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Investments in Industry 4.0 are making a significant impact on various sectors by integrating advanced digital technologies. The chances of financial losses for organisations' investments due to new technologies are high, and there is a low possibility of recovering the investments. Reduced spending on long-term costs by organisations due to low investments and consumer demand for durable goods has resulted in sluggish global trade in advanced and emerging markets. Challenges have arisen for companies in securing loans for investments due to past economic slowdowns, resulting in increased corporate borrowing expenses. The literature acknowledges Supply Chain Finance (SCF) as a vital approach to optimising efficiency. Industry leaders are turning to SCF as high costs persist during the transformation process for manufacturers. SCF can unlock substantial working capital by improving cash flow, which can be used to back essential business initiatives. This evolving environment presents opportunities and requires a deeper investigation of possibilities and challenges in advancing SCF to support Industry 4.0 efforts. Given this, the Special Issue released in the International Journal of Production Research pushes forward this crucial research focus. Nine articles accepted in this Special Issue used different methodologies, theories, and contexts to address research needs and offer valuable insights on supply chain finance and industry 4.0 investment challenges. This Editorial summarises these studies, emphasising possibilities for future research pathways. [ABSTRACT FROM AUTHOR]

Consumers' dramatic demand has a pernicious effect throughout the supply chain. It exacerbates inventory distortion because of significant revenue loss caused by stock-level issues. Despite the availability of several forecasting techniques, large organisations, manufacturing firms, and e-commerce websites collectively lose around $1.8 trillion annually to inventory distortion. If this problem is solved, sales may increase by 10.3 percent. The businesses are concerned about mitigating this loss. Artificial intelligence (AI) can play a significant role in building resilient supply chains. However, developing AI models consumes time and cost. In this paper, we propose a No Code Artificial Intelligence (NCAI) enabling non-technical companies to build machine learning models based on production quantity and inventory replenishment. The development of the NCAI model is fast and inexpensive. However, little research deals with applying NCAI to operations and supply chain problems. Addressing the existing gap, we show the application of NCAI in the retail industry. [ABSTRACT FROM AUTHOR]

The agricultural supply chains (ASCs) are exposed to unprecedented risks following COVID-19. It is necessary to investigate the impact of risks and to create resilient ASC organisations. In this study, we have identified and assessed the ASC risks caused by disruptions. These threats were assessed using Fuzzy Linguistic Quantifier Order Weighted Aggregation (FLQ-OWA). The findings reveal that supply risks, demand risks, financial risks, logistics and infrastructure risks, management and operational, policy and regulation, and biological and environmental risks have a significant impact in ASC depending upon the organisations scope and scale. Various strategies such as adoption of industry 4.0 technologies, supply chain collaboration and shared responsibility is identified for sustainable future. Theoretical and managerial implications are provided based on the outcomes of the study. [ABSTRACT FROM AUTHOR]

In a dynamic and quickly changing world, digital innovation and transformation can help enhancing organizational efficiency and have competitive advantage. In addition, the digital innovation and transformation can facilitate the development of a growth‐oriented culture of workforce. Therefore, this study aims at developing the digital innovation and transformation capabilities at large organization. The study uses a four‐layered process for driving the digital innovation and transformation in the case organization. The study positions the digital innovation and transformation mechanism through the lens of the dynamic capability view and institutional theories. The findings indicate the emergence of digital champions as change agents, a digital council as a monitoring channel, a digital core team as technological enablers and reverse mentoring as an innovative cultural dimension of change facilitating dynamic capabilities of the organization. In terms of institutional pressures, coercive and mimetic pressures emerged as major contributors to the advancement of the digital skill set and digital mindset of the experienced workforce especially, supported by Hofstede's cultural dimensions. Study further delineates the insights for practice, theory and policy. To this end, the study showcases the future scope of work at the case company, since it is an ongoing project on digital innovation and transformation to make organization and related infrastructure resilient, digital and innovative. [ABSTRACT FROM AUTHOR]

