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Purpose

This study aims to explore how work-applied management (WAM) tools can enhance organizational readiness for hospital accreditation in Indonesia. It focuses on how human resource learning, standard operating procedures (SOPs) and governance reform act as practical pathways for organizational change in resource-limited Class D hospitals.

Design/methodology/approach

A qualitative-dominant embedded mixed-method case study was employed, adapting classical strategic tools (strengths, weaknesses, opportunities and threats (SWOT), internal–external (IE) matrix and quantitative strategic planning matrix (QSPM)) into a work-applied strategic mapping (WASM) framework. This reframing positions the tools as both diagnostic and reflective learning devices that engage hospital managers and staff in the strategy-to-practice process. Data were collected through interviews with 9 key informants, document analysis, field observations, a questionnaire survey of 40 hospital staff and analytic hierarchy process (AHP)-supported strategic prioritization.

Findings

The WASM analysis identified that human resource training and SOP standardization are central to building accreditation readiness, while governance reform strengthens accountability and sustainability. Therefore, accreditation readiness in Class-D hospitals is less about large-scale technological investment and more about embedding work-applied organizational learning into daily practice, thereby extending existing evidence on organizational readiness through work-applied strategic mapping and the participatory implementation of strategies.

Practical implications

This study demonstrates how work-applied strategic mapping can translate strategy into workplace learning, supporting hospital leaders, managers, healthcare staff and accreditation assessors in aligning limited resources with accreditation requirements.

Originality/value

This study uses the WAM literature by operationalizing and reframing SWOT, IE, QSPM and AHP as reflective organizational-learning mechanisms. It provides empirical evidence from the underexplored context of Indonesian Class D hospitals, offering a practice-based perspective on how applied management tools can foster workplace changes and improve future accreditation readiness.

Hospital accreditation has become a key mechanism for improving healthcare quality, patient safety and institutional governance across health systems (Endalamaw et al., 2024; Karami et al., 2023). Beyond regulatory compliance, accreditation increasingly functions as an organizational learning process that supports professional development and continuous quality improvement, particularly in low- and middle-income countries (LMICs). However, hospitals frequently face infrastructure, workforce and governance constraints that limit accreditation to compliance rather than sustained improvement (Seyghalani Talab et al., 2024).

In Indonesia, hospital accreditation is mandated by the Ministry of Health and implemented through the Hospital Accreditation Commission (Komisi Akreditasi Rumah Sakit/KARS) as part of national universal health coverage (UHC) reforms. Of the more than 2,900 hospitals nationwide, over 70% are classified as Class C or D facilities (Komisi Akreditasi Rumah Sakit [KARS], 2023). These hospitals form the backbone of healthcare delivery in peri-urban and rural areas. Despite their central role in the health system, many Class D hospitals face difficulties in meeting higher accreditation standards owing to limited financial autonomy, managerial capacity constraints and workforce shortages (Maheswara, 2024; Sari et al., 2023).

This structural imbalance is reflected in the national hospital landscape. As illustrated in Figures 1 and 2, Class C and Class D hospitals dominate Indonesia's healthcare system, highlighting the need to strengthen accreditation readiness in resource-limited settings.

Previous accreditation studies in Indonesia and comparable LMIC settings have primarily focused on regulatory compliance, technical implementation, infrastructure readiness and quality assurance (Pourmohammadi et al., 2020; Nyokabi and Hilda, 2025). However, limited attention has been given to how strategic management tools are translated into everyday organizational learning and managerial practice in resource-constrained hospitals, where accreditation readiness depends on coordinated capabilities across macro-level regulation, meso-level governance and micro-level clinical practice (Weiner, 2009; Teece, 2014).

Systematic reviews suggest that accreditation is most effective when supported by organizational culture, leadership, workforce development and continuous learning (Alhawajreh et al., 2023, 2025; Gurisch et al., 2024). However, sustainability remains a challenge. Accreditation gains may diminish over time without continuous governance reinforcement and monitoring (Hussein, 2025). Evidence from repeated accreditation surveys indicates that sustaining accreditation depends on continuous organizational learning, governance reinforcement and workforce capability (Devkaran et al., 2019).

