The current business environment characterized by volatility, uncertainty, complexity, and ambiguity (VUCA) advances numerous challenges for organizations. To respond effectively to these changing demands, traditional approaches to solving problems often prove inadequate in this dynamic context. A new approach, the ProCESS methodology, was developed and tested in the last three years within an Erasmus+ consortium in four European countries. This approach stimulates unconventional thinking and the finding of creative solutions for real-world business challenges. The aim of this perspective paper is to present the research data collected in two Romanian companies by testing ProCESS methodology. In the discussion section, the paper highlights the potential of this methodology that uses various artistic tools like drawing, music, modeling, or meditation to encourage participants to tap into their sensory, emotional, and spiritual sides for finding new and unexpected solutions. The paper also discusses potential influences on organizational culture and employee well-being.

This article explores the implications of directive change management, characterized by top-down leadership and minimal employee involvement, on organizational dynamics, employee morale, and job security. This approach's psychological and operational impacts are underscored, emphasizing the imperative of addressing employee perceptions and fostering trust. Strategies for rebuilding trust and enhancing morale post-directive change management are presented, including transparent communication, participative decision-making, and recognition of employee contributions. The significance of enhancing job security through clear policies, open dialogue, and robust mental health and well-being support systems is highlighted. Practices that encourage job dedication are introduced, emphasizing goal alignment, meaningful work design, and a culture of innovation and continuous improvement. Long-term strategies for cultivating a healthy workplace, such as establishing feedback mechanisms, investing in leadership development, and maintaining organizational adaptability, are also discussed. This brief article is an introductory resource for business leaders, managers, and change practitioners seeking to be better equipped with the necessary tools and strategies to navigate the post-implementation effects of directive change management. It is anticipated that this information can assist leaders and organizations in navigating the challenges of directive change management, promoting resilience, employee well-being, and sustainable organizational success.

In today’s fast-moving, disrupted business environment, supply chain risk management is crucial. More critically, Industry 4.0 has conferred competitive advantages on supply chains through the integration of digital technologies into manufacturing and logistics, but it also implies several challenges and opportunities regarding the management of these risks. This paper looks at some ways emerging technologies, especially Artificial Intelligence (AI), help address pressing concerns about the management of risk and sustainability in logistics and supply chains. The study, using a systemic literature review (SLR) backed by a mapping study based on the Scopus database, reveals the main themes and gaps of prior studies. The findings indicate that AI can substantially enhance resilience through early risk identification, optimizing operations, enriching decision-making, and ensuring transparency throughout the value chain. The key message from the study is to bring out what technology contributes to rendering supply chains resilient against today’s uncertainties.

Distributed Energy Resources (DERs), such as solar photovoltaic (PV) systems, wind turbines, and energy storage systems, offer many benefits, including increased energy efficiency, sustainability, and grid reliability. However, their integration into the smart grid also introduces new vulnerabilities to cyber threats. The smart grid is becoming more digitalized, with advanced technologies like Internet of Things (IoT) devices, communication networks, and automation systems that enable the integration of DER systems. While this enhances grid efficiency and control, it creates more entry points for attackers and thus expands the attack surface for potential cyber threats. Protecting DERs from cyberattacks is crucial to maintaining the overall reliability, security, and privacy of the smart grid. The adopted cybersecurity strategies should not only address current threats but also anticipate future dangers. This requires ongoing risk assessments, staying updated on emerging threats, and being prepared to adapt cybersecurity measures accordingly. This paper highlights some critical points regarding the importance of cybersecurity for Distributed Energy Resources (DERs) and the evolving landscape of the smart grid. This research study shows that there is need for a proactive and adaptable cybersecurity approach that encompasses prevention, detection, response, and recovery to safeguard these critical energy systems against cyber threats, both today and in the future. This work serves as a valuable tool in enhancing the cybersecurity posture of utilities and grid-connected DER owners and operators. It allows them to make informed decisions, protect critical infrastructure, and ensure the reliability and security of grid-connected DER systems in an evolving energy landscape.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.