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Programming education is being rapidly transformed by generative AI tools and educators must determine how best to support students in this context. This study aims to explore the experiences of programming educators and students to inform future education provision.

Twelve students and six members of faculty in a small technology-focused university were interviewed. Thematic analysis of the interview data was combined with data collected from a survey of 44 students at the same university. Self-determination theory was applied as an analytical framework.

Three themes were identified – bespoke learning, affect and support – that significantly impact motivation and learning outcomes in programming education. It was also found that students are already making extensive use of large language models (LLMs). LLMs can significantly improve learner autonomy and sense of competence by improving the options for bespoke learning; fostering emotions that are conducive to engendering and maintaining motivation; and inhibiting the negative affective states that discourage learning. However, current LLMs cannot adequately provide or replace social support, which is still a key factor in learner motivation.

Integrating the use of LLMs into curricula can improve learning motivation and outcomes. It can also free educators from certain tasks, leaving them with more time and capacity to focus their attention on developing social learning opportunities to further enhance learner motivation.

To the best of the authors’ knowledge, this is the first attempt to explore the relationship between motivation and LLM use in programming education.

Augmented reality (AR) is an advanced version of the dynamic physical space that is perceived and received via visual, audio, digital and other sensory stimuli. The capabilities of virtual technologies change the field of university and education considerably. The necessity of using virtual technologies in the education field was revealed more in unforeseen disasters such as the COVID-19 pandemic. The adoption of a technology by its users is an important factor in the successful implementation of the technology. The present study evaluates several factors affecting the adoption of AR technology in the realm of tertiary education.

This study is applied in nature, and the necessary data were gathered through a survey questionnaire. The opinions of 621 students were investigated using a simple random sampling method. The multinomial logit test was used in this research.

It was found that individual and social factors such as age, education level, major and economic characteristics such as one’s income in a month, expenses of a person in a month, the level of access to high-speed internet and access to a laptop or smartphone are effective in AR technology adoption in the field of academic education.

The theoretical contribution of this study is to identify the key factors that influence the adoption of AR technology and develop a model specifically applicable to the educational field. The results of this research can be used by university managers and educational policymakers for the efficient and effective use of this technology.

This paper investigates the effectiveness of the Ambidextrous Scorecard (ASC) in facilitating the integration of organizational ambidexterity in four-star Puebla City hotels for managing exploitation and exploration activities. It proposes an integrated approach to ambidexterity and introduces the ASC as a tool explicitly targeting hotels’ challenges and opportunities.

The study analyzes survey data from 41 hotels (85.42% response rate). Our methodology involves a literature review, the Delphi technique for questionnaire validation, and data collection through Google Forms. Statistical tests confirm the reliability and validity of the approach for assessing the effective integration of exploitation and exploration activities.

The paper highlights how the ASC promotes an integrated approach to managing both activities. By incorporating exploitation activities (cost reduction, strategic alliances), and facilitating exploration activities (process innovation, new market attraction), the ASC empowers hotels to streamline operations, develop novel offerings, and achieve enhanced operational efficiency and innovation.

We acknowledge limitations due to its specific focus on the hotel industry in Puebla City, suggesting that the results may not be universally applicable. We recommended that further investigation be conducted into the application of the Ambidextrous Scorecard (ASC) across different sectors and regions to enhance understanding of organizational ambidexterity. Exploring the impact of integrating exploitation and exploration activities across corporate areas could offer valuable insights for implementing the ASC in diverse business settings.

The paper indicates that hotels can achieve ambidexterity by integrating exploitation and exploration activities using the Balanced Scorecard. This approach enhances competitiveness, allowing hotels to anticipate and respond to market trends quickly. It highlights the significance of considering ambidexterity across all organizational areas to ensure sustained adaptability and performance in dynamic environments.

This paper introduces the concept of integrated ambidexterity and the ASC as a novel tool for managing the balance between innovation and efficiency. The ASC transcends the hotel industry, potentially benefiting various service sectors by facilitating a more integrated approach to organizational performance.