These challenges highlight the need for approaches that connect accreditation standards with everyday management and clinical practice. Work-applied management (WAM) directly addresses this gap by emphasizing learning through practice, reflection and action within everyday organizational settings (Pederzini, 2019). Recent Journal of Work Applied Management (JWAM) studies similarly emphasize the roles of institutional leadership, workforce readiness and adaptive learning ecosystems in organizational change (Butt, 2024; Bryant, 2024; Wolek Rocha, 2024).

Drawing on this perspective, this study examines how WAM tools can support hospital accreditation readiness in a resource-limited setting. Using a qualitative case study conducted in a Class D hospital in Central Java, the study reframes classical strategic management tools and analysis, the internal–external (IE) matrix and the quantitative strategic planning matrix (QSPM) – as reflective organizational-learning mechanisms embedded in daily managerial practice. Rather than functioning solely as analytical instruments, these tools are used as reflective organizational learning mechanisms in accreditation practice that support sense-making, prioritization and collective learning among hospital leaders and staff members. Accordingly, this study contributes to the WAM literature by demonstrating how established strategic management tools can be reframed as reflective organizational-learning mechanisms that connect strategic analysis with everyday managerial practice during accreditation preparation in a resource-constrained Indonesian Class D hospital.

This study adapts and reframes classical strategic tools into a work-applied learning cycle (WALC) that helps managers align accreditation standards with everyday managerial practice and operationalize readiness as an iterative organizational-learning process.

While the framework shares participatory elements with action research and strategy-as-practice (Jarzabkowski and Spee, 2009), its contribution is not to develop a new strategic theory but to demonstrate how established strategic tools (SWOT, IE Matrix and QSPM) can be operationalized through the sequence of the work-applied strategy model (WASM), organizational position mapping (OPM) and strategic prioritization grid (SPG) as reflective organizational-learning mechanisms that connect strategic analysis with everyday managerial practice during accreditation preparations.

Hospital accreditation has been increasingly adopted as a key mechanism for improving healthcare quality, patient safety and organizational accountability in LMICs. It functions as both a regulatory instrument and a quality improvement mechanism by establishing standardized benchmarks for clinical governance and service delivery (Mansour et al., 2020).

The sustainability of accreditation systems in LMICs is shaped by institutional governance, regulatory frameworks, financial capacity and professional capability. A scoping review by Dharmagunawardene et al. (2025) proposed the ACES-GLEAM framework (antecedent influences, contextual factors, establishment factors, standards, surveyors, stimulants, survey-related factors, governance, legislation, execution and assessment and monitoring) to explain the macro-level conditions influencing accreditation programs, highlighting the importance of governance stability, legal frameworks, financing structures and monitoring mechanisms. However, relatively little attention has been paid to how hospital managers and clinical staff translate accreditation standards into everyday organizational practice.

Organizational readiness refers to the extent to which organizational members are psychologically and operationally prepared to implement new practices (Weiner, 2009). In the context of hospital accreditation, readiness involves multiple dimensions, including staff competence, leadership commitment, infrastructure availability and standardized operational procedures. Research on healthcare workers' readiness for accreditation-related changes shows that staff engagement, training and a shared understanding of quality standards are critical for successful implementation (Andriana et al., 2025). Without sufficient readiness, accreditation risks becoming a documentation exercise rather than a process of organizational learning and improvement.

Strategic management frameworks are increasingly being applied in healthcare organizations to support decision-making, organizational development and service improvement. Analytical tools such as SWOT analysis, the IE matrix and the QSPM are commonly used to identify organizational strengths and weaknesses, evaluate external opportunities and threats and prioritize strategic initiatives.

These tools are generally considered analytical instruments rather than mechanisms for organizational learning. The application of these tools can be interpreted from the perspectives of organizational readiness and dynamic capabilities (Barney, 1991; Teece et al., 2018). However, limited research has examined how established strategic management tools can be operationalized and reframed as reflective organizational-learning mechanisms that facilitate collective learning and accreditation readiness in resource-constrained healthcare organizations. This perspective underpins the present study by linking strategic analysis with participatory learning embedded in everyday managerial practice.

In Indonesia, hospital accreditation plays a central role in ensuring healthcare quality and accountability within the national health system. The accreditation process is administered by the Hospital Accreditation Commission (KARS) and is an integral part of healthcare governance in Indonesia. Hospitals are required to meet standardized criteria for patient safety, clinical governance, quality management and service delivery.

