Business, Economics and Management

Abstract: Digital technologies can change not only how organizational activities are performed and coordinated but also the dependencies through which those activities are connected. This article develops dependency restructuring as a meso-level organizational mechanism linking technologically enabled changes in activity configurations to changes in coordination requirements and organizational adaptation. Building on coordination theory, organizational information-processing research, interdependence theory, and information-systems research on technological enactment, we distinguish dependency restructuring from technological adoption, process change, and changes in coordination mechanisms. Four analytical transformations are identified: dependency creation, elimination, redirection, and recombination. Historical illustrations from centralized and personal computing, enterprise systems, cloud computing, and artificial intelligence illustrate the analytical applicability of the mechanism across heterogeneous digital technologies. The analysis highlights that eliminating or redirecting human-mediated dependencies can simultaneously create technological or interorganizational dependencies, such that greater local autonomy need not reduce system-level dependence. The article contributes to research on digitally enabled organizational change by bringing changes in dependency configuration to the foreground as a distinct analytical mechanism and develops propositions and directions for empirical investigation.

Abstract: The electricity grid is a collective good that tends toward monopoly. It links private electricity generation to private electricity use. Its design converged near-globally at the end of the 20th century. Large-scale producers have separated ownership from transmission system operators. Quasi-markets link them. New challenges and opportunities render that design obsolete. Solar and wind energy are low-cost but intermittent. Secondary electricity, decentralized, becomes low-cost as well. Fast switches enable real-time adjustments in electricity production and use. Low-cost High-Voltage Direct Current lines centralize while also enabling decentralized frequency control. Centralizing and decentralizing options do not fit the currently fragmented markets and grid. Their integrated redesign is due. Key design elements include: a multi-layered meshed grid; multiple independent grid nodes; market rules that prohibit ownership of multiple linked nodes; real-time nodal pricing; equal prices for all purchasers at a node; and automatic nodal and full-grid equilibrium. The new driving mechanisms improve electricity system efficiency and resilience, contributing to several SDGs. They include a single real-time integrated market, car batteries replacing in-grid batteries, and system expansion linking to low-cost renewables. Costs are reduced by 1/4 in North America and Northeastern Asia and by 2/3 (!) in Western Europe-Mediterranean, currently highly fragmented.

Abstract: Employee-turnover warning in finance and taxation education must account for different job roles, repeated monthly records, rare departures, and uncertainty about when some fields became available. This study analyzed 1,397 de-identified employee records and reconstructed 6,935 monthly records for predicting voluntary turnover within 90 days. It compared 22 classifiers with the Hierarchical Risk Encoding XGBoost–CatBoost Ensemble (HRE-XCB), which combines Raw-XGB, HRE-XGB, and native CatBoost. Before model development, 278 employees were selected without reading their out comes. None of their earlier records entered feature screening, tuning, encoding, weighting, or cutoff selection. The search evaluated 152 base structures and selected weights of 0.65, 0.15, and 0.20. The June 2022 evaluation contained 278 separated employees and 24 departures. HRE-XCB achieved recall 0.7500, F1 0.3750, and PR-AUC0.3477. Among the equally tuned shortlist, random forest obtained the highest PR-AUC (0.3772), Extra Trees the highest F1 (0.4324), and histogram gradient boosting recall 0.7917 with the lowest Brier score (0.0752). A separate lower-tuning screen was led by preset gradient boosting (PR-AUC 0.4229). In 5,000 employee-cluster bootstrap samples, no tuned model had a PR-AUC difference from HRE-XCB whose 95% interval excluded zero. Component ablation showed that Raw-XGB alone had nearly the same PR-AUC as the complete ensemble (0.3481 versus 0.3477), while Raw-XGB plus HRE-XGB reached 0.3492. The study therefore supports employee-separated evaluation and decision-specific model choice, but not a universal-best algorithm or exact individual departure probabilities.

