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The Eastasouth Management and Business
Published by Eastasouth Institute
ISSN : 29857120     EISSN : 29633591     DOI : https://doi.org/10.58812/esmb
Core Subject : Science,
Decision Sciences, Operations Research & Management
ESMB - The Eastasouth Management and Business is a peer-reviewed journal and open access three times a year (March, July and November) published by Eastasouth Institute. ESMB aims to publish articles in the field of Strategic management, Operations management, Marketing and Sales, Supply chain and logistics, Human resource management, Leadership, and organization management, International business, Sustainable business, Information technology management, Risk and security management, Business ethics and corporate social responsibility. ESMB accepts manuscripts of both quantitative and qualitative research. ESMB publishes papers: 1) review papers, 2) basic research papers, and 3) case study papers.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 184 Documents
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A Comprehensive Financial and Organizational Analysis of Telerehabilitation Business Models for Sustainable Growth and Market Expansion in the Healthcare Sector Dhirenbhai Kalal
The Eastasouth Management and Business Vol. 2 No. 03 (2024): The Eastasouth Management and Business (ESMB)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esmb.v2i03.1143

Abstract

This shift marked the end of the pandemic era, where telerehabilitation was merely an emergency measure, and the beginning of a new growth trajectory for digital health, with the global market estimated at USD 5.32 billion in 2024 and projected to grow to USD 11.81 billion by 2030 at a CAGR of 13.2 per cent. However, the financial and organisational basis of this growth is poorly documented, to varying degrees, in the different clinical indications. This paper presents a financial and organisational evaluation of fourteen peer-reviewed and industry-based sources to create a holistic view of business models for telerehabilitation. Evidence is presented under three themes: Business model frameworks in digital health, Health-economic evidence for telerehabilitation, and Clinical and organisational implementation. Results found that per-patient savings ranged from USD 565.66 to USD 2,352.00, with four of eight studies showing moderate results for combined neurological and cardiological populations; per-patient savings were found to be favourable, with ninety-two per cent of reviewed cardiac studies showing favourable results for protocolized, exercise-based cardiac interventions; and results were least consistent for heterogeneous musculoskeletal indications. Financial sustainability of telerehabilitation businesses was identified through business model syntheses as having common elements such as diversified revenue streams, partnerships with payers and with technology vendors, and adaptive governance. Analysis shows that rather than a common telerehabilitation approach, business model design is the most defendable path to sustainable market expansion.
A Strategic Operations Management Framework for Enhancing Service Efficiency, Therapist Productivity, and Patient Flow Optimization in Outpatient Physical Therapy Clinics Dhirenbhai Kalal
The Eastasouth Management and Business Vol. 2 No. 02 (2024): The Eastasouth Management and Business (ESMB)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esmb.v2i02.1144

Abstract

Outpatient Physical Therapy (OPT) clinics are facing increasing pressure to balance patient demand, strict therapist staffing levels, patient non-attendance and productivity demands dictated by reimbursement requirements. This paper brings together results from twenty peer-reviewed and thesis-level papers covering healthcare scheduling optimization, physical therapist productivity measurement, patient no-show prediction, and lean process redesign to present an integrated Strategic Operations Management Framework for outpatient physical therapy environments. It combines a predictive scheduling optimization system with a real-time capacity allocation system for therapists and a lean-based patient-flow monitoring loop, based on the evidence gained from a discrete-event simulation and mathematical programming. Synthesized results show that a simulation-optimization scheduling approach can increase therapist utilisation to around 91 per cent and decrease the incidence of no shows up to 27 per cent over rule-based block scheduling, and lean healthcare interventions can lead to a median decrease in patient waiting time by 31 per cent and process cycle time by 26 per cent. Productivity indices that have been created over the past 40 years from departmental evaluations reveal a cumulative increase of about 58 percent, while documented risks of clinician burnout have occurred when trying to increase productivity without workforce protections. This proposed framework is divided into four interacting zones: predictive scheduling, lean process redesign, dynamic capacity management and workforce well-being, and provides a staged implementation roadmap. Limitations associated with the retrospective and cross setting nature of the synthesized evidence are discussed, as are implications for clinic administrators, payers, and workforce policy.
Semantic AI-Orchestrated Cross-Domain Automation Framework for Sustainable Smart Factories Milan Bharatkumar Makwana
The Eastasouth Management and Business Vol. 3 No. 02 (2025): The Eastasouth Management and Business (ESMB)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esmb.v3i02.1145