The Ministry of Health Regulation No. 1128 of 2022 further strengthens these requirements by emphasizing quality improvement, patient safety and standardized operational procedures. Despite these regulatory developments, many hospitals, particularly smaller regional hospitals classified as Class D institutions, continue to face challenges in achieving accreditation readiness. Resource limitations, staffing shortages and managerial capacity constraints often hinder the effective implementation of accreditation standards. This highlights the need for WAM approaches that translate strategic planning tools into reflective organizational learning mechanisms that support accreditation readiness.

This study adopts a WAM approach that integrates strategy formulation with everyday organizational learning (Pederzini, 2019; Bryant, 2024). Within this orientation, managers and professionals collaboratively diagnose organizational challenges and interpret strategic information to support accreditation practices under resource constraints (Butt, 2024; Quigley, 2023; Wolek Rocha, 2024). Accordingly, accreditation readiness is conceptualized as an evolving organizational capability rather than a static compliance outcome. Therefore, strategic tools are used to support reflective learning, dialogs and collective decision-making.

This study employed a qualitative-dominant embedded mixed-method case study design grounded in an interpretive work-applied orientation that integrates participatory qualitative inquiry with structured strategic analysis (Creswell and Plano Clark, 2017). The empirical setting is a private Class D hospital in Central Java, Indonesia, mandated to progress toward higher accreditation standards under the national accreditation framework (KARS, 2018; Maheswara, 2024).

The analysis follows David et al.'s (2023) three-stage strategy formulation model: input, matching and decision, operationalized within a work-applied-learning framework. The input stage was implemented through WASM, which was adapted from the SWOT analysis to identify internal and external accreditation-related factors. The matching stage was conducted using the OPM, adapted from the IE matrix, to interpret organizational readiness and strategic posture. The decision stage was implemented through a strategic prioritization grid (SPG), adapted from the QSPM to prioritize strategic actions through participatory evaluation. These applications embedded classical strategic tools within reflective dialogs rather than being applied as purely linear planning instruments (Bryant, 2024).

The study site was a private Class D hospital in Central Java serving peri-urban populations that are largely dependent on the national health insurance system (BPJS Kesehatan). The hospital faces the typical constraints of lower-tier facilities, including workforce shortages, limited infrastructure and evolving governance arrangements (Sari et al., 2023; Bergholt et al., 2021; Gurisch et al., 2024; Hussein, 2025). The institution has 59 inpatient beds and provides emergency, inpatient and outpatient services with a workforce of 12 specialist physicians, 10 general practitioners and approximately 128 staff members. These conditions make it a relevant setting for examining accreditation readiness in resource-constrained hospitals in Indonesia.

This study adopts a single-case study design to enable an in-depth examination of accreditation readiness within a real organizational context. Case study research is appropriate for investigating complex organizational processes embedded in specific institutional environments (Yin, 2018). Following Yin's (2018) logic of analytical generalization, the aim was to generate contextual and theoretical insights into accreditation readiness processes rather than statistical representativeness.

Participants were recruited using purposive sampling to include organizational actors directly involved in accreditation activities (Denzin and Lincoln, 2018). Two participant groups were included in this study. The qualitative component involved a hospital director, departmental managers, administrative staff and a KARS accreditation assessor (n = 9). In addition, the quantitative component included 40 hospital staff members who completed a structured questionnaire to assess organizational readiness across the study domains. These participants were purposively selected because they were directly involved in the accreditation preparation and strategic decision-making processes. Within the WAM orientation, participants were treated as reflective practitioners and co-learners who contributed not only data but also role-specific interpretations and validations of the strategic findings according to their organizational responsibilities (Wolek Rocha, 2024).

Data collection employed methodological triangulation using four complementary sources of evidence: (1) qualitative interviews with nine key informants involved in accreditation preparation, (2) a structured questionnaire survey administered to 40 hospital staff members, (3) document analysis and (4) KARS field observations.

Accreditation readiness was operationalized using strategic domains derived from the accreditation and organizational readiness literature and the national accreditation standards. Table 1 summarizes the domains, indicators, data sources and measurement approaches used in this study.

