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This paper aims to develop indicators of happiness in learning of the Thai open university (TOU)'s undergraduate students.

Sampling for the study was comprised of two groups. Group I comprised eight lecturers who are experts in their disciplines and six students who were purposively sampled. The focus group was used to validate the appropriateness of the indicators. In Group II, 332 students were engaged in a multistage sampling process. The responses were analyzed using descriptive statistics, coefficient correlation, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The indicators of happiness in learning of undergraduate students of TOU were classified in six categories. These included satisfaction with learning environment (five indicators), learning anxiety (five indicators), satisfaction with learning (five indicators), enthusiasm to learn (six indicators), self-satisfaction (six indicators) and readiness to learn (seven indicators). The six categories explained happiness in learning of undergraduate students of TOU at the 65% and fit empirical data.

The TOU can use the indicators for the assessment of happiness in learning of its students as well as guidelines for the improvement of its student learning environments.

There have been very few studies on indicators of happiness in learning of TOU students. Most were done at the basic education level. This study disclosed the six factors affecting happiness in learning of TOU students; therefore, it should inspire and draw attention of many in the field of higher education distance learning.

The study of sustainability within universities is recognized as essential for debates and research; in the long term, the “sustainable university” concepts can contribute to sustainability from a larger perspective. This study aims to propose a conceptual model for evaluating the students’ sustainability considering their interactions with the university and the environment. The proposed model is titled Sunshine model. It is applied to students of the La Salle University, Peru.

The model combines academic performance, happiness and the ecological footprint to quantify university students’ sustainability. A structured questionnaire survey was elaborated and applied to get the raw data that feeds the three methods. The students’ average grades evaluate academic performance. Happiness is quantified by the happiness index method, and the ecological footprint is measured by the demand for food, paper, electricity, transport and built-up areas. Results are evaluated under both approaches, overall group performance and clusters.

The proposed model avoids misleading interpretations of a single indicator or discussions on sustainability that lack a conceptual model, bringing robustness in assessing students’ sustainability in universities. To have a low ecological footprint, the student needs to need up to 1 planet for their lifestyle, be considered happy with at least 0.8 (of 1) for happiness index, and have good academic performance with at least a grade of 7 (of 10) in their course. Regarding the case study, La Salle students show a high academic grade degree of 7, a high level for happiness index of 0.8 and low performance for ecological footprint by demanding 1.8 Earth planets, resulting in an “environmentally distracted” overall classification for students with 2019 data. From a cluster approach, 81% of evaluated students (n = 603) have low performance for ecological footprint, whereas 31% have low performance for indicators of recreational activities of happiness. Changing lifestyles and making more recreational activities available play crucial roles in achieving higher sustainability for the La Salle students.

The happiness assessment questionnaire can be subject to criticism, as it was created as a specific method for this type of audience based on existing questionnaires in the literature. Although it can be seen as an important approach for diagnoses, the proposed model does not consider the cause–effect aspect. The decision-maker must consider the sociocultural aspects before implementing plan actions.

University managers can better understand why university students have high or low sustainability performance and provide more effective actions toward higher levels of students’ sustainability.

The proposed model, Sunshine model, overcomes the single-criteria existing tools that access the sustainability of universities. Rather than focusing on university infrastructure, the proposed model focuses on the students and their relationship with the university.

This chapter will examine the interplay among actors who took part in the process of consensus building towards a post-2015 education agenda via different channels of global governance, including both formal and informal channels.

Most of the forums and entities established as part of the global governance structure are composed of representatives from UN or UNESCO member states, civil society organizations (CSOs) and UN agencies. However, each of these categories has diverse constituent groups; representing these groups is not as straightforward a task as the governance structure seems to assume. Therefore, based on interviews and qualitative text analysis, this chapter will introduce major groups of actors and their major issues of concern, decision-making structure, mode of communication and relationship with other actors. Then, based on an understanding of the characteristics of the various channels and actors, it will present the structural issues that arose during the analysis of post-2015 discourse and the educational issues that emerged as the shared concerns of the ‘education community’. While most of the analysis to untangle the nature of discourse relies on qualitative analysis of texts and interviews, the end of this chapter will also demonstrate the trends of discourse in quantitative terms.