Goal orientation shapes employees’ approach to and interpretation of workplace aspects such as supervisors’ behavior. However, research has not fully examined the effect of goal orientation as an antecedent of abusive supervision. Drawing from victim precipitation theory, this study aims to fill this research gap by investigating how employees’ goal orientation influences their perception of abusive supervision.

Two studies were conducted to test the hypotheses. In Study 1, 181 employees in 45 departments participated in the survey, and multilevel confirmatory factor analysis, two-level path model and polynomial regression were used. In Study 2, 108 working adults recruited from a professional online survey platform participated in a two-wave time-lagged survey. Confirmatory factor analysis, hierarchical linear regression and polynomial regression were used.

This study found that employees’ learning goal orientation was negatively related to their perception of abusive supervision. In contrast, performance-avoidance goal orientation was positively related to their perception of abusive supervision, whereas performance-approach goal orientation was unrelated to this perception. Moreover, employees’ perception of abusive supervision was greater when learning and performance-approach goal orientation alignment occurred at lower rather than higher levels, and when performance-avoidance and performance-approach goal orientation alignment occurred at higher rather than lower levels.

This research identified two novel victim traits as antecedents of abusive supervision – employees’ learning goal orientation and performance-avoidance goal orientation. Furthermore, adopting a multiple goal perspective, the authors examined the combined effects of goal orientation on employees’ perception of abusive supervision.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

This paper aims to investigate the effect of CEO social media celebrity status on credit ratings and to determine whether potential threats on the CEO celebrity status negatively moderate the above association.

The authors collected tweets for 874 CEOs from 513 unique S&P 1500 firms. A panel data analysis was conducted on a panel with 4,235 observations from 2009 to 2020. We then tested the hypothesis with the ordinal logit model.

The empirical findings confirmed that CEO social media celebrity status is positively associated with corporate credit rating outcomes. Our path analyses revealed that CEOs with higher social media celebrity status have less incentive to conduct risk-taking behaviors and thus benefit credit ratings. When the rating agencies perceive potential threats to CEO celebrity status, including CEO myopia and CEO overconfidence, the association between CEO social media celebrity status and credit rating is weakened.

This study provides an in-depth understanding of CEO social media perception on credit ratings for firms' managers and capital market participants. Findings can help managers and firms improve their strategies for leveraging social media to release credit constraints. The debt market participants could adopt the CEO social media celebrity status and its concerned threats to setting debt contracts with an adequate price.

This is likely to be the first study that examines the effect of CEO social media celebrity status on credit ratings. The findings of this study also reveal that social media certificated celebrity CEOs tend to be capable of enhancing firm revenue and have lower risk-taking incentives, unlike mass media certificated celebrity CEOs.

The regulatory design of Indian stock market provides us with the opportunity to disaggregate initial returns into two categories, i.e. voluntary premarket underpricing and post market mispricing. This study explores the impact of investor attention on the disaggregated short-run returns and long-run performance of initial public offerings (IPOs).

The study employs regression techniques on the sample of IPOs listed from 2005 to 2019. It measures investor attention with the help of the Google Search Volume Index (GSVI) extracted from Google Trends. Along with GSVI, the subscription rate is used as a proxy to measure investor attention.

The empirical results suggest a positive and significant relationship between initial returns and investor attention, thus validating the attention theory for Indian IPOs. Furthermore, when the returns are analysed for a more extended period using buy-and-hold abnormal returns (BHARs), it was found that price reversal holds in the long run.

This study highlights the importance of information diffusion in the market. It emphasizes the behavioural tendency of the investors in the pre-market, which reduces the market efficiency. Hence, along with fundamentals, investor attention also plays an essential role in deciding the returns for an IPO.

According to the best of the authors’ knowledge, this is one of the first studies that has attempted to explore the influence of investor attention and its interplay with underpricing and long-run performance for IPOs of Indian markets.

The dissemination of misleading and false information through media can jeopardize a company’s reputation, thus posing a threat to its stock and performance. Institutional investors are known to influence capital markets. Therefore, this paper investigates whether institutional investors engage in shaping the media sentiment stock nexus, stabilize company stocks and enhance performance.