This study adopts a qualitative-dominant embedded mixed-method design, in which qualitative inquiry forms the primary analytical foundation and quantitative elements support structured strategic assessment (Creswell and Plano Clark, 2017). Qualitative findings from interviews, observations and document analysis informed the WASM stage, while questionnaire data supported factor weighting in the Internal factor evaluation (IFE)/external factor evaluation (EFE) matrices and the SPG. The integration grounded quantitative outputs in qualitative practitioner interpretations, strengthening methodological coherence and interpretation.

Data analysis followed the WASM–OPM–SPG sequence. IFE and EFE matrices were used to quantify the relative strengths of the internal and external factors identified during the WASM stage. Qualitative interview data were analyzed using thematic analysis following Braun and Clarke (2006), with themes refined through practitioner validation.

Methodological rigor was strengthened through the triangulation of interviews, observations, questionnaires and document analysis to enhance credibility. Reflective practitioner validation supported confirmability, documentary records provided an audit trail for dependability and analytical generalization supported the transferability of the findings (Lincoln and Guba, 1985; Yin, 2018).

To support structured decision-making, factor weights were refined using the analytic hierarchy process (AHP) following Saaty's (2008) pairwise comparison method. Strategic factors derived from the WASM stage were evaluated through independently conducted pairwise comparisons by nine experts, including the hospital director, departmental managers and a KARS accreditation assessor, and were aggregated using geometric means. Differences in judgments were discussed during reflective validation sessions to ensure shared strategic priorities. Priority weights were calculated using eigenvector normalization, and consistency ratios (CR) below 0.10 were considered acceptable for judgment reliability (Saaty, 2008; Ho, 2008; Park et al., 2023). The resulting weights were used in the strategic prioritization grid through reflective practitioner validation. The detailed pairwise matrices and consistency calculations are presented in Appendix A2.

Ethical approval was obtained from the Institutional Ethics Committee. All participants provided informed consent, and confidentiality was maintained in accordance with ethical standards for healthcare and management research (Kelly et al., 2023; Nicklin, 2021).

The methodological framework incorporates a WALC that integrates iterative reflection across analytical stages (Pederzini, 2019; Bryant, 2024). The cycle links the WASM, OPM and SPG stages into a continuous process of collaborative analysis, strategic prioritization and reflective learning during accreditation preparation. This structure aligns with dynamic capabilities theory, particularly the processes of sensing accreditation gaps, seizing feasible strategic priorities and reconfiguring organizational routines through standard operating procedure (SOP) adaptation and workforce learning (Teece et al., 2018) and organizational readiness theory (Weiner, 2009).

The analytical framework builds on David’s et al. (2023) three-stage strategy formulation model and adapts it into three work-applied stages: strategic mapping, organizational positioning and strategic prioritization. The framework conceptualizes strategy formulation as an iterative learning process that is embedded in everyday managerial practice (Pederzini, 2019; Bryant, 2024; Wolek Rocha, 2024).

Table 2 summarizes the operationalization of the WASM, OPM and SPG stages and their theoretical foundations, drawing on dynamic capabilities (Teece et al., 2018), multicriteria decision-making through AHP (Saaty, 2008; Ho, 2008; Park et al., 2023) and continuous organizational learning for accreditation readiness (Bergholt et al., 2022; Hussein, 2025). Figure 3 illustrates their integration through the WALC model.

The analysis revealed a configuration of enablers and constraints that shaped accreditation readiness at the hospital. Internal enablers were primarily related to leadership commitment, staff motivation and opportunities for inter-organizational collaboration (see Table 3). In contrast, internal constraints were dominated by shortages of specialist clinicians, weak SOPs and underdeveloped health information systems.

Respondents highlighted inconsistent SOP implementation and the need for training to improve accreditation compliance, aligning with interviews and documented evidence identifying weak procedural standardization and limited capacity-building initiatives as key internal constraints. National accreditation policies and the Jaminan Kesehatan Nasional (JKN) scheme provide enabling conditions by ensuring a stable patient base and regulatory support. Simultaneously, competition from private hospitals, stricter accreditation standards and rising patient expectations create significant constraints for public hospitals. Practitioners interpreted these findings as indicating that human resource capacity and SOP standardization represent the most critical accreditation readiness gaps.