Abstract: Leadership has become one of the most critical determinants of organizational resilience, institutional effectiveness, societal transformation, and sustainable development. Yet despite decades of research, leadership scholarship remains fragmented across multiple theoretical traditions—including transformational, authentic, servant, adaptive, strategic, distributed, and complexity leadership—each emphasizing particular behaviors, competencies, or relational processes. Existing approaches have significantly advanced the understanding of leadership but provide limited capacity to compare leadership readiness across organizations, sectors, or countries using a standardized and multidimensional measurement framework. Consequently, no internationally recognized index currently exists to assess leadership capacity in a manner comparable to widely used composite indicators such as the Human Development Index or the Global Innovation Index.This article addresses this gap by introducing the Leadership Capacity Index (LCI), a novel conceptual and methodological framework designed to measure leadership capacity as a multidimensional capability rather than a collection of isolated leadership traits or styles. The article argues that leadership capacity is an emergent systemic property reflecting the ability of individuals, organizations, and institutions to mobilize people, knowledge, ethical values, innovation, and adaptive learning to achieve sustainable and regenerative transformation under conditions of complexity and uncertainty.Building upon an extensive review of leadership theories and organizational capability research, the paper proposes the Leadership Capacity Theory (LCT), which conceptualizes leadership capacity as a dynamic interaction among ten complementary dimensions: visionary capacity, ethical capacity, adaptive capacity, learning capacity, innovation capacity, collaborative capacity, systems thinking, cultural intelligence, ecological stewardship, and regenerative leadership. These dimensions are integrated into the Leadership Capacity Framework (LCF) and operationalized through the proposed Leadership Capacity Index (LCI), accompanied by a Leadership Capacity Maturity Model and a Leadership Diagnostic Toolkit.Rather than presenting a fully validated quantitative instrument, this article establishes the theoretical foundations for an international leadership measurement system. It outlines future directions for operationalization, psychometric validation, mathematical modeling, artificial intelligence-assisted assessment, and cross-cultural benchmarking. The Leadership Capacity Index is intended to support evidence-based leadership development across governments, businesses, universities, civil society organizations, and international institutions. Ultimately, the article argues that measuring leadership capacity is becoming as strategically important as measuring economic performance, innovation, or human development in addressing the complex challenges of the twenty-first century.

Abstract: Organizations increasingly require integrated mechanisms to continuously interpret human, structural, and cultural signals often overlooked by conventional business intelligence and human resource systems. This study presents IntellicaHR, a web-based socio-technical Organizational Intelligence System integrating role-based workflows, normalized performance indicators, Large Language Model–supported semantic analysis and interpretation, gamification, and established management theory. The platform operationalizes the McKinsey 7S Framework for continuous organizational alignment monitoring and uses Deming’s System of Profound Knowledge to structure executive-level explanations and recommendations. Because real workplace data on emotional climate, leadership behavior, skill alignment, and conflict are ethically and practically difficult to obtain, the system is demonstrated using three literature-grounded synthetic organizational scenarios: a Healthy Organization, a Skill-Misaligned Organization, and a Toxic Management Environment. Scenario characteristics are formalized through fuzzy linguistic states and overlapping membership functions to generate synthetic users, reports, assessments, project interactions, and managerial communications over a 45-day simulation. These artifacts are processed through IntellicaHR’s native analytics and interpretation pipeline. The resulting metric profiles matched the intended scenario definitions and were clearly distinguishable. The Healthy Organization exhibited high participation, strong skill adequacy, positive emotional tone, and low conflict; the Skill-Misaligned Organization showed capability and execution deficiencies; and the Toxic Management Environment exhibited elevated conflict, negative emotional patterns, and weaker managerial responsiveness. These findings demonstrate the functional coherence and scenario-sensitive behavior of IntellicaHR as a proof-of-concept artifact but do not establish real-world diagnostic accuracy, predictive validity, or organizational effectiveness, which require future longitudinal evaluation with real users and organizational data.

Abstract: Job satisfaction has become a significant factor in organizational performance, particularly in operational sectors such as port activities, where efficiency, coordination, and safety are essential. This study aimed to analyze the relationship between job satisfaction and perceived productivity among technical workers at port companies in Guayaquil, Ecuador. A mixed-methods approach with a convergent design was employed, integrating ordinal data obtained via surveys with qualitative data from semi-structured interviews. The survey, based on a 7-point Likert scale, was administered to 54 port technicians to measure job satisfaction and perceived productivity. The qualitative component consisted of semi-structured interviews with industry experts. Descriptive statistics and Spearman’s correlation coefficient were used to analyze the ordinal data, while the qualitative information was analyzed using thematic analysis. The findings revealed high levels of job satisfaction (59.3%) and perceived productivity (85.2%). Furthermore, a strong, statistically significant positive association was identified between the two variables (ρ = 0.770, p<0.001). Qualitative results reinforced these findings, highlighting motivation, recognition, and organizational climate as key elements influencing work performance. The study concludes that higher levels of job satisfaction are associated with higher levels of perceived productivity. The findings contribute to the social sustainability literature by showing how job satisfaction, recognition, motivation, and organizational climate are associated with perceived productivity in a highly demanding port context. The study highlights the importance of labor well-being and positive work environments as social sustainability dimensions that may support more sustainable and productive port operations.

