Innovation in water management is believed to hold the key to sustainable use and effective administration of water resources. Most of the existing literature generally discusses technological advancements and managerial reforms that improve productivity; the role of business model innovation (BMI) is less explored in the literature. Addressing this gap, our study investigates the impact of BMI, as measured by the net asset turnover ratio, on productivity in Iran's water and wastewater sector. Iran presents a unique case due to its water scarcity, public management structure, and persistent operational challenges, making it an instructive context for examining how internal innovations can drive performance. We analyze panel data from 33 provincial water and wastewater companies collected between 2016 and 2022, using a Cobb–Douglas production function to estimate the effects of BMI, labor, and capital on output. In addition, based on the estimated production function, the Divisia index is used to measure total factor productivity. Our results show that net asset turnover, alongside labor and capital, has a significant positive effect on output. These findings highlight the importance of BMI for enhancing efficiency in asset‐intensive and resource‐constrained public utilities, offering valuable insights for researchers and managers in similar contexts.
The article discusses the process of automation of the quality management system in organizations in the context of digital transformation. An algorithm has been developed for the implementation of a digital quality management system, the architecture of which is based on the implementation of the principle of individualization. The proposed system allows you to flexibly respond to changes in business processes and improve the efficiency and quality of management decision-making. The versatility of the approaches makes it possible to adapt the solution to the needs of both internal and external customers. Special attention is paid to the development of individualization of solutions in quality management systems and their impact on the efficiency of business processes. Within the framework of the study, the current problems of the organization of Power Machines JSC in the quality management system are analyzed, the signs of the principle of individualization are identified and formulated, which are critically important for creating a digital quality management system with maximum usefulness and effectiveness. The use of these features plays a key role in achieving the goals of digitalization of the quality management system, ensuring its adaptation to changing conditions and requirements, contributing to a deeper and more beneficial effect of its implementation. An important conclusion of the study was the determination that the most difficult part of creating a digital quality management system is not only its visualization, but also the precise definition of the features of the principle of individualization, which must be taken into account at all stages of the development and operation of the system. This is necessary to ensure flexibility and increase the system's resilience to changes in the external and internal environment. The proposed algorithm for creating a digital quality management system using the principle of individualization has been tested in practice. In addition, the distinctive features of this principle are identified, and approaches to scaling the proven approach to enterprises of the machine-building complex are proposed. The study also shows that a digital quality system based on the principle of individualization serves as the foundation for building an intelligent decision support system that includes advanced analytics, forecasting and artificial intelligence to make recommendations for action. The results obtained confirm the high efficiency of the proposed approach to quality management in the context of digital transformation. / В статье рассматривается процесс автоматизации системы управления качеством в организациях в контексте цифровой трансформации. Разработан алгоритм реализации цифровой системы управления качеством, архитектура которой основана на внедрении принципа индивидуализации. Предложенная система позволяет гибко реагировать на изменения в бизнес-процессах и повышать оперативность и качество принятия управленческих решений. Универсальность подходов позволяет адаптировать решение под потребности как внутренних, так и внешних клиентов. Особое внимание уделено развитию индивидуализации решений в системах управления качеством и их влиянию на эффективность бизнес-процессов. В рамках исследования проанализированы текущие проблемы организации АО «Силовые машины» в системе управления качеством, определены и сформулированы признаки принципа индивидуализации, критически важные для создания цифровой системы управления качеством с максимальной полезностью и результативностью. Применение этих признаков играет ключевую роль в достижении целей цифровизации системы управления качеством, обеспечивая ее адаптацию к изменяющимся условиям и требованиям, внося более глубокий и полезный эффект от ее внедрения. Важным выводом исследования стало определение того, что наиболее сложной частью создания цифровой системы управления качеством является не только ее визуализация, но и точное определение признаков принципа индивидуализации, которые должны учитываться на всех этапах разработки и эксплуатации системы. Это необходимо для обеспечения гибкости и повышения устойчивости системы к изменениям во внешней и внутренней среде. Предложенный алгоритм создания цифровой системы управления качеством с применением принципа индивидуализации был апробирован на практике. Кроме того, определены отличительные особенности данного принципа, а также предложены способы масштабирования апробированного подхода на предприятия машиностроительного комплекса. В результате исследования также показано, что цифровая система качества на основе принципа индивидуализации служит фундаментом для построения интеллектуальной системы поддержки принятия решений, включающей продвинутую аналитику, прогнозирование и искусственный интеллект для выработки рекомендаций к действию. Полученные результаты подтверждают высокую эффективность предложенного подхода к управлению качеством в контексте цифровой трансформации.
Since 2011, the term 'Industry 4.0' (I4.0) has gained significance in industry. After a decade of digital transformation, the European Commission is now advancing towards Industry 5.0 (I5.0). The focus is on using technology to support people, enhance ecological sustainability, and make industry more resilient. This paper examines the transition from I4.0 to I5.0, with a particular focus on the learning factory Smart Production Lab as a model for future-oriented manufacturing companies. The study involves a systematic literature review to identify key technologies and concepts of I4.0 and analyse their evolution in the context of I5.0. A comparative analysis forms the basis for a matrix that facilitates a clear comparison and guides future developments of the Lab. This research identifies the technologies underpinning the goals of I5.0 and their implications for practical applications in manufacturing. It also provides actionable recommendations for companies.
Rapid developments in nanotechnology have led to considerable progress in fabricating electrospun and nanofibrous membranes. Electrospun and nanofiber membranes enjoy numerous advantages, including highly porous and 3D structures, high surface-to-volume ratio, and interconnected pores. Having considered these advantages, they can be used promisingly for a wide range of applications, such as waste/wastewater treatment, medical and drug delivery purposes, air filtration, and energy storage. This chapter provides a deep overview of the fundamentals of electrospinning technology. Various aspects and dominant operating parameters have been investigated comprehensively. A brief overview of the applications has also been provided.
Combinatorial choice models are based on the implicit assumption that decision-makers consider all possible combinations that can be made by the options in a given set.Therefore, these models assumed that the chosen combination is the most preferable combination.However, decision-makers may not consider all possible combinations due to the limited attention.Thus, the chosen combination is not necessarily the best.This paper presents a model that can explain such choice behaviors.After presenting the model, we investigate its revealed preference implications and explain how one can make inferences about individuals' preferences considering their choices in the new context.Finally, for the model to be testable, we present its characterizing axiom and show that it is equivalent to the model.