The relative importance of the WASM factors was further examined using internal (IFE) and EFE matrices (see Table 4). The IFE score of 2.37 indicates moderate internal readiness, suggesting that existing strengths are present but are not sufficiently robust to fully support accreditation advancement. Weaknesses related to specialist availability, facilities, SOP implementation and information systems exerted a substantial downward influence on the hospital's internal score.

The EFE results in Table 5 yield a score of 2.60, reflecting moderate external opportunities. Government support mechanisms and the JKN scheme provide meaningful leverage, although they are partially offset by regulatory complexity and competitive pressure. Together, these findings indicate moderate internal readiness within a supportive external environment.

Plotting the IFE and EFE scores in the OPM positioned the hospital within the balanced readiness (hold and maintain) quadrant (Figure 4). This quadrant represents organizations with moderate internal and external readiness, where consolidation and selective improvement are more appropriate than aggressive expansion strategies. Stakeholder discussions involving hospital leaders, managers and clinical and administrative staff emphasized strengthening human resources and improving SOP compliance as feasible actions directly linked to accreditation outcomes. This incremental approach is consistent with the evidence from resource-limited healthcare settings (Uggerby et al., 2021).

The final stage focuses on prioritizing strategies to enhance accreditation's readiness. Based on the hospital's position in the balanced readiness quadrant, strategic alternatives were evaluated using the strategic prioritization grid (SPG) (see Table 6).

Human resource training combined with SOP standardization was identified as the highest-priority strategy (SPI = 2.892), followed by governance reform (SPI = 2.130). Facility improvement and information technology (IT) system strengthening were given lower priority. This prioritization reflects the reflective practitioner judgment within the hospital's Hold and Maintain position. Reflective discussions during the SPG stage shifted the prioritization from infrastructure expansion to human resources (HR) training and SOP standardization, as participants collectively interpreted these strategies as more feasible under existing resource constraints. As one senior manager noted, “Accreditation readiness begins with competent staff and clear processes; without these, infrastructure and IT systems will not make a difference.” This view aligns with evidence that sustainable accreditation outcomes in resource-constrained hospitals primarily depend on human capital development and process standardization (Hussein, 2025; Kelly et al., 2023).

The prioritization process maintained coherence across the WASM–OPM–SPG sequence through reflective-practitioner validation. Strategic choices were grounded in earlier mappings of organizational enablers and constraints, with learning weights from the WASM stage carried forward into the SPG to maintain coherence across the analytical stages. This sequence illustrates how the WASM–OPM–SPG stages function as iterative organizational learning cycles linking strategic diagnosis, interpretation and prioritization.

4.4.1 AHP-based weight derivation

To enhance methodological transparency, the learning weights in the SPG were derived using the AHP (Saaty, 2008). The strategic factors identified during the WASM stage were evaluated through pairwise comparisons conducted by hospital executives, clinical managers and accreditation assessors. Eigenvector normalization produced priority weights, and CR below 0.10 indicates acceptable reliability (Ishizaka and Labib, 2011). The detailed matrices are presented in Appendix A2.

This study extends the existing accreditation readiness literature by conceptualizing readiness as an applied organizational learning process through everyday managerial and clinical work. By integrating the WASM–IFE/EFE–OPM–SPG sequence into the WALC, established strategic management tools are reframed as reflective organizational learning mechanisms that support accreditation readiness. This case illustrates how accreditation readiness emerges through gradual organizational consolidation, even under resource constraints. Although leadership commitment and policy support provide the initial foundation, constraints related to human resources, SOP compliance and infrastructure continue to limit readiness.

These findings support the evidence that accreditation outcomes are strengthened through incremental organizational learning. Evidence from accreditation reforms indicates that improvements in patient safety and service quality emerge when internal processes gradually align with external standards rather than when accreditation is treated as a one-off compliance exercise (Bergholt et al., 2021, 2022; Uggerby et al., 2021). Unlike previous studies that primarily evaluate accreditation outcomes, this study explains how organizational readiness can be operationalized through participatory strategic management tools embedded within routine organizational practice and continuous work-applied learning.

From a WAM perspective, strategic diagnosis should move beyond static SWOT analyses that are not detached from practice. In this study, the WASM, IFE/EFE and OPM enabled practitioners to collectively interpret readiness gaps and improvement priorities. Rather than functioning solely as analytical instruments, these strategic tools were reframed as reflective organizational learning mechanisms that facilitated collective sense-making, dialog, shared interpretation and adaptive decision-making throughout the accreditation process.