Abstract: This perspective article argues that a critical weakness in contemporary Indian corporate governance lies in the inadequacy of the due diligence processes through which independent directors are appointed. Drawing on agency theory, resource dependency theory and the busyness hypothesis, it examines some major governance failures between 2022 and 2025. While these organizations differed in ownership structures, regulatory environments and business models, they exhibited recurring governance patterns despite the formal presence of independent directors. The article contends that prevailing governance reforms have focused primarily on structural compliance while paying insufficient attention to the substantive qualities that determine effectiveness. Synthesizing theoretical insights and contemporary governance evidence, it proposes that effective independent directors are distinguished by four interrelated attributes: domain expertise, time commitment, independence and a willingness to challenge management where appropriate. The article further argues that nomination and remuneration committees should function as rigorous due diligence institutions rather than procedural gatekeepers. By shifting attention from formal independence to functional effectiveness, the article contributes to ongoing debates on board governance, director accountability and corporate oversight in emerging markets. It offers a practical framework for strengthening independent director appointments and improving board effectiveness in promoter-dominated corporate environments.

Abstract: The tourism and hospitality industry relies fundamentally on the quality of human interactions, yet the sector continues to grapple with significant challenges in effectively and consistently training its workforce using resource-intensive traditional methods. This study addresses these challenges by presenting the design, development, and validation of an intelligent agent for training and evaluation, powered by Google’s Gemini 2.0 Flash model. The system processes internal organizational documentation to build a knowledge base, generates diverse question types for training, and provides automated evaluation and personalized feedback. Validation was conducted in a controlled laboratory environment corresponding to Technology Readiness Level 4 (TRL 4). The system achieved an overall success rate of approximately 82% across all test cases. It demonstrated perfect performance (100%) in social interaction and guided training capabilities. Notably, the automated evaluation engine achieved a 92% agreement rate with expert benchmarks, even for open-ended responses. However, limitations were identified in managing ambiguity and performing deep inferential reasoning beyond explicit documentation. The findings confirm the technical and functional viability of LLM-powered agents for automating hospitality training. This technology offers a scalable, objective solution that significantly reduces resource requirements while enabling personalized learning, although future optimization is needed for complex inference scenarios.

Abstract: The hospitality industry faces ongoing challenges when it comes to training and evaluating staff on critical operational procedures in an efficient and scalable way. Traditional training approaches are often expensive, time-consuming, and difficult to personalize for large teams. This paper presents the design, development, and validation of an intelligent conversational agent powered by Large Language Models (LLMs) aimed at automating training and assessment processes for hotel personnel. The proposed system leverages Google’s Gemini 2.0 Flash model, integrated into a conversational interface built with Chainlit, to support natural language interactions across four core modalities: general inquiries, structured training sessions, practice exercises, and formal assessments. The agent is capable of dynamically generating four types of questions—true/false, multiple choice, open-ended, and scenario-based—using internal hotel documentation as its knowledge base. It automatically evaluates user responses, delivers personalized feedback, and produces detailed performance reports enriched with data visualizations. A Technology Readiness Level 4 (TRL-4) validation was conducted in a controlled laboratory setting, where nine comprehensive functional test cases were executed. The results showed a 95% success rate across all validation criteria, demonstrating the system’s ability to accurately response to general queries, provide targeted training content, generate diverse assessment questions, perform objective evaluations with constructive feedback, etc. This proof of concept highlights the potential of LLM-based conversational agents to transform corporate training in the service industry by offering scalable, personalized, and cost-effective learning solutions. Future work will focus on advancing to TRL-5 validation through deployment with real users in operational hotel environments.

