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The study integrated understanding by design-Internet of Things (UbD-IoT) education with design thinking and computational thinking to plan and design an IoT course. Cross-domain application examples were employed to train students in problem-understanding, deep thinking and logical design for IoT applications.

In this study, the UbD model was integrated with design thinking and computational thinking in the planning and design of an IoT course. The examples of cross-domain applications were used to train students to understand a problem by engaging themselves in deep thinking and helping them think and design logically for an IoT application.

The UbD-IoT learning design greatly decreased students' overall cognitive load. UbD-IoT learning has a significant impact on the performance of computational thinking in problem-solving and problem-understanding. The impact of UbD-IoT learning on logical thinking and program learning cognition in students needs to be verified.

The results of this study have shown that the UbD model is effective in reducing the cognitive load of a learning course and also strengthens T-competencies in the lateral skills of computational thinking, critical problem-solving, logical thinking and creative thinking.

This study aims to reflect on the future of work dimensions through the new concept of inclusive organizational behaviour (IOB) and its practices.

This work is a reflective concept development paper that focuses on new dimensions of organizational behaviour (OB) exploring IOB practices in the new workplace which can broaden the concept of OB that fits into the future of work.

The IOB practices will adapt and help in adapting to the new work dynamics that can create more humane and stimulating workplaces, thereby benefiting society at large. Individual positive psychological traits, team dynamics and a fusion of digital corporate culture with a human-centric approach and sustainability are highlighted in the redefined IOB, expanding the concept of OB from the three levels of analysis (individual, group and the entire organization’s behaviour) in the new normal post-COVID situation.

Limited research studies are being conducted to investigate the future of work dynamics in the new standard post-COVID environment, which is dominated by digitization. The lack of literature and the changing situations that impact OB are the limitations.

Corporate houses, policymakers and leaders who understand the workplace dynamics in the post-COVID scenario can effectively leverage the insights from this work and may chalk out a road map for future work through IOB practices.

This research extends knowledge pertaining to IOB practices and the changing dynamics that need to be followed in the future OB practices.

The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area.

In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents.

As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used.

Based on the conclusion presented in this paper, there are several potential implications for research, practice and society.

This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations.

The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole.

It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.

The purpose of this study was to develop and validate a scale to assess the influence of Higher Educational Facilities for the growth of education in higher education institutions.

The first step in the process of scale development is to generate an item pool containing as many items as possible which captures the construct of interest. A total of 111 items were constructed for the initial try-out of the scale measuring the construct of higher educational facilities. This rating scale was based on the Likert-type was designed, where each item had to be rated on a five-point scale. The scale consisted of a few items involving the dimensions of infrastructure, quality assessment and quality assurance regard to the vision actualization.

Higher Educational Facilities Scale (HEFS) was developed by the investigator and designed in the format of a 5-point rating scale of the Likert type. There are different phases identified for the scale construction. In the first phase, items are created and the content’s validity is determined. The scale is constructed in the second phase. Pre-testing the questions, administering the survey, reducing the number of items and determining how many factors the scale captures are all steps in the scale construction process. The number of dimensions, reliability and validity are all verified in the third phase, scale evaluation. In developing the scale, the content and face validity was ascertained. The reliability of the scale and its three subscales were established. This scale has potential value for policymakers to assess the perception held by the religious faculty members working in higher education institutions.

The research is part of the doctoral thesis by Dr Deepa Thomas under the supervision of Dr Fr. Joseph C. C. and the co-supervision of Dr Kennedy Andrew Thomas. The purpose of the scale is to assess the higher educational facilities of in institutions of higher Education. Quality, excellence and service are the vision and purpose of higher education institutions to provide ample opportunities and good facilities for their beneficiaries, thus creating tremendous changes in the Indian education scenario.

Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.

Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media.

For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance.

The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts.

Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.

The paper intends to show why farms as we know them today may soon be a thing of the past and that organisational behaviour research has an important contribution to make in assisting the upcoming transformation.

