Industry 4.0 and Industry 5.0 are reshaping business models and scientific concepts, bringing challenges and opportunities. Stakeholders require a performance measurement system that enables them to address challenges and effectively capture opportunities. However, the current literature lacks consistency in utilising appropriate performance measurement systems, and the authors aim to identify current trends in measuring organisational performance within the context of Industry 4.0 and Industry 5.0 in manufacturing companies. A systematic literature review, based on the PRISMA model, was conducted to identify which performance measurement systems for manufacturing companies are utilised in the context of Industry 4.0 and Industry 5.0. Findings indicate that the current literature lacks consistency regarding performance measurement systems for manufacturing companies, which encompass elements of Industry 5.0, including human-centrism and sustainability. We recommend a human-centric and sustainability-oriented approach to measuring performance in Industry 5.0, prioritising metrics that value employees as co-creators of success, integrate well-being and ethical dimensions, and focus on human-technology collaboration. Such an approach should ensure that technology supports, rather than replaces, humans, aligning organisational goals with societal and environmental values.

In an era of rapid digital transformation, organisations must cultivate dynamic capabilities that promote innovation and continuous learning. This study examines how self-determined motivation and innovation adoption are crucial enablers in developing the digital competencies essential for employees to navigate digital transformation. Grounded in Self-Determination Theory and the Diffusion of Innovation framework, our research underscores the systemic role of individual agency, technological advancements, and organisational structures in facilitating workforce adaptation. Employing a quantitative approach with 152 survey participants, our findings reveal that self-determined motivation alone is inadequate, while adopting innovation significantly influences digital competence. We demonstrate that human-centred factors must align with systemic digital transformation efforts. Moreover, we highlight the necessity of integrating employee capabilities into broader enterprise and government digital innovation strategies. The implications of this study are both theoretical and practical. We stress the need for organisations to design change processes that support digital knowledge acquisition and adaptability in evolving workplaces. Our research offers a systemic perspective on digital transformation, reinforcing that successful organisational innovation requires structured learning environments that empower employees. By fostering an ecosystem where digital competencies are nurtured, organisations can enhance agility, resilience, and sustained competitiveness in the digital age.

Being a part of the creative economy, the craft sector is currently experiencing a revival. The sector is distinguished by a business setting, production of goods, which are “creative” by nature, as well as entrepreneurs, who are often more content, rather than commercially, driven. However, research on the craft sector and understanding of the diversity of craft entrepreneurs is still limited. Within the broad area of research on entrepreneurship, this article aims to explore the nature of the entrepreneurs in the craft sector in relation to their social identity as an entrepreneur pursuing an opportunity in the craft sector and to propose a typology of craft entrepreneurs. The article presents a qualitative empirical study based on twenty case studies, representing different cases of craft ventures in Latvia. The results offer insight into the peculiarities of the entrepreneurial pursuit of opportunities in the craft sector and put forward a typology of craft entrepreneurs based on their social identity and developed opportunity.

Organizational acceptance of change and the willingness to embrace it is largely dependent on employees and their experiences – generations respond to change differently, especially when change is related to information technologies. The paper aims to explore how three major generations of employees – Baby Boomers, Xers and Millennials, react to change and how their commitment to change affect satisfaction and engagement. Data (N = 202) is collected through structured questionnaire and structural equation modelling technique is used for analysis. The results reveal what major differences between generations are in place. Recommendations for managing organisational change across the three generations are provided.

This conceptual article introduces Perceived Cognitive Assistance (PCA)—a novel psychological construct capturing how interactive support from Large Language Models (LLMs) alters investors’ perception of their cognitive capacity to execute complex trading strategies. PCA formalizes a behavioral shift: LLM-empowered retail investors may transition from intuitive heuristics to institutional-grade strategies—sometimes without adequate comprehension. This empowerment–distortion duality forms the theoretical contribution’s core. To empirically validate this model, this article outlines a five-step research agenda including psychological diagnostics, trading behavior analysis, market efficiency tests, and a Behavioral Shift Index (BSI). One agenda component—a dual-agent simulation framework—enables causal benchmarking in post-LLM environments. This simulation includes two contributions: (1) the Virtual Trader, a cognitively degraded benchmark approximating bounded human reasoning, and (2) the Digital Persona, a psychologically emulated agent grounded in behaviorally plausible logic. These components offer methods for isolating LLM assistance’s cognitive uplift and evaluating behavioral implications under controlled conditions. This article contributes by specifying a testable link from established decision frameworks (Theory of Planned Behavior, Technology Acceptance Model, and Risk-as-Feelings) to two estimators: a moderated regression for individual decisions (Equation (1)) and a composite Behavioral Shift Index derived from trading logs (Equation (2)). We state directional, falsifiable predictions for the regression coefficients and for index dynamics, and we outline an identification and robustness plan—versioned, time-locked, and auditable—to be executed in the subsequent empirical phase. The result is a clear operational pathway from theory to measurement and testing, prior to empirical implementation. No empirical results are reported here; the contribution is the operational, falsifiable architecture and its implementation plan, to be executed in a separate preregistered study.