Abstract: Corporate social responsibility (CSR) is increasingly expected to fill welfare gaps in rural communities, especially in transition economies where firms often provide schools, healthcare, infrastructure, and other quasi-public goods. If CSR improves rural living con-ditions, it should, in principle, help retain population. Yet migration theory suggests a more ambiguous possibility: development may not only reduce deprivation but also ex-pand the aspirations and capabilities that make mobility feasible. This study examines this paradox using district-level data from eight rural districts in Kazakhstan’s Akmola region from 2010 to 2021. Applying Partial Least Squares Structural Equation Modeling, we estimate how CSR, amenities, agricultural structure, and economic vitality shape net migration. The results show that CSR substantially improves local amenities, but ameni-ties alone do not generate a strong retention effect. Economic vitality remains the central driver of migration outcomes, while agricultural development has limited demographic effects. These findings suggest that CSR can improve rural welfare without necessarily preventing outmigration. In transition economies, corporate-led development may there-fore operate less as a demographic anchor than as part of a broader process through which rural residents become more capable of pursuing opportunities elsewhere.

Abstract: While generative AI enhances efficiency, it simultaneously undermines the professional authority of high performers, thereby posing an expert identity threat to these high performers. Contrary to traditional perspectives that view identity threats as triggers of passive defensiveness, this paper constructs a moderated mediation model based on the dual-dimensional structure of identity (centrality-solidarity). A two-stage questionnaire analysis of 323 employees reveals that: (1) high performers perceive stronger expert identity threats; (2) these threats conversely prompt them to guide colleagues in using AI; (3) task-AI fit positively moderates this mediation effect. This study breaks through the traditional defense paradigm, confirming that high performers achieve identity compensation and power regeneration through helping others and empowering them, providing insights for organizations to promote the transformation of excellent employees into "human-AI collaboration mentor ".

Abstract:

Against the backdrop of rapid digital acceleration and a tightening UK labor market, Small and Medium-sized Enterprises (SMEs) are increasingly pressured to move beyond manual administrative processes to bridge the national "productivity gap." While digital transformation is often framed within a large corporate context, this research investigates the specific role of Human Resource Information Systems (HRIS) in driving operational efficiency and strategic performance within resource-constrained SME environments. This study aims to evaluate how HRIS integration transforms HR functions from an administrative burden into a strategic asset, while identifying the unique implementation hurdles and performance outcomes experienced by resource-constrained UK firms.This study adopts an interpretivist, qualitative approach to examine how HRIS integration transforms HR functions from administrative burdens into strategic assets. Data were collected through semi-structured interviews with 12 HR managers across the hospitality, retail, and recruitment sectors, and analyzed using thematic analysis.The findings reveal a three-stage, non-linear process of value creation: (1) administrative liberation through automation, (2) strategic visibility via data-driven insights, and (3) digital friction arising from cultural and technical barriers. While HRIS enhances operational efficiency and decision-making capability, its strategic impact is contingent upon organizational readiness, particularly digital literacy and change management practices. This study contributes to the HRIS and SME digital transformation literature by conceptualizing "digital friction" as a critical mediating construct, demonstrating that value creation in SMEs is an iterative and context-dependent process rather than a linear implementation. For practitioners, the study provides a roadmap for navigating digital transitions, emphasizing that the "human element" of change management is as vital as the technological infrastructure. While limited by its qualitative scope, the research sets a foundation for future longitudinal studies to measure the long-term ROI of integrated HR platforms in diversifying SME sectors.

Abstract: Over the last two decades, social enterprises in Romania have taken on an increasingly important role in the production and provision of social goods and services for vulnerable groups. Although forms of the social economy have long existed in Romanian society, sustainability remains a constant concern, particularly in the context of dependence on European Union structural funds. This study identifies the multidimensional factors influencing the sustainability of social enterprises in Romania, combining a quantitative analysis of 121 certified social enterprises from the National Register (2016–2022) with qualitative case studies of 15 selected organisations. Revenue diversification significantly contributed to financial sustainability (β = −0.28, p < 0.01), whilst high dependence on EU funding (>50% of revenue) negatively affected long-term viability (HR = 2.18, p = 0.002). Participation in networks increased three-year survival rates from 69.8% to 87.2%. Six key sustainability strategies were identified: hybrid revenue models, integration into the value chain, community inclusion, adaptive leadership, strategic partnerships, and effective communication of results and impact. The findings confirm the absence of an integrated support framework for the sustainable activities of the social economy and, in some cases, the limited capacity of public institutions to support vulnerable groups. Policy recommendations include phased funding mechanisms, transitional support instruments and the systematic development of regional ecosystems.

