected the accountants' ability to deal with the work–life interplay. Engagement and satisfaction with work mediated this relationship. More specifically, involved accountants who were engaged and satisfied with their work conditions were less likely to report struggles between work and life.

Involvement implies an intensification of work, heralding an overlapping between work and life. Nonetheless, accountants who are engaged and satisfied with work are less touched by involvement's drawback on WLB. A precautionary approach should be taken to avoid that involvement results in workaholism, thus undermining individual well-being.

The article originally discusses involvement's implications on WLB across accountants. Being involved at work impairs the individual ability to achieve a balance between work and life, endangering well-being at work. Whilst the findings cannot be generalized beyond the accounting profession, they deliver some intriguing insights that highlight avenues for further developments.

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.

Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).

Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.

Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.

The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.

By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.

Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.

This article aims to map the expectations of manufacturing companies towards suppliers in terms of implementing improvement activities. The article poses two research questions: RQ1: What kind of improvement of activities do the surveyed producers expect from their suppliers? RQ2: Do factors such as size, capital or implemented systems influence different assessments of the analyzed requirements toward suppliers?

The Computer Assisted Telephone Interview (CATI) technique was used to collect data. The sample consists of 150 producers (employing over 50 people) who were suppliers for enterprises from the automotive, electromechanical and chemical sectors operating in the Polish business-to-business (B2B) market. We analyzed 11 improvement activities, while their correlation structure was examined by exploratory factor analysis.

We have identified three latent factors – risk reduction, product innovation and increasing efficiency – which summarize the main expectations of manufacturing companies towards suppliers. Expectations for these factors are independent of the implemented management system, although the analysis showed higher expectations for product innovation in organizations with the implementation of Kaizen.

The article fills the research gap in the literature. The research results presented in the literature so far have focused on the expectations of enterprises towards suppliers in terms of meeting the criteria for their initial and periodic assessment. The research gap in the article is the result of empirical research presenting the expectations of manufacturers towards suppliers in terms of improving their processes. Based on the findings of the presented study, development trends and implications for managers responsible for purchasing processes and relationships with suppliers can be determined.

The purpose of the research is to analyze the factors that determine the intention of small- and medium-sized enterprises (SMEs) to adopt the Metaverse. For this purpose, the analysis of the effort expectancy and performance expectancy of the constructs in relation to business satisfaction is proposed.

The analysis was performed on a sample of 182 Spanish SMEs in the technology sector, using a PLS-SEM approach for development. For the confirmation of the model and its results, an analysis with PLSpredict was performed, obtaining a high predictive capacity of the model.

After the analysis of the model proposed in this research, it is recorded that the valuation of the effort to be made and the possible performance expected by the companies does not directly determine the intention to use immersive technology in their strategic behavior. Instead, the results obtained indicate that business satisfaction will involve obtaining information, reducing uncertainty and analyzing the competition necessary for approaching this new virtual environment.

The study represents one of the first approaches to the intention of business behavior in the development of performance strategies within Metaverse systems. So far, the literature has approached immersive systems from perspectives close to consumer behavior, but the study of strategic business behavior has been left aside due to the high degree of experimentalism of this field of study and its scientific approach. The present study aims to contribute to the knowledge of the factors involved in the intention to use the Metaverse by SMEs interested in this field.

While most marketing research on organic products refers to the premium price levels of organic products, little research exists on consumers’ behavioural responses to price promotions or discounts of organic products. The present study aims to fill this research gap.

To develop alternative hypotheses about consumers’ behavioural responses to price promotions of organic fast-moving consumer good (FMCG) products, the authors used the researcher-introspection method in a pre-study. To test the hypotheses developed based on the pre-study, the authors conducted a field experiment on online advertising of an FMCG sold in drugstores. In the field experiment, the authors exposed consumers to an online ad featuring either a price promotion (−20%) or the regular price of the product. The ads also varied in terms of whether they contained explicit organic claims or not, and whether they included implicit organic cues or not.

The price promotion increased the clickthrough rate of the ad both when combined with an explicit organic claim and when combined with the implicit cue of green product pack. The results suggest that consumers do not have significant suspicions about price promotions of organic products, but rather presume that the price promotion of an organic FMCG product is a periodical promotional action, similar to the price promotions for conventional, non-organic products. Also, consumers seem to assume that the regular prices of organic FMCG products are so high that the retailer/manufacturer can well afford periodic price discounts.

The present research shifts the focus of organic marketing research from the premium price levels to the effectiveness of price promotions and discounts. Further, the present results contrast with certain earlier studies that have questioned the effectiveness of price promotions for organic products.

The results have different implications for marketing managers of brands not yet providing organic product versions in the market, of brands producing non-organic products, which cannot easily be rendered organic, and of brands offering organic products in the market.

This is, to the best of the authors’ knowledge, the first empirical study and field experiment on price promotions of organic products, including explicit organic claims.

This paper delves into cross-border E-business, unraveling its intricate dynamics and forecasting its future trajectory.

This paper projects the prospective market size of cross-border E-business in China for the year 2023 using the GM (1,1) gray forecasting model. Furthermore, to enhance the analysis, the paper attempts to simulate and forecast the size of China’s cross-border E-business sector using the GM (1,3) gray model. This extended model considers not only the historical trends of cross-border E-business but also the growth patterns of GDP and the digital economy.

The forecast indicates a market size of 18,760 to 18,934 billion RMB in 2023, aligning with the consistent growth observed in previous years. This suggests a sustained positive trajectory for cross-border E-business.

Cross-border e-commerce critically shapes China’s global integration and traditional industry development. The research in this paper provides insights beyond statistical trends, contributing to a nuanced understanding of the pivotal role played by cross-border e-commerce in shaping China’s economic future.