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The main objective of the present investigation is to develop a novel efficient stochastic model for availability optimization of reverse osmosis machine system (ROMS) for water purification under the concepts of exponentially distributed decision variables and various redundancy strategies at the component level.

ROMS is a complex framework configured in a series structure using six subsystems. Initially, a state transition diagram is developed and Chapman–Kolmogorov differential-difference equations are derived using Markov birth death process. The steady-state availability of the ROMS is derived for a particular case. The impact of variation in failure and repair rates measured on availability. Furthermore, an effort is made to predict the optimal availability of the ROMS system using the metaheuristic algorithms, namely, dragonfly algorithm (DA), grasshopper optimization algorithm (GOA) and whale optimization algorithm (WOA).

It is observed that the ROMS system predicts optimal availability of 0.999926 after five iterations with a population size of 300 by the WOA. The findings of this study are significant for reliability engineers as well as for maintenance engineers to ensure the availability of ROMS for water purification.

In the present investigation, a novel stochastic model is developed for ROMS, and metaheuristics algorithms are applied to predict the optimal availability.

Employee engagement has been identified as a prevalent issue affecting higher education institutions, particularly since the emergence of COVID-19. Therefore, this study aims to investigate the factors contributing to employee engagement in Islamic higher education institutions in the context of Malaysia.

A quantitative research design was used for this study, and a survey questionnaire was used to collect data from 340 staff members of Islamic higher education institutions in Malaysia. The proposed hypotheses underwent testing through the statistical technique of structural equation modelling, using statistical package for the social sciences (SPSS) and analysis of moment structures (AMOS).

The results indicate that training and development, trustworthiness, workplace spirituality, reward and recognition, management support and job autonomy significantly contribute to employee engagement in Islamic higher education institutions in Malaysia.

This study is limited to the staff of Islamic higher education institutions in Malaysia. A comparative cross-cultural research approach may be preferred for a more comprehensive understanding. Therefore, future researchers are encouraged to consider this limitation when investigating the factors contributing to employee engagement in Islamic higher education institutions, particularly to confirm the cogency of our findings.

The findings provide valuable insights into the workforce factors that play key roles in developing a highly engaged workforce in Islamic higher education institutions. This study contributes to the enrichment of the literature in this specific area of study.

Coparenting is a complex construct showing the quality of parental beliefs, motives, and actions related to cooperation in the child-rearing process. Its important role has been proven in child development and in shaping parents’ quality of life outcomes or marital satisfaction. This chapter presents the results of a study aimed at exploring the significance of selected parenting and child-related variables for the various components of coparenting in families with a child with disabilities. Material was collected in a group of 118 parenting couples using The Coparenting Relationship Scale. It was found that fathers scored higher in Coparenting Undermining and Endorse Partner Parenting. The variable of education was significant: parents with higher education showed the highest parental compatibility, and mothers also showed relatively highest satisfaction with the division of responsibilities. Parental age, age, and gender of the child with a disability were not significant. Difficult behaviors in the child correlated negatively with favorable coparenting components in parents and positively with unfavorable ones. Functional status was negatively associated with Coparenting Agreement and Endorse Partner in fathers. The complementarity of parental roles must be taken into account in the process of specialized support from psychologists, school counselors, social workers, etc.

Purpose: This chapter aims to unveil the challenges of adopting and using banking chatbots in India and identify the challenges of Chat Generative Pre-trained Transformer (ChatGPT) for future banking.

Need for the study: Unveiling the challenges of chatbots and ChatGPT in the banking industry in India is crucial to understand the limitations and areas of improvement to enhance customer experience, ensure data security, and maintain regulatory compliance.

Methodology: The researchers conducted a narrative review systematically summarising and analysing existing literature on chatbots and ChatGPT, providing a comprehensive overview of the challenges faced in the industry.

Findings: The authors identify perceived risk, platform quality, connectivity and infrastructure, data privacy and security, user education and acceptance, existing legacy systems, and regulatory guidelines as the challenges of adopting chatbots. Additionally, the findings reveal that the challenges posed by ChatGPT in future banking include the potential reduction of traditional banking jobs, linguistic diversity, data privacy and security, ethical considerations and bias mitigation, explainability and accountability, integration with existing banking systems, and user trust and acceptance. However, implementing these new technologies also presents opportunities for individuals with unique human skills, such as critical thinking, empathy, and creativity, which are difficult to replace with technology.

Practical implications: By minimising the challenges of ChatGPT and chatbots, the banking industry could achieve improved customer service, cost efficiency, automation of routine tasks, and 24/7 availability, leading to enhanced customer satisfaction and operational efficiency in the banking industry. Additionally, these artificial intelligence (AI) tools enable data-driven insights, personalised experiences, scalability, and efficient handling of large customer volumes, contributing to better decision-making and enhanced customer engagement.