Abstract: Human Resource Analytics (HRA) promises to improve decision-making, workforce planning, and organisational performance through data-driven insights (Isson & Harriott, 2016; Marler & Boudreau, 2017; Minbaeva, 2021; McCartney & Fu, 2022a[M1.1]). Yet, despite growing interest in people analytics, many organisations still struggle to embed HRA into strategic and operational decision processes in ways that support innovation, effective governance, and long-term organisational sustainability. This article examines strategic misalignment as a critical but underexplored barrier to the adoption of HRA in the airline industry. Drawing on a qualitative study based on semi-structured interviews with 15 professionals connected to Portugal’s commercial aviation sector—including Experts in AI (n = 5), HR/Airline Professionals (n = 4), and HR/Airline Executives (n = 6)—the paper shows that HRA is constrained not merely by technical limitations but by the weak strategic positioning of HR itself and by governance arrangements that fail to integrate people-related evidence into executive decision-making. The findings indicate three interrelated barriers: the marginal role of HR in strategic decision-making, fragmented data and cross-functional silos, and inconsistent executive sponsorship for analytics-driven people management. These barriers reduce the practical value of analytics initiatives, weaken the governance of workforce-related decisions, and confine HRA to descriptive reporting rather than strategic intervention. The study contributes to the literature by reframing strategic alignment not as a secondary success factor, but as a prerequisite for meaningful HRA implementation and for building sustainable organisations able to connect workforce capability, operational resilience, and business value. Practical implications are discussed for organisations seeking to strengthen digital HR transformation in highly regulated and operationally complex sectors.

Abstract: This study examines how family background shapes individual occupational status within a behavioral science framework, using pooled data from the 2018 and 2020 waves of the China Family Panel Studies (CFPS). Grounded in New Human Capital Theory, it further investigates the moderating roles of cognitive and non-cognitive abilities in this relationship. The results indicate that family background exerts a significant and persistent positive effect on both initial and current occupational status, suggesting the enduring influence of intergenerational advantage. Robustness checks using alternative indicators, including father’s occupational status and mother’s education, confirm the stability of the findings. In addition, digital skills, appearance investment, and selected Big Five personality traits—agreeableness, openness, and conscientiousness—significantly strengthen the positive association between family background and occupational outcomes. These findings suggest that, beyond structural advantages, individual behavioral and psychological characteristics play a critical role in enabling individuals to effectively transform family resources into labor market success. Overall, the study provides empirical evidence on how behavioral factors interact with family background to shape occupational inequality in contemporary China.

Abstract: Purpose – This article aimed to offer insight into and discuss how the concepts of Industry 5.0 and Society 5.0 are perceived and understood by managers in the Norwegian construction industry. The research questions were limited to the perceptions and opinions of a group of bachelor's students in construction site management. Design/methodology/approach – The study used qualitative data collection, encompassing participants with different functions and experiences in the Norwegian construction industry. The student group was thus interdisciplinary. Everyone was a part-time student and had a full job at the same time. The participants represented two classes, with a total of 70 students divided into 15 work/study groups. Findings – The empirical evidence shows that the groups had insight into the concepts of Industry 5.0 and Society 5.0. They reflected on opportunities and obstacles. A transition to Industry 5.0 and Society 5.0 will require a focus on competence and self-directed learning, as well as a willingness to invest in competence and technology. This can be seen in light of a knowledge-intensive society and sustainable development. The participants emphasised the Norwegian working life model as a strength in the possible implementation of Industry 5.0 as it has several similarities with the concept of Industry 5.0 in terms of being human-centred. Originality/value – The article contributes insights into how the concepts of Society 5.0 and Industry 5.0 are perceived and understood by bachelor's students in construction site management. The study provides an in-depth analysis of the concept of resilience and the sub-concepts of vulnerability and capacity in a Norwegian context. Practical implications – The practical impact of the study can be linked to the students' participation as both informants and in assisting analysis of the empirical material, which has given them a foundation to communicate the topic of Industry 5.0 and Society 5.0 in their workplaces and other forums in which they participate as leaders in the construction industry.

Abstract: Digital transformation represents a critical challenge for contemporary organizations, yet substantial variation persists in their ability to successfully implement digital initi-atives. This study examines whether digital leadership acts as a key enabling factor by shaping the organizational mechanisms through which transformation is realized. Drawing on leadership theory, innovation climate research, and the dynamic capabili-ties perspective, the study develops and tests a structural model linking Digital Vision Leadership, Innovation Climate, Digital Capability Development, Technology Integra-tion, and Digital Transformation Outcomes. Data from 2,901 respondents were ana-lyzed using structural equation modeling. The results show that Digital Vision Lead-ership significantly influences both Innovation Climate and Digital Capability Devel-opment, while Innovation Climate enables capability development and technology in-tegration. Technology Integration emerges as the primary driver of transformation outcomes, supported by additional direct effects of capabilities and innovation climate. Notably, the direct effect of Digital Capability Development on Technology Integration is not supported, indicating that capabilities require enabling organizational condi-tions to be effectively deployed. The findings demonstrate that digital transformation is not driven by capabilities or technology alone, but by a structured sequence of or-ganizational mechanisms in which leadership and innovation climate determine whether capabilities translate into technology integration. The study contributes by advancing a process-based model of digital transformation and clarifying why digital capabilities alone do not ensure successful technology implementation.

