Search Results (2,051)

This study explains how strategy–execution gaps become self-reinforcing during digital process transformation in layered manufacturing organizations. Drawing on an embedded qualitative process study of a large Chinese brewery’s transformation (2020–2024), we triangulate 10 semi-structured interviews across hierarchical levels with longitudinal public disclosures to reconstruct the initiative timeline and trace mechanisms across change phases. The analysis shows that platform-based process governance can scale faster than shared meaning and dialog, producing frontline sensemaking gaps and formalistic, top-down communication. These conditions thin employee voice and weaken feedback closure, which in turn erodes the legitimacy of organizational diagnosis and fragments implementation support. As interface problems are handled through local workarounds, management intensifies visibility-based monitoring, further suppressing voice and reinforcing the execution gap. We develop an organizational development process model that centers feedback closure and diagnosis legitimacy as bridging mechanisms linking soft change dynamics (meaning, trust, voice) with hard digital governance (process standards, data infrastructures, monitoring). The model offers actionable implications for leaders to build closure and legitimate diagnosis as operational capabilities throughout transformation. Full article

A business model is an essential concept for securing long-term success and competitive advantage, where technologies take on an enabling role. Without the respective technology, the business model becomes unviable. Digital technologies are well known to enable business models, and various definitions of the term digital business models and their characteristics are discussed in the existing literature. However, scholars sometimes use this term interchangeably with the term technology-based business models, although not all technologies are digital in nature. In fact, many different types of technologies other than digital ones exist. A strong theoretical foundation for digital business models is available, while the research on technology-based business models is fragmented and incomplete. This term has been used without further defining its meaning or the definitions provided are too narrow and decisive characteristics are missing. Although authors have used these two terms interchangeably, they cannot be seen as equivalent, and the definitions and characteristics of digital business models cannot be simply transferred to the concept of technology-based ones. Therefore, the absence of a holistic and comprehensive definition of the term technology-based business models in the existing literature represents a significant gap that this research seeks to address. The aim of our study was to examine how business models are based on a particular technology. We use the results of a systematic literature review and semi-structured expert interviews to construct a comprehensive definition for the term technology-based business models, and we identify the major and minor characteristics of both terms. In addition to adding to the business model literature, these findings help practitioners understand technology-based business models in more detail and how technology can enable business models to meet customers’ needs. Full article

This study examines how artificial intelligence (AI) contributes to the formation of new quality productive forces (NQPF) at the employee level. While prior research has largely treated AI as an external technological driver, this study investigates whether AI becomes embedded within employees’ capabilities through confidence and skill transformation. Using survey data from 303 employees in Vietnamese commercial banks, the study applies exploratory factor analysis and regression models to analyze the relationships among AI confidence, skill transformation, work experience, and NQPF. The results show that AI confidence has a significant positive effect on NQPF, and this relationship is strengthened by skill transformation. However, work experience weakens this effect, suggesting uneven adaptation across employee groups. These findings indicate that the impact of AI on productive transformation depends not only on technological deployment but also on workforce capability development. The study contributes to the literature by providing micro-level evidence on how AI may be internalized within labor processes in emerging economies. Full article

Leaders and managers frequently face the need to make highly complex decisions with incomplete or fragmented information. Traditional decision support systems largely emphasize the visualization of data but often fall short in producing context-sensitive insights that can directly inform decision-making. This paper examines how narrative techniques combined with machine learning can strengthen communication across organizational hierarchies, particularly by improving the transfer of tacit expertise and contextual knowledge. To explore this, a transdisciplinary literature review was conducted using articles published within the last five years from databases such as Scopus, Web of Science, and ScienceDirect. The review highlights that narrative-driven reporting has been most commonly applied in fields such as accounting and sustainability, where expert interpretation replaces purely numerical summaries with more meaningful analytical explanations. Such approaches can also embed sentiment and personalization, commonly referred to as Narrative Disclosure Tone. Building on this foundation, the study investigates how Artificial Intelligence-driven decision support can formally integrate narrative elements to enhance report clarity, usability, and strategic relevance. Findings suggest that combining machine learning with expert-driven narrative reporting supports more innovative decision support systems and facilitates the alignment of tacit knowledge with data-driven insights. Full article

