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The language of participative theatre can be considered immersive in the treatment of its dialectics where participants engage fully with their dichotomies and value systems through physical and psychological exploratory processes as they commit themselves to transformation.

The use of drama as an intervention for challenging recurring mental models of oppressive narratives is used extensively in experiential psychotherapy and as a socio-psychological integrative tool. This experiential methodology allows for an organic development and expression of themes and motifs by encouraging a participant to develop a deeper awareness of how he/she interprets their identity and that of the community in which they function.

This paper aims to review the implications of applying drama-based interventions as positive psychotherapeutic devices to facilitate self-reflection and active-constructive responding in enabling a rendering of positive patterns of thought and purposeful movement towards emotional and physical well-being.

Research on the principles of positive psychology suggests that positive emotions lead to therapeutic change. Nurturing positive emotions which are immanent in spirituality, creativity and optimistic perseverance through autonomy and self-regulation enable individual potential to come to meaningful fruition.

The paper conceptualizes psychodrama as a framing technique in enabling reflexive action in identity transformation and well-being.

This study aims to examine the factors influencing the intention of Muslim Millennial Generation in Indonesia to donate cash waqf digitally.

A quantitative approach was employed, surveying 284 Muslim Millennial Generation in Indonesia. The study integrated the Decomposed Theory of Planned Behavior (DTPB) and Technology Acceptance Model (TAM) to investigate the key factors driving the intention to contribute to cash waqf digitally. The researcher analyzed data using Partial Least Squares Structural Equation Modeling (PLS-SEM).

The findings of this study indicate that all hypotheses related to the variables are supported, including both direct and indirect correlations, except for perceived religiosity. This study confirms that the decision of millennials to donate cash waqf online is influenced by various factors, including their attitudes, the environment they are in, their ability to control their behavior, their perception of the ease and usefulness of technology and the availability of suitable facilities. Knowledge of technology is also a decisive component. Nevertheless, this study yielded intriguing findings that the perceived level of religious devotion does not impact the millennials’ willingness to make online cash waqf donations.

This study’s findings offer valuable insights for waqf institutions, providing a better understanding of Muslim millennials’ characteristics and preferences regarding spending, donations and waqf activities. This understanding can be instrumental in enhancing innovative digital platforms for cash waqf in the digital economy era.

This study uniquely explores the determinants of digital cash waqf donations among Muslim Millennial Generation in Indonesia. Contributions include integrating the DTPB and the TAM for a comprehensive analysis. Cross-disciplinary perspectives from behavioral economics and digital marketing enrich the research. Comparative studies and potential longitudinal analysis enhance depth, providing nuanced insights into the dynamic factors shaping digital donation behavior among Muslim millennials.

The Indian government’s launch of Digital India initiative is critical to achieving a sustainable future by leveraging digital capabilities to promote social justice, economic prosperity and environmental stewardship. There are a lot of factors affecting digital India’s transformation to achieve sustainable development goals. This study aims to identify, examine and develop an empirical model estimating the relationship among enablers affecting and enhancing digital India’s transformation toward sustainability.

Following a thorough review of the literature, 10 key enablers were identified and analyzed using the total interpretive structural model (TISM). This novel approach has been adopted to analyze the hierarchical linkage between identified Enablers. Further Matrice d’impacts croisés multiplication appliquée à un classement (MICMAC) analysis technique is used to evaluate the driving and dependence power among enablers.

Findings show that the government’s supportive policy is the strategic enabler with the highest driving power, positioned at the bottom of the model. The government must support digital empowerment initiatives to ensure all individuals have access to the information they require to make proper decisions regarding their lives. This study examines the literature to generalize the findings to focus on the motivator of digital India transformation to achieve sustainable development goals.

This study suggests that TISM and MICMAC-based hierarchical models help practitioners, managers and other stakeholders to focus more on strategic factors to enhance the performance aspects of digital transformation. Government, business and academic cooperation promotes a comprehensive approach to environmental sustainability by stimulating innovation and digital approach implementation.

In addition, it offers novel insights into the enablers, such as how the identified enablers interact with one another depending on the drive and dependency power to achieve the goals of digital India’s transformation to achieve sustainable development goals.

The construction industry plays a significant economic role but has struggled with improving labor productivity. Understanding the reasons behind this slow growth is valuable for the industry’s sustainability and improving wages. This study aims to explore the impact of capital intensity and the interaction effect of market regulations on construction labor productivity.

Using two-stage least squares panel data modeling, financial data from 55 Malaysian construction firms and economic data from 2009 to 2020 are analyzed.