Two strains of literature are reviewed and then synthesised: the literature on robots replacing humans in agricultural production and the literature on vertical integration that shifts decisions to agribusiness. Then the potential contribution of organisational behaviour research is outlined.

It is shown how the farm is likely to lose both roles for which their geographic entity is important: making decisions and carrying out production. This requires contributions from organisational behaviour research in the realms of decision designs and social systems.

It can be anticipated that the most profitable strategy for farmland owners in the future will be collaboration with contractors. Farms as organisations, are increasingly losing their importance. This not only has grave social implications for farmworkers and landowners but also for scholars in organisational behaviour research.

The paper challenges an organisational unit that is so familiar to us that it is rarely questioned.

The purpose of this study is to examine the relationships between chief executive officers (CEOs) with military service and firm dividend and cash holding decisions.

The authors use a sample of Standard and Poor's (S&P) 1500 firms in the USA over a sample period from 1999 to 2017 and a panel data approach, as well as instrumental variable (IV)analysis. The models control for firm characteristics as well as industry and year-fixed effects.

The results show CEOs with military service are associated with higher total payout and less cash. Higher dividends appear to drive the total payout result. When cash holdings are split into pure cash and short-term investments, the reduction in cash holdings is driven by a reduction in pure cash. The findings are more pronounced for powerful CEOs and CEOs with low labor mobility. Military CEOs are also associated with less risk, measured by stock return volatility and return on assets (ROA) volatility.

Overall, the results are consistent with military CEOs implementing conservative policies that reduce firm risk, curtailing the demand for precautionary cash and reducing the necessity to forego dividend payouts.

This study aims to explore the association between chief executive officer (CEO) tenure and the quality of information disclosed through integrated reporting quality (IRQ), which combines financial and non-financial data. The authors also investigate how formal (e.g. board independence and gender diversity) and informal (e.g. corporate culture) governance mechanisms influence this association. By analysing these factors, the authors expect to provide valuable insights on the impact of CEO tenure and governance structures on the comprehensive nature of integrated reporting.

This study uses a sample of the top 200 Australian Securities Exchange (ASX)-listed companies from 2015 to 2019. IRQ is measured through levels of compliance with the integrated reporting (IR) framework proposed by the International Integrated Reporting Council (IIRC). The hypotheses are tested using multiple regression analyses.

The authors find that CEO tenure is negatively associated with IRQ. Furthermore, CEO tenure has a more positive influence on IRQ in the early CEO tenure years than later ones. The authors' study finds that the association between CEO tenure and IRQ is insignificant when firms have a high level of monitoring, as measured by board independence and gender diversity. The authors also document that competitive corporate culture moderates the negative association between CEO tenure and IRQ.

The authors' study highlights the significant impact of internal formal and informal governance mechanisms on disclosure practices in Australia's voluntary IR environment. By shedding light on these factors, the authors' research enhances understanding of Australian companies' IR practices and offers valuable insights for scholars, policymakers and practitioners in the field.

The authors investigate the adoption of nomination committees in Australia and identify the managerial power perspective as one explanation for firms not establishing nomination committees. A positive outcome of establishing a nomination committee from the perspective of board diversity is also examined.

The authors adopt an archival approach by collecting data for firms listed on the Australian Securities Exchange (ASX) during the period 2010 to 2018. The authors establish the prevalence of nomination committees for small medium and large Australian firms. Regression analyses are used to determine whether the power of the chief executive officer (CEO) influences the adoption of a nomination committee. The association between having nomination committee and board diversity is also analyzed using regression analyses.

Less than half of firms adopt a nomination committee. Larger firms are more likely to adopt a nomination committee than medium and smaller sized firms. Firms with less powerful CEOs are more likely to adopt a nomination committee. Adoption of a nomination committee is also associated with greater board tenure dispersion and board gender diversity in medium and smaller sized firms.

Evidence on nomination committees provides original research that extends previous research focusing on the audit, risk and remuneration committees and samples restricted to large firms. The nomination committee has an important role to play in the appointment of directors yet limited evidence exists of the adoption rate, explanation for non-adoption and benefits of adoption. The authors add to this evidence.