Robust measurement of entrepreneurial competencies (ECs) is crucial for entrepreneurship education, yet their internal structure remains theoretically contested and empirically underexamined. This study examined whether the four-factor Entrepreneurial Career Competency Instrument (ECCI) exhibits a hierarchical (bifactor) structure among South African entrepreneurs. Using two non-probability samples (N = 1305; N = 280), we analysed competing models, including a bifactor exploratory structural equation model (ESEM). The selected 56-item bifactor ESEM solution was examined for conceptual replicability in the smaller sample using Bayesian structural equation modelling (BSEM) with informative priors and sensitivity analyses to address small-sample uncertainty. Our findings revealed a theoretically supported hierarchical structure with a strong general factor and distinct specific factors: entrepreneurial career mindset, innovativeness, motivation, and implementation, enhancing the interpretation of scores. This study guides ECCI usage by suggesting total scores for broad assessments and domain scores for diagnostic feedback. Methodologically, the findings demonstrate that combining frequentist and Bayesian approaches across samples strengthened structural validity and provided insights into evaluating imprecise responses to self-report measures and addressing sampling constraints. Overall, this work contributes a robust structural model of the ECCI and enriches the EC literature, serving as a framework for refining, testing and applying attribute-based EC measures in diverse contexts. Full article

Today’s global and competitive environment forces companies to revise their competitive strategies and assess their operations’ performance. Customers are demanding new products and services, and organizations should adapt to the changing requirements of the customers. Companies may achieve excellence in their operations with cost reduction, by reducing time-to-market, and through improvements in delivery and quality. The main contribution of this study is assessing the linkages among operational performance (OP), environmental dynamism (ED), and competitive strategy (CS) in an emerging economy, Turkey. This study also aims to define the dimensions used to assess the operational performance, which are called the competitive manufacturing priorities in the operations management literature. To test the linkages between environmental dynamism, operational performance, and competitive strategy, a structural model is proposed. Analyses are conducted in SPSS 28.0 and AMOS 24.0 programs using the data gathered from Turkish manufacturing companies. Since 99.8% of firms operating in Türkiye are SMEs, most of the companies participating in this study (124 of 211) are also SMEs, and another contribution of this study is understanding the dimensions affecting the operational performance of SMEs According to the results, environmental dynamism has a significant relation to operational performance, and operational performance has a positive linkage with competitive strategy as well. The results also indicate that the most important dimensions used in assessing operational performance are customer satisfaction and supplier performance, as expected for manufacturing companies. Furthermore, the results of this study are expected to support organizations in developing and implementing effective strategies that integrate new capabilities and environmental considerations into their competitive strategy. As expected in SMEs, the most used competitive strategy is found to be “cost leadership,” because they can achieve operational performance by efficiently using resources, and by minimizing the production and transaction costs, they can enhance their competitiveness in the market. Full article

Lean production philosophy and sustainability approach have become a critical framework for efficiency improvement, waste reduction, and promoting sustainable manufacturing practices. In the age of artificial intelligence (AI), there is a synergy, which has now found new dimensions, data-driven decision-making, predictive analytics, and operational agility. AI technologies promise to transform industrial processes by converging lean production and sustainability principles, a synergy explored in this paper. AI APIs enable the use of AI to improve resource utilization, reduce environmental pressure, and maintain economic growth inherent to all business sectors while also fostering social accountability. In this study, a robust regression model is employed to study the role of AI in moderating the lean practices and sustainability outcomes relationship, using a sample of 528 manufacturing firms. The results show that the contribution of AI technologies to economic, ecological, and social sustainability is effectively multiplied by that of lean production. This research offers a framework to help practitioners and policymakers optimize production systems in line with Sustainable Development Goals. Finally, the study delivers actionable recommendations for navigating skill gaps and cybersecurity risks that were identified. In sum, this paper contributes to the rapidly emerging conversation by providing empirical evidence on AI’s moderating role in the lean–sustainability relationship and offering a strategic framework for practitioners. Full article

This study examines the development and consequences of student–institution distrust (SID) in higher education. While prior research has predominantly focused on trust, limited attention has been given to distrust as a distinct psychological construct influencing student experiences. Guided by Institutional Logics Theory, the study investigates how perceived institutional practices, institutional support, and cost–value (ROI) perceptions shape SID and how distrust influences sense of belonging, academic engagement, and help-seeking intentions. Data were collected from 600 undergraduate students enrolled in Business Administration and Tourism programs at public universities in Saudi Arabia. Multi-Group Structural Equation Modeling (MG-SEM) was employed to examine the proposed relationships and the moderating role of academic discipline. The results indicate that institutional practices, perceived support, and ROI perceptions significantly predict student–institution distrust. In turn, distrust exerts significant negative effects on students’ sense of belonging, academic engagement, and help-seeking intentions, confirming the theorized detrimental role of distrust in shaping student outcomes. The findings further reveal that academic discipline strengthens the negative impact of distrust on student outcomes, with stronger effects observed among Tourism students. By conceptualizing distrust as a multidimensional construct rather than simply the absence of trust, this study contributes to the literature on student–institution relationships and provides practical insights for designing transparent and supportive institutional environments that reduce distrust and enhance student engagement. Full article