A central reflection concerns the primacy of human capital and process standardization in accreditation preparedness. The findings suggest that accreditation readiness depends primarily on the institutionalization of workforce learning and procedural coordination rather than on resource-intensive expansion. This finding aligns with evidence reported in several resource-constrained healthcare settings, where accreditation sustainability depends heavily on workforce capability and process standardization (Hussein, 2025; Kelly et al., 2023). In this context, SOP standardization functions not only as a compliance mechanism but also as an organizational reconfiguration capability that stabilizes routines, supports coordination and enables continuous adaptation during accreditation preparation. From a theoretical perspective, this supports organizational readiness and dynamic capabilities theory by emphasizing workforce capability, process adaptation and reconfiguration of existing resources under contextual constraints (Teece et al., 2018).

From a dynamic capabilities perspective, the framework reflects the processes of sensing (identifying accreditation readiness gaps), seizing (prioritizing HR and governance strategies) and reconfiguring (embedding SOP routines and workforce learning into organizational practices) (Teece et al., 2018). These findings extend dynamic capabilities by illustrating how learning routines support strategic adaptation in resource-constrained settings.

The hospital's hold and maintain position underscores the relevance of incremental strategies in resource-constrained settings. Accordingly, the hospital prioritized workforce capability, governance and SOP compliance over resource-intensive expansions. This approach aligns with the organizational readiness theory. Consistent with Weiner (2009) and Holt et al. (2007), the findings suggest that shared readiness develops through iterative strategic reflection, participatory learning and procedural stabilization embedded in everyday organizational practices. In this sense, accreditation readiness emerges not as an individual managerial attribute but as a collectively constructed organizational condition shaped through iterative learning, coordination and procedural stabilization across professional groups.

Methodologically, this study demonstrates that integrating qualitative inquiry with structured strategic management tools within the WALC provides a systematic approach for translating strategic analysis into organizational learning and accreditation readiness. The findings suggest that accreditation readiness should be viewed as an adaptive organizational learning process rather than merely a compliance-based administrative exercise. This orientation aligns with the ethos of WAM, emphasizing that strategy should be co-created and refined through iterative cycles of action and reflection (Pederzini, 2019; Bryant, 2024; Wolek-Rocha, 2024).

From a policy and managerial perspective, within the context of this case hospital, the findings highlight the importance of leadership that prioritizes organizational learning, workforce capability and process standardization. For hospital leaders, the framework provides a structured approach to diagnose readiness, prioritize actions and engage staff in continuous learning processes, thereby supporting improvements in service quality, UHC and sustainable development goals. Therefore, accreditation readiness should be viewed as a strategic organizational learning process rather than a compliance exercise.

This study examined hospital accreditation readiness in a resource-constrained setting by applying an integrated framework (WASM–OPM–SPG) supported by a WALC. The findings indicate that accreditation readiness depends primarily on strengthening workforce capability, governance and SOP implementation, rather than on infrastructure expansion. The hospital's position in the hold and maintain quadrant highlights the need for consolidation and incremental improvements rather than ambitious expansion. The prioritization results indicate that human resource development and SOP standardization are the most critical and feasible pathways for strengthening accreditation readiness, supported by reflective organizational learning embedded in everyday practice.

Conceptually, this study contributes to the WAM literature by demonstrating how established strategic management tools can be reframed as reflective organizational-learning mechanisms that support accreditation readiness through everyday managerial practice. This is supported by reflective organizational learning embedded in everyday practice. The WALC provides a structured process linking diagnosis, collaboration, prioritization and reflection during accreditation preparation. Practically, the framework offers hospital managers and policymakers a structured yet context-sensitive approach to diagnose readiness and prioritize strategic actions under resource constraints. These findings support incremental accreditation strategies centered on workforce development and SOP standardization.

This study has several limitations. First, the study examined a single Class D hospital and therefore supports analytical rather than statistical generalization (Yin, 2018). Second, practitioner perspectives were context-specific. Third, although structured through AHP aggregation and reflective validation, the prioritization process remains partly sensitive to subjective judgments that are common in multicriteria decision-making. Future research should examine multiple hospitals using longitudinal designs to evaluate the sustainability of accreditation readiness across different organizational contexts and accreditation cycles.

