Purpose: The purpose of this paper is to build a research model that examines the impact of leadership on trust, knowledge management and organizational performance.Design/methodology/approach: An instrument containing six constructs (leadership: leading organization; leadership: leading people; leadership: leading self, trust, knowledge management and organizational performance) was designed and administered to subjects from all levels of management in various organizations in nine regions of the USA. Collected data were analyzed using partial least squares path modeling to test the hypotheses.Findings: The study’s findings revealed positive and significant linear connection among leadership (leading organization, leading people and leading self), trust, knowledge management and organizational performance.Practical implications: The findings imply that effective leadership (leading organization, leading people and leading self) contributes to elevated trust among people, promotes the successful implementation of knowledge management processes, and in turn enhances organizational performance. Therefore, leadership training and development must be a top strategic priority for any organization.Originality/value: This study enriches the literature by demonstrating that effective leadership stands as the bedrock of the elevated trust, the successful knowledge management processes and the enhanced organizational performance.

The paper aims to identify how digital transformation and Generative Artificial Intelligence (GAI), in particular, affect the manufacturing processes. Several dimensions of the Industry 4.0 field have been considered, such as the design of new products, workforce and skill optimisation, enhancing quality control, predictive maintenance, demand forecasting, and marketing strategy. The paper adopts qualitative research based on a critical review approach. It provides evidence of the GAI technology support in the mentioned areas. Appropriate use of emerging technology allows managers to transform manufacturing by optimising processes, improving product design, enhancing quality control, and contributing to overall efficiency and innovation in the industry. Simultaneously, GAI technologies facilitate predictive analytics to forecast and anticipate future demand, quality issues, and potential risks, improve a marketing strategy and identify market trends.

The purpose of this study was to find out which one of the four selected predictor variables, i.e., leadership, trusting beliefs, role values, and information security policy awareness are most influential in predicting employees’ intention to comply with organizational information security policy. An instrument with five constructs was administered to subjects from a higher-education university in the USA. Collected data were methodically examined through multiple regression analysis. Results indicated that all four predictor variables were influential in predicting employees’ intention to comply with organizational information security policy requirements. Implications of the findings are discussed and recommendations for future research are made.