The findings reveal that higher capital intensity associated with mechanization and innovation generally boosts labor productivity. However, certain market regulations, such as economic and capital freedom (ECF) and foreign debt rules (FDR), can counteract this positive effect. This suggests that poorly developed financial regulations may lead to inefficient capital allocation, reducing labor productivity in the long run.

The study highlights the importance of policymakers understanding these dynamics to develop effective strategies for enhancing labor productivity in the construction industry by considering the impact of capital intensity and the moderating effect of market regulation.

This study expanded the model of technology acceptance and investigated how the relationship between usefulness, ease of use, efficiency, personalization, safety and security and behavioural intention differ on Gen Z and silver tourists toward smart hotel. This study further applies multiple group analysis to examine whether there are substantial differences among these two groups of respondents.

Using an online survey, this study was undertaken with Gen Z and silver tourists in mainland China who had stayed in smart hotel over the past 12 months. A total of 474 valid responses were collected. Structural equation modelling and multigroup analysis were employed to test the proposed relationships.

This study revealed that personalization did not affect the behavioural intention among Gen Z tourists, meanwhile, there is no positive relationship between usefulness, efficiency and behavioural intention on silver group. Additionally, the findings revealed that there are no substantial differences among Gen Z (digital natives) and silver customers (digital immigrants) regarding smart hotel behavioural intentions.

This study offers strategic guidance for hotel managers to design and reposition smart hotel based on different customer sectors. Further, important implications for smart devices manufacturers are also provided to improve the functioning of hotel service robots.

This is the first study to compare the drivers and outcomes of behavioural intentions among different age groups of tourists toward smart hotels.

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.

Accurate solar photovoltaic models (SPVM) are critical for optimizing solar photovoltaic (PV) capacity to convert sunlight into electricity. The simulation and design of PV systems rely on estimating unknown constraints from solar photovoltaic (SPV) cells. Each parameter plays a crucial task in the output properties of an SPV under actual environmental conditions. Optimizing the unknown constraints of the SPVM is not an easy task due to the nonlinear characteristics of the PV cell. This study aims to develop a novel metaheuristic algorithm, enhanced dynamic inertia particle swarm optimization (EDIPSO) algorithm with velocity clamping, to establish all the seven and five constraints of the two-diode model (TDM) and one-diode model (ODM).

In complex parameter spaces, the conventional particle swarm optimization (PSO) approach typically leads to poor convergence because it fails to balance exploration and exploitation. The proposed approach is an EDIPSO with velocity clamping to minimize the possibility of overshooting possible solutions and improve stability. Velocity clamping is also used to prevent particle velocities from rising over specified limitations. Beginning the process with a large inertia weight to promote exploration and progressively decreasing it to improve exploitation, leading to a thorough analysis of the search space. The algorithm is implemented to investigate the accuracy of estimated constraint values of RTC-France (RTC-F) solar cell, Photo watt-PWP 201 SPV module (PWP 201 SPV), KC 200GT SPV module (KC 200 GT SPV) for ODM and TDM.

The proposed approach is used to extract the seven and five constraints of the TDM and ODM under standard test conditions for three different SPV modules. Thorough simulation and statistical analysis indicate that the EDIPSO with velocity clamping may outperform other cutting-edge optimization algorithms exclusively regarding accuracy, computational time and reliability.

An enhanced dynamic inertia PSO is suggested for determining the parameters of the TDM and ODM in SPV modules. This method specifically accounts for the recombination saturation current within the p–n junction’s depletion region, without overlooking or assuming away any parameters, thereby achieving greater accuracy. When comparing the estimated constraints of TDM and ODM for various SPVs, EDIPSO almost precisely aligns the data from the proposed model with the practical data. Thus, the proposed method for calculating the SPV model parameter may exhibit to be a feasible and efficient solution.

This paper aims to analyze the publication structure of academic research on organizational creativity between 1975 and 2022.

Bibliographic data on organizational creativity are extracted from the Scopus database and then analyzed through VOSviewer and R Statistical Software.

This paper analyzes 416 publications on organizational creativity from 1975 to 2022. Accordingly, the study identifies the most productive countries, universities, authors, journals and prolific organizational creativity publications. Also, the study uses VOSviewer and R Statistical Software Bibliometrix Package to visualize the mapping based on co-citation, bibliographic coupling and co-occurrence of keywords.

The study’s main contribution is that it provides an overview of the trends and trajectories of organizational creativity, which may help researchers and practitioners comprehend the trends and future research directions.