We first investigate the effect of media sentiment on market reactions by using panel regression models. To examine the role of institutional investors, we design a quasi-experiment by exploiting the Financial Crisis of 2008 and go further by examining the heterogeneity across levels of institutional ownership. Due to risk-averse, investors may respond asymmetrically to pessimistic and positive sentiment. Accordingly, we split the sample into two sub-types, good news and bad news, based on keywords representing positive or negative content.

We find supportive evidence that institutional investors have impacts on how the markets react to media news, and the impacts are heterogeneous in the face of bad and good news. We conjecture that institutional investors act as a stabilizer of stock prices through media sentiment management.

This paper confirms the distinctive effects of institutional investors on capital markets, and uncovers the behind-the-scenes intervention and possible causal link running from institutional investors to media sentiment management. It contributes to the broad field of institutional investors' behavior, media news involvement in capital markets and market efficiency.

This paper aims to analyze the influences of context and methodological differences in how universities confront, report and manage carbon neutrality in selected Andean universities, contrasted with a university in the USA.

A sequential, mixed-methods design, using quantitative and qualitative approaches was applied. The data analysis is based on a systematic literature review with bibliometric analysis to identify how carbon neutrality in universities is understood and applied. Informed by the quantitative analysis, the qualitative phase compared the assessment methodologies, opportunities and obstacles in three Andean universities – EAFIT in Colombia, EPN in Ecuador and the UC in Chile – contrasted with MIT (USA) for comparative purposes beyond the region.

The bibliometric analysis points to the evolution of carbon management and carbon neutrality in universities and indicates how universities have applied methodologies and defined opportunities and obstacles. In this comparative experience, the contextual issues are brought to the fore. The conclusions highlight the importance of context in carbon neutrality assessment and argue against crude comparative metrics. While carbon assessment protocols provide data on which actions may be taken, the phase of carbon management development and the specifics of context – based on local institutional, geographical, climatic, cultural, socioeconomic and national policy conditions – are far more relevant for identifying actions.

This study only considered four universities, and the findings are not generalizable. The argument highlights the point that contextual factors generate important differences that may complicate simple comparisons based on the university's type or size. It also highlights the differences in the carbon calculation methodologies used by the institutions.

Results build on the recent publications that document the Latin American context. The article contributes to knowledge about Andean university commitments and actions relating to climate change and carbon neutrality. This knowledge can contribute to how universities in the region seek to apply different methodologies, set targets and the timing of actions and consider their contextual opportunities and obstacles.

Comparing university carbon footprints and carbon neutrality plans is an emerging topic, presenting methodological and institutional difficulties. This paper reveals some of these difficulties by comparing parameters, actions and implementation processes against contextual factors. While there is a drive for international and national comparisons and systematization of data on university carbon performance, significant methodological gaps still need to be resolved to account for these contextual factors.

This study aims to investigate the relationship between Airbnb and long-term residential rents, using Santa Monica, California, as a case study. In 2015, Santa Monica adopted the home sharing ordinance (HSO), a stringent regulation aimed at restricting short-term rentals (STR). This research examines the implications of this ordinance on the local housing market.

The synthetic control method (SCM) is applied to a panel data set comprising Airbnb listings and residential rents from multiple cities in Los Angeles County. This approach is used to estimate the causal effects of Santa Monica’s HSO on two outcomes: Airbnb listings and residential rents.

The empirical results show a 60% reduction in Airbnb listings in Santa Monica within two years of implementing the ordinance. Despite this significant decrease, the effect of the regulation on rents was not significant. Suggestive evidence indicates that the ordinance’s ineffectiveness in increasing the number of houses allocated to long-term tenants may have contributed to its negligible impact on rental rates.

To the best of the author’s knowledge, this research is the first to use the SCM for evaluating the impact of STR regulations. It offers crucial insights to policymakers on regulating platforms like Airbnb. The study reveals a scenario where a marked decrease in Airbnb activity did not lower residential rents, highlighting the need for context-specific evaluations in understanding the housing market’s dynamics. Additionally, these findings are valuable for investors considering the implications of regulatory changes in the STR sector.