What was the post-2015 discourse for the so-called education community, which in itself has an ambiguous and virtual existence? The keywords post-2015 and post-EFA provide us with an opportunity to untangle how shared norms and codes of conduct were shaped at the global scale.

The Indian stock market can be tricky when there's trouble in the world, like wars or big conflicts. It's like trying to read a secret message. We want to figure out what makes investors nervous or happy, because their feelings often affect how they buy and sell stocks. We're building a tool to make prediction that uses both numbers and people's opinions.

Hybrid approach leverages Twitter sentiment, market data, volatility index (VIX) and momentum indicators like moving average convergence divergence (MACD) and relative strength index (RSI) to deliver accurate market insights for informed investment decisions during uncertainty.

Our study reveals that geopolitical tensions' impact on stock markets is fleeting and confined to the short term. Capitalizing on this insight, we built a ground-breaking predictive model with an impressive 98.47% accuracy in forecasting stock market values during such events.

To the best of the authors' knowledge, this model's originality lies in its focus on short-term impact, novel data fusion and high accuracy. Focus on short-term impact: Our model uniquely identifies and quantifies the fleeting effects of geopolitical tensions on market behavior, a previously under-researched area. Novel data fusion: Combining sentiment analysis with established market indicators like VIX and momentum offers a comprehensive and dynamic approach to predicting market movements during volatile periods. Advanced predictive accuracy: Achieving the prediction accuracy (98.47%) sets this model apart from existing solutions, making it a valuable tool for informed decision-making.

Although No Secrets suggests that adult protection practices should seek to prevent abuse, it can be argued that such practice predominately focuses on pursuing effective responses to abuse that has already happened, rather than preventing the onset of abuse. This research sought to contribute to the prevention of abuse, through the identification of ‘early indicators’. Early indicators were identified, and this knowledge has been applied to equip families and practitioners to report concerns at an early stage and seek protective responses.

The paper's purposes are to establish organizational learning theory as evolving from the theoretical and empirical study of organizations and to build grounded theory explaining organizational learning in schools.

Implementation of instructional technology as a process of organizational learning was explored at an elementary school. Findings from qualitative data revealed determinants of organization learning discussed as grounded theory, building on the relationship between social psychology and structural systemic aspects of organizational theory.

Five elements influenced organizational learning: priority of the learning in the organization, consistency and breadth of information distribution, unpredictability or uncertainty, the ease of learning new routines (how to) and the difficulty of learning new conceptual frameworks (why).

Assessing the type of change (routine or conceptual) and the adequacy of information distribution can predict the ease of organizational change. Identifying existing beliefs or procedures that impede new learning can explain lack of progression, and prioritizing the learning through both words and action can facilitate the process.

The paper develops organizational learning theory in schools as contextual indicators and conditions with theoretical roots in the structural technical and social cognitive study of organizations.

The coronavirus disease 2019 pandemic changed the lives of people around the world. In a post pandemic era, leaders have a role to enable the changes needed to make workplaces smart and happier. The aim of this study is to look at human resource management (HRM) from new perspectives: being smart and happy in the workplace. Some research questions are proposed: What do we know about smart human resources (smart HR)? What do we know about human resource analytics (HRA)? and how can future research on smart and happy HRM be oriented?

A bibliometric technique is used to identify the main topics studied in smart HR and HRA. A logical reasoning is applied to propose future research models.

For smart HR, the roadmap considers the approaches, practices and purposes. For HRA, the roadmap shows what are the perspectives HR processes, tools and its usefulness. Considering the context of Industry 5.0 and post pandemic era, a future research line for studying smart HRA for happy management is proposed.

This study has developed a proposed model to guide future research on the application of HRA to manage smart and happy workers.