Abstract

Manufacturing sectors pursuing Industry 5.0 objectives increasingly require automation architectures capable of reasoning across heterogeneous cyber-physical domains while advancing sustainability targets. This paper synthesizes evidence from eighteen references spanning semantic web technologies, cyber-physical systems, digital twins, blockchain-enabled traceability, and multi-agent reinforcement learning to propose a Semantic AI-Orchestrated Cross-Domain Automation Framework for sustainable smart factories. The framework integrates a five-layer architecture, comprising physical sensing, cyber-physical integration, semantic reasoning, cross-domain orchestration, and sustainability decision layers, into a unified reasoning pipeline in which ontology-driven knowledge graphs mediate interoperability among heterogeneous equipment, enterprise systems, and human operators. Comparative synthesis indicates that semantic-based autonomous computing architectures reduce unplanned downtime by as much as 37 percent, while multi-agent reinforcement learning scheduling raises resource utilization to 88 percent relative to 58 percent under conventional rule-based scheduling. Interoperability standards such as OPC-UA demonstrate adoption rates near 78 percent among reviewed implementations, and hybrid semantic-blockchain ledgers achieve transaction throughput exceeding 2,100 transactions per second at latencies below 40 seconds, outperforming public proof-of-work ledgers by more than two orders of magnitude. Digital twin adoption trajectories synthesized from the references rose from approximately 8 percent in 2016 to 66 percent by 2024, correlating with a 24 percent reduction in energy consumption and a 31 percent reduction in material waste across reviewed sustainable manufacturing cases. The findings imply that semantic orchestration, combined with decentralized ledgers and human-centric digital twins, offers a scalable pathway toward resilient, low-carbon, and economically viable smart factory operations, while highlighting persistent challenges in ontology standardization, explainability, and cross-organizational governance.
Causality-Preserving Distributed Decision Fabrics for AI-Native Financial Enterprise Architectures Nithesh Gudipuri
The Eastasouth Management and Business Vol. 1 No. 03 (2023): The Eastasouth Management and Business (ESMB)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esmb.v1i03.1169

Abstract

Today, financial enterprise architectures are increasingly incorporating artificial intelligence (AI) capabilities into distributed transaction-processing systems, creating a tension between the need for rapid service availability and the need for a causally coherent audit trail of AI-made decisions. In this paper, we marshal research on causal consistency models, causal inference, explainable AI (XAI), and blockchain-based financial infrastructure to propose a conceptual framework called the causality-preserving distributed decision fabric. Causal consistency, which is formalized in causal-memory and session-guarantee models, is explored as a compromise between the high availability of eventual consistency and the coordination cost of linearizability, which is limited by the CAP theorem. Methods for causal inference and model-agnostic explainability, such as Shapley-value attribution and local surrogate modeling, are examined as ways to make automated financial decisions interpretable to those who manage the risks in financial institutions and regulators. Distributed ledger architectures are viewed as an audit trail that can track and order AI-backed decisions between organizational lines. The synthesis suggests that none of the single mechanisms alone meet the simultaneous requirements of availability, explainability, and auditability; thus, a layered architecture of causal-consistency protocols, an explainability layer, and a permissioned ledger is proposed. Comparisons on a conceptual level regarding consistency models and explainability methods, as well as architectural diagrams depicting the proposed layering, are presented. The findings suggest that maintaining causality is a key prerequisite for trustworthy AI-native financial systems, but that interoperability and computational load are major obstacles to implementation.

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