Abstract: Employee well-being has become a central concern in organizational research due to its strong implications for performance, job satisfaction, and organizational sustainability (Bakker & Demerouti, 2007; Schaufeli & Taris, 2014). In high-pressure sectors such as banking and microfinance, managers operate under strict regulatory requirements, demanding performance targets, and continuous monitoring, which may significantly affect their psychological well-being (Giorgi et al., 2017; Lee & Kim, 2023). Managerial well-being is particularly important because managers are responsible not only for achieving organizational objectives but also for supervising employees and maintaining operational stability. These challenges are especially relevant in emerging financial systems such as Albania’s, where the financial sector is largely lending-oriented and dominated by commercial banks, with microfinance institutions playing a complementary role in expanding access to finance (Bank of Albania, 2025; World Bank, 2020). Managers in these institutions face pressures related to regulatory compliance, performance expectations, and the responsibility of supporting credit access for households and SMEs. This study investigates the determinants of managers’ well-being in Albanian lending institutions using the Job Demands–Resources (JD-R) model (Bakker & Demerouti, 2007). It examines how job demands (e.g., workload, performance pressure), job resources (e.g., organizational support, autonomy), and work–family conflict influence managerial well-being. The study also explores whether significant differences in well-being exist across demographic characteristics such as gender, age, type of institution, position, years of service, and number of supervised employees.

Abstract: Application Tracking Systems (ATS) have evolved significantly since their inception in 1996, transitioning from simple resumé repositories to AI-driven tools with advanced capabilities. Although these innovations have improved recruitment efficiency, they have also introduced significant ethical and Human Rights challenges. Bias in machine learning (ML) training data and over reliance on algorithmic decision making have led to violations of Human dignity, equality, privacy, and other fundamental rights. This study examines these challenges and proposes a Human-centered approach to recruitment processes that integrates ATS with ethical safeguards. The proposed methodology involves the development of a Humanization application service to mitigate bias and enhance Human oversight. Key features include validating job vacancy requirements, identifying and addressing bias triggers in recruitment algorithms, and requiring digital signatures from qualified professionals to approve job postings, ensuring that there are humans that assume responsibility. By incorporating generative AI and blockchain, this system facilitates compliance, transparency, and fairness in recruitment, thereby addressing the ethical concerns of algorithmic hiring. Crucially, this study demonstrates that organizations can achieve meaningful Humanization of their recruitment processes, including the mitigation of bias and provision of personalized feedback (among many other potential steps) through targeted interventions that require surprisingly modest financial investment, time commitment, and computational resources. This study underscores the importance of combining technological advancements with ethical considerations to create equitable recruitment processes in an accessible and resource-efficient manner.

Abstract: The shift to remote and hybrid work has exposed the limitations of traditional performance management systems, which often rely on physical presence or intrusive surveillance rather than outcome-based evaluation. This paper asks how AI-driven performance management can be designed to address the documented challenges of teleworking while safeguarding employee autonomy, fairness, and well-being. The study integrates a comprehensive literature review on AI capabilities with empirical evidence from a sequential mixed-methods study of Canadian public servants, comprising machine learning analysis of over 205,000 tweets, document analysis of federal and provincial teleworking policies, a survey of 176 public servants analyzed using logistic regression, and semi-structured interviews with Government of Canada employees. Grounded in socio-technical theory and the Theory of Planned Behavior, the findings reveal that organizational support, workplace socialization, and attitudes are stronger predictors of teleworking success than digital skills or monitoring, while isolation functions as a measurable risk factor. These empirical patterns are mapped to specific AI capabilities to produce a socio-technical framework organized around three interdependent layers: technological, organizational, and human-centered. The paper contributes an empirically grounded alternative to purely speculative treatments of AI in performance management, offering design requirements derived from what remote workers actually experience rather than from technological possibilities alone.