To provide a coherent theoretical framework for interdisciplinary research on happiness, integrating the psychological, physiological/biological, and social/cultural levels, permitting integration of disparate approaches within and across disciplines.

Principles and findings of cybernetics are combined to shed light on difficulties encountered by research on happiness. Using a problem‐oriented approach, the reference system is defined as a psychological information‐processing and decision‐making system. This is an actor system in the social world needing orientation to act. Bossel's systems theory of orientation is applied to emotionality as a subsystem of the psychological system. Happiness, in terms of orientation theory, can be conceived as a meta‐orientor indicating wholeness, health, and the functioning of the overall‐system.

Emotionality and rationality are complementary decision‐making systems. Conditions are identified for developing the capability for emotional orientation and happiness in individuals. These conditions are strongly dependent on the social/cultural environment. Among them are the need for diversity in real‐life experience and for psychological acceptance of both oneself and the (sociocultural) environment. They can permit (relative) stability of happiness defined as an emotional state.

Further research can produce methods to improve happiness both by coaching individuals and by developing social conditions more conducive to happiness, e.g. in education. Happiness is a subjective indicator for physical, psychological, and social wellbeing taken together, which is the definition of health of WHO.

This sociocybernetic approach, combining systems concepts with orientation theory, can serve as an integrative theoretical framework for so far separate theoretical approaches.

The paper examines ways that Knowledge Management (KM) can demonstrate practical value for organizations. It begins by reviewing the claims made about KM, i.e. the benefits KM can provide to organizations. These claims are compared with traditional firm performance metrics to derive a criterion to measure the value of KM. Seven practical outcomes of KM are then presented as methods to persuade managers to invest in KM. These practical outcomes are then evaluated against the value criterion. The paper is based on empirical evidence from a five year longitudinal study.

This paper is based on a longitudinal change project for a large Australian Research Council (ARC) Linkage Project grant in the period 2008-2013. The Project was a transformational change program which aimed to help make the partner organisation a learning organisation. The partner organisation was a large Australian Government Department, which faced the threat of knowledge loss caused by its ageing workforce. The sample was 118 respondents, mainly engineering and technical workers. A total of 150 respondents were invited to participate in the study which involved an annual survey and attendance at regular training workshops and related activities, with a participation rate of 79 per cent.

This paper provides a checklist from which to evaluate KM in terms of financial and non-financial measures and seven practical outcomes from which to identify the organisational problem which may be addressed by KM. Lead and lag indicators – what needs to be done and what will result – are also provided. Managers may use this framework to identify the value proposition in any KM investment.

The research is based on a single case study in a public sector organization. While the longitudinal nature of the study and the rich data collected offsets this issue, it also presents good opportunities for researchers and practitioners to test the ideas presented in this paper in other industry contexts. The seven practical outcomes also vary in the maturity of the empirical evidence supporting KM ' s impact. Strategic alignment, value management, and psychological contract, in particular, are still under-developed and could be areas for specific further research testing the ideas presented here.

This paper argues that investment decisions regarding KM may benefit from focusing on significant and on-going organisational problems, which will connect KM with firm performance and demonstrate financial and non-financial impact. The seven practical outcomes were evaluated against measurement criteria and against KM ' s claims. Overall, common themes were time and cost, as well as capability growth and performance improvements. Financial impact was mainly found in cost savings. Non-financial impact was found across the seven practical outcomes. It provides management with a checklist to make investment decisions regarding KM.

The decision whether to invest in KM begins with methods used to evaluate any organisational project. Managers must determine first whether necessary funds are available; and then whether the project is worthwhile. The standard method for evaluating a project ' s worth is return on investment (ROI). However, calculating ROI for KM investment is problematic. Unless KM can be proven to directly improve performance in financial terms, managers may struggle to see its ROI. The paper begins by reviewing the claims made about KM, i.e. the benefits KM can provide to organizations. These claims are compared with traditional firm performance metrics to derive a criterion to measure the value of KM.