Generative artificial intelligence (GenAI) is increasingly portrayed as a transformative technology capable of simultaneously enhancing operational efficiency and enabling strategic growth. Yet small and medium-sized enterprises (SMEs) experience heterogeneous outcomes, suggesting that GenAI does not generate value uniformly across firms. This study develops and empirically informs a contingency framework explaining how distinct GenAI functions relate to differentiated strategic objectives and how technological, organizational, and environmental (TOE) readiness conditions shape this relationship. Using a three-round Delphi study with an interdisciplinary expert panel, including GenAI consultants, corporate managers, legal experts, academic researchers, and public-sector policymakers, we identify six core GenAI functional domains associated with efficiency-oriented and growth-oriented strategies. The findings suggest that operational automation and data intelligence are more strongly associated with efficiency objectives, whereas market intelligence, market testing, linguistic expansion, and idea generation are more closely related to growth objectives, although none is exclusively linked to a single strategic goal. Importantly, TOE readiness is found to play a key role in shaping the extent to which function-specific GenAI deployment translates into realized strategic value, with organizational readiness appearing more prominent than technological or environmental conditions. By shifting the focus from adoption to function-specific strategic alignment and readiness configurations, this study advances understanding of GenAI-enabled strategic value realization and heterogeneous transformation pathways in SMEs. Full article

The emergence of smart healthcare platforms has significantly enhanced the accessibility of medical services, yet it has also introduced critical challenges such as information overload and patient decision-making dilemmas. This study investigates the interaction and synergistic optimization of a dual-drive mechanism—comprising ‘patient proactive search’ and ‘artificial intelligence (AI)-driven recommendations’—within healthcare platform recommendation systems. By developing a game-theoretic model that incorporates heterogeneous users (including random single-search users and rational multi-stage decision-makers) and competitive medical institutions, we systematically analyze how different recommendation strategies influence market equilibrium, patient utility, and platform profit. The findings reveal that in the absence of AI-driven recommendations, a higher proportion of random users intensifies price competition among providers. In contrast, the integration of AI-driven recommendations with proactive search behavior effectively mitigates price wars and enhances matching efficiency. Furthermore, our analysis identifies an optimal recommendation strategy weight that enables the platform to simultaneously improve both equilibrium price and user demand. This research offers a theoretical foundation for the design of efficient and sustainable recommendation systems in smart healthcare platforms and provides practical managerial insights for improving medical service efficiency and optimizing resource allocation. Full article

The contemporary crisis of trust in institutions and organizations has intensified what recent literature describes as a “leadership recession”, characterized by declining ethical legitimacy and limited capacity to manage systemic change. This article introduces the concept of leadership recession as a systemic and ethical phenomenon and proposes an ethical–systemic leadership model as potential pathway toward leadership recovery. Drawing on Aristotelian ethics—particularly the concepts of phronesis (practical wisdom), justice, and virtue—combined with systems theory and change management, the study develops an integrated theoretical framework that reconceptualizes leadership legitimacy as both a moral and organizational condition. Empirically, the study is based on a quantitative survey of 402 employees from the public and private sectors in Greece. The findings indicate that employees’ perceptions of effective leadership are positively associated with ethical virtues and leaders’ capacity to understand and manage organizational interdependencies. Ethical legitimacy emerges as an important relational mechanism that enhances trust, participation, and acceptance of organizational change. The article contributes to leadership and administrative sciences literature by introducing the notion of leadership recession and by proposing an ethical–systemic leadership paradigm that integrates values-based leadership, systemic thinking, and change management. The findings offer both theoretical insights and practical implications for leaders and organizations seeking sustainable and ethically legitimate transformation. Full article