R.R. conceptualized the study, designed the research framework and wrote the manuscript. F.A.R. contributed to the data collection, analysis and interpretation of the results. I.D.R. assisted with the literature review, drafted sections of the discussion and edited the manuscript. All authors have read and approved the final version of this manuscript.

The authors thank the hospital leadership, staff, accreditation assessors and local health office for their support and for providing access to relevant data and policy documents used in this study.

The supplementary material for this article can be found online.

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Published in Journal of Work-Applied Management. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at Link to the terms of the CC BY 4.0 licence.

Supplementary data

Data & Figures

Figure 1
A bar graph showing the distribution of Indonesian hospitals by accreditation-relevant classification.A horizontal bar graph compares the percentage of hospitals across different accreditation-relevant classifications. The horizontal axis represents the percentage of hospitals, ranging from 0 to 60 percent. The vertical axis lists the classifications: Class C, Class D, Class B, Class A, Class D Pratama, and Not Classified. The bars are colored differently for each classification: blue for Class C, green for Class D, teal for Class B, orange for Class A, pink for Class D Pratama, and purple for Not Classified. Class C has the highest percentage at 54.0 percent, followed by Class D at 27.3 percent, Class B at 13.9 percent, Class A at 2.4 percent, Class D Pratama at 2.2 percent, and Not Classified at 0.2 percent. The total number of hospitals is 3,216. Each bar is labeled with the exact percentage and the number of hospitals in that classification.

Distribution of Indonesian hospitals by accreditation-relevant classification. Source: Maheswara (2024) 

Figure 1
A bar graph showing the distribution of Indonesian hospitals by accreditation-relevant classification.A horizontal bar graph compares the percentage of hospitals across different accreditation-relevant classifications. The horizontal axis represents the percentage of hospitals, ranging from 0 to 60 percent. The vertical axis lists the classifications: Class C, Class D, Class B, Class A, Class D Pratama, and Not Classified. The bars are colored differently for each classification: blue for Class C, green for Class D, teal for Class B, orange for Class A, pink for Class D Pratama, and purple for Not Classified. Class C has the highest percentage at 54.0 percent, followed by Class D at 27.3 percent, Class B at 13.9 percent, Class A at 2.4 percent, Class D Pratama at 2.2 percent, and Not Classified at 0.2 percent. The total number of hospitals is 3,216. Each bar is labeled with the exact percentage and the number of hospitals in that classification.

Distribution of Indonesian hospitals by accreditation-relevant classification. Source: Maheswara (2024) 

Close modal
Figure 2
A bar graph showing the distribution of hospitals by class across Indonesian provinces.The bar graph compares the number of hospitals across various Indonesian provinces, categorized by class. The x-axis lists the provinces, including Aceh, North Sumatra, West Sumatra, Riau, Riau Islands, Jambi, Bengkulu, South Sumatra, Lampung, Bangka Belitung, DKI Jakarta, West Java, Central Java, DI Yogyakarta, East Java, Banten, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, North Kalimantan, East Kalimantan, Southeast Sulawesi, Gorontalo, West Sulawesi, South Sulawesi, Central Sulawesi, Maluku, North Maluku, West Papua, and Papua. The y-axis indicates the number of hospitals, ranging from 0 to 400. The graph uses a stacked bar format with four colors representing different hospital classes: blue for Class A, orange for Class B, green for Class C, and red for Class D. Each bar represents the total number of hospitals in a province, segmented by class. All values are approximated.

Distribution of hospitals by class across Indonesian provinces. Source: Komisi Akreditasi Rumah Sakit (KARS, 2023) 

Figure 2
A bar graph showing the distribution of hospitals by class across Indonesian provinces.The bar graph compares the number of hospitals across various Indonesian provinces, categorized by class. The x-axis lists the provinces, including Aceh, North Sumatra, West Sumatra, Riau, Riau Islands, Jambi, Bengkulu, South Sumatra, Lampung, Bangka Belitung, DKI Jakarta, West Java, Central Java, DI Yogyakarta, East Java, Banten, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, North Kalimantan, East Kalimantan, Southeast Sulawesi, Gorontalo, West Sulawesi, South Sulawesi, Central Sulawesi, Maluku, North Maluku, West Papua, and Papua. The y-axis indicates the number of hospitals, ranging from 0 to 400. The graph uses a stacked bar format with four colors representing different hospital classes: blue for Class A, orange for Class B, green for Class C, and red for Class D. Each bar represents the total number of hospitals in a province, segmented by class. All values are approximated.