Ammonia, as the second most-produced chemical worldwide, serves diverse roles in the industrial and agricultural sectors. However, its conventional production via the Haber–Bosch process poses significant challenges, including high energy consumption and carbon dioxide emissions. In contrast, photocatalytic nitrogen (N2) fixation, utilizing solar energy with minimal emissions, offers a promising method for sustainable ammonia synthesis. Despite ongoing efforts, photocatalytic nitrogen fixation catalysts continue to encounter challenges such as inadequate N2 adsorption, limited light absorption, and rapid photocarrier recombination. This review explores how the electronic structure and surface characteristics of one-dimensional nanomaterials could mitigate these challenges, making them promising photocatalysts for N2 fixation. The review delves into the underlying photocatalytic mechanisms of nitrogen fixation and various synthesis methods for one-dimensional nanomaterials. Additionally, it highlights the role of the high surface area of one-dimensional nanomaterials in enhancing photocatalytic performance. A comparative analysis of the photocatalytic nitrogen fixation capabilities of different one-dimensional nanomaterials is provided. Lastly, the review offers insights into potential future advancements in photocatalytic nitrogen fixation. [ABSTRACT FROM AUTHOR]

In the industrial sector, efficient production and optimal use of thermal energy are primary concerns for managers and engineers. Considerable research has been devoted to improving and promoting thermal energy efficiency, especially energy recovery in the context of sustainability. Pinch analysis is one of the most powerful methods in this regard. To maximise the energy recovery (MER), the pinch method is well-established in designing an optimal heat exchange network (HEN). Exergy analysis is combined with the pinch method to minimise the work potential loss (exergy loss) while ensuring maximum heat recovery. This study presents a generic algorithm built using Python language to predict and quantify energy and exergy targets in industrial processes. It provides a framework to guide experts and planners in efficiently using the combined analysis tools. The generic algorithm is based on advanced numerical and graphical tools. It provides exergy problem table algorithm (Ex–PTA) and grand composite curve (EHR and HRP) tools. For Δ T min = 10°C, the generic algorithm is implemented in a building complex case study. The energy targets for heating and cooling requirements are 316.2625 kW and 0 kW, respectively. The obtained exergy targets are less attractive given an improvement from advanced utility integration; this is due to the treated system (medium-temperature system) and not to the reliability and efficiency of the generic algorithm. To evaluate the generic algorithm calculations, they are executed in a low-temperature process in which pinch exergy analysis (PExA) has already been performed. The simulated and generated results are identical, demonstrating the reliability and effectiveness of the developed generic algorithm. [ABSTRACT FROM AUTHOR]

Corporate entrepreneurial leadership (CEL) plays a critical role in promoting innovative behavior that disrupts existing practices in organizations, to say the least, encouraging new policy initiatives that could affect the business and social performance of the organizations under their sustainable development goals (SDGs). CEL can help achieve SDGs by redesigning different contextual factors to help promote various policy initiatives. In this vein, this study identifies the factors which could improve the business and social performance of the organizations helping to achieve SDGs through an amalgam of theoretical lenses, particularly the dynamic capability view. Based on extant literature, we developed, validated, and applied a theoretical model using the partial least square structural equation modeling technique on data collected from 327 respondents from different organizations. The study found that CEL capability significantly and positively impacts the various organizational entities and resources, which in turn affects the business and social performance of the organizations. Theoretical and managerial implications of the findings are also discussed. [ABSTRACT FROM AUTHOR]

Overthinking refers to the process of dwelling on thoughts and ideas for an extended period of time, often leading to a feeling of mental exhaustion and anxiety. It involves analyzing and interpreting situations and events in excessive detail and repeatedly replaying scenarios in one's mind. We found that people who are experiencing an overthinking issue, are unable to make tough life decisions or when they are dealing with insecurities. Causes of this mental clutter are daily stress, the paradox of choices, too much stuff, and the negativity bias. We also found the SMART (which stands for Specific, Measurable, Attainable, Relevant, and Time-bound) goals design approach during our literature study. Through our research paper, we try to solve this issue by employing Design Research Methodology (DRM). During this DRM, we did secondary research, conducted interviews with stakeholders as a part of our primary research, and talked with psychologists to deepen our knowledge in this domain which helped us to define our target users. The outcome of this research was a mobile application that aims to assist overthinkers in social interaction and achieving their individual goals while also assisting them to reframe their cognitive processes. [ABSTRACT FROM AUTHOR]

The present study investigates use of blended concept map technique applied to the thermodynamics in the second year of Mechanical engineering of University of Mumbai, India. Two studies have been designed. In one study, traditional teacher leaning was followed to learn the topic of thermodynamics and in another study, students taught the same topic with concept map using software. The present work shows that there is significant difference between test score of pre and posttests who uses concept maps. Students showed positive inclination towards use of concept maps. [ABSTRACT FROM AUTHOR]