Background: Artificial intelligence (AI) is transforming leadership and raising critical questions about decision-making, leadership capabilities, and ethical accountability in increasingly digitalized organizations. Objective: This systematic review synthesizes peer-reviewed evidence to answer: How does AI integration transform leadership and decision-making in organizations? Methods: A PRISMA 2020-compliant systematic review was conducted using structured Boolean searches in Scopus and Web of Science Core Collection on 26 February 2026. Eligibility was restricted to English-language, peer-reviewed, open-access journal articles with an explicit AI–leadership integration signal. Records were deduplicated and screened by two reviewers, with full-text assessment conducted against predefined criteria. A qualitative, narrative (conceptual) synthesis integrated heterogeneous empirical and conceptual contributions. Results: From 452 records, 84 studies met inclusion criteria. The synthesis identified three recurring analytical dimensions: (i) AI-augmented decision-making, (ii) leadership competencies and role shifts, and (iii) ethical challenges (accountability, transparency/opacity, fairness, privacy, and human agency). Integrating these dimensions, the review conceptualizes AI-driven leadership as a hybrid decision phenomenon in which AI accelerates and expands decision cycles, leaders reconfigure roles toward decision architecture and orchestration, and ethical conditions shape legitimacy, adoption, and authority dynamics. Conclusions: The review advances theory by specifying a mechanism-oriented model of AI-driven leadership and proposing testable propositions linking AI modality, role reconfiguration, and ethically conditioned legitimacy under key boundary conditions (e.g., sectoral stakes, governance capacity, and data/infrastructure readiness). Practically, it outlines an implementation pathway emphasizing decision criticality assessment, formalized human–AI task allocation, and institutionalized oversight mechanisms. Limitations: Findings are bounded by database selection and the open-access full-text constraint, which may under-represent paywalled scholarship. Full article

In the current context of the complexity of municipal management, the sustainable development of communities and compliance with the “2030 Agenda” objectives are essential. These objectives aim to reduce the negative environmental impact of cities by the year 2030, with special attention to issues such as air quality and municipal waste management, among other UN actions. The main objective is to verify the impacts on the residents around the São João monument, located in a city in the interior of Brazil, with its installation following the principles of sustainable development, Agenda 2030, and SDG 8. It is relevant to verify, with the rural community, the positive and negative impacts on the quality of life and development of families who reside around the São João monument. The research method was a single case study, and the data collection techniques were qualitative. Finally, the results point to benefits for the community with the implementation of the São João monument, such as the generation of income and jobs, the development of tourism, and compliance with SDG 8, goal 8.9. However, improvements in local planning and development are still needed. Full article

Chile faces an institutional context marked by public distrust and increasing demands for legitimacy in public management. In this scenario, this study aimed to examine, within the framework of the Job Demands–Resources (JD-R) theory and the HERO model, the relationships between servant leadership, public service motivation, work engagement, and healthy organizational outcomes in the Chilean public sector, considering the moderating effect of the supervisor’s gender. We used a sample of 428 employees from 22 public institutions, with validated instruments to assess servant leadership, public service motivation, work engagement, and organizational outcomes. Structural equation modeling confirmed the five proposed hypotheses: servant leadership was positively related to public service motivation and work engagement, and work engagement was positively associated with healthy organizational outcomes, showing partial mediation effects among these variables. No moderating effects of the supervisor’s gender were found. This study provides empirical evidence on the motivational mechanisms operating within the public sector and highlights the relevance of servant leadership as a key social resource for fostering motivation, work engagement, and organizational well-being within the specific context of Chilean public institutions included in the study. Full article

Hospitals play a central role in promoting health and well-being, yet they are also among the most resource-intensive institutions, contributing significantly to environmental degradation through high energy and water consumption, extensive waste generation, and reliance on single-use materials. This conceptual paper explores how principles of the circular economy and green economy can be integrated into hospital operations through a strategic Corporate Social Responsibility (CSR) framework, reframing sustainability as a strategic management issue rather than a compliance-driven activity. Drawing on environmental economics, sustainability studies, and institutional theory, the paper develops an integrated conceptual model structured around the environmental, social, and economic pillars of sustainability. Within this framework, four interconnected operational domains are identified: waste management and circular practices, energy consumption and renewable integration, sustainable procurement and circular supply chains, and economic and policy incentives. The social dimension explicitly encompasses healthcare staff and patients, addressing issues of workforce well-being, health education, safety, quality of life, and equitable care delivery. This advances theory by positioning strategic CSR as a function of circular and green economy, yielding a new model for hospitals, S-CSR = f(CE, GE). The paper also examines institutional and cultural barriers that constrain sustainability implementation and highlights the role of strategic leadership, governance, and system-wide innovation in overcoming these challenges. While not empirical, the study provides a theoretical foundation to inform future research, policy development, and strategic decision-making aimed at advancing sustainable, low-carbon, and resilient healthcare systems. Full article