Distribution of hospitals by class across Indonesian provinces. Source: Komisi Akreditasi Rumah Sakit (KARS, 2023) 

Close modal
Figure 3
A flowchart illustrating a work-applied strategy formulation framework.The flowchart illustrates a work-applied strategy formulation framework. The process begins with Strategic Mapping, which involves Problem Identification. This step leads to Organizational Positioning, where Collaborative Analysis is conducted. Following this, the process moves to Strategic Prioritization, focusing on Action Prioritization. There is a continuous feedback loop that connects all three steps back to Continuous Reflection & Adaptation, ensuring ongoing evaluation and adjustment. The flowchart uses arrows to indicate the flow between these steps, with dashed lines representing the feedback loop.

Work-applied strategy formulation framework. Source: Adapted from David et al. (2023), Teece et al. (2018) and Weiner (2009), integrated with WAM literature and AHP applications (Saaty, 2008; Ho, 2008; Park et al., 2023; Truong and Le, 2024)

Figure 3
A flowchart illustrating a work-applied strategy formulation framework.The flowchart illustrates a work-applied strategy formulation framework. The process begins with Strategic Mapping, which involves Problem Identification. This step leads to Organizational Positioning, where Collaborative Analysis is conducted. Following this, the process moves to Strategic Prioritization, focusing on Action Prioritization. There is a continuous feedback loop that connects all three steps back to Continuous Reflection & Adaptation, ensuring ongoing evaluation and adjustment. The flowchart uses arrows to indicate the flow between these steps, with dashed lines representing the feedback loop.

Work-applied strategy formulation framework. Source: Adapted from David et al. (2023), Teece et al. (2018) and Weiner (2009), integrated with WAM literature and AHP applications (Saaty, 2008; Ho, 2008; Park et al., 2023; Truong and Le, 2024)

Close modal
Figure 4
A matrix showing organizational positioning based on external and internal readiness scores.The matrix is divided into nine quadrants based on external readiness score (EFE) on the vertical axis and internal readiness score (IFE) on the horizontal axis. The external readiness score ranges from low (1.0 to 1.99) to high (3.0 to 4.0), while the internal readiness score ranges from low (1.0 to 1.99) to high (3.0 to 4.0). The quadrants are labeled as follows: Growth, Cautious Growth, Decline, Selective Growth, Balanced Readiness, Vulnerable Position, Aggressive Expansion, Strategic Build-Up, and Risky Growth. Each quadrant provides a recommended strategy for organizations based on their positioning. The current position is marked in the Selective Growth quadrant with an EFE of 2.60 and an IFE of 2.37. The recommended strategy for the Balanced Readiness quadrant includes maintaining strengths, improving human resources, strengthening standard operating procedures, and upgrading systems.

Organizational positioning matrix

Figure 4
A matrix showing organizational positioning based on external and internal readiness scores.The matrix is divided into nine quadrants based on external readiness score (EFE) on the vertical axis and internal readiness score (IFE) on the horizontal axis. The external readiness score ranges from low (1.0 to 1.99) to high (3.0 to 4.0), while the internal readiness score ranges from low (1.0 to 1.99) to high (3.0 to 4.0). The quadrants are labeled as follows: Growth, Cautious Growth, Decline, Selective Growth, Balanced Readiness, Vulnerable Position, Aggressive Expansion, Strategic Build-Up, and Risky Growth. Each quadrant provides a recommended strategy for organizations based on their positioning. The current position is marked in the Selective Growth quadrant with an EFE of 2.60 and an IFE of 2.37. The recommended strategy for the Balanced Readiness quadrant includes maintaining strengths, improving human resources, strengthening standard operating procedures, and upgrading systems.

Organizational positioning matrix

Close modal
Table 1

Operationalization of accreditation readiness assessment variables

Strategic aspectIndicatorData collection methodScale/NotesSupporting references
Governance and leadershipVision–mission, SOPs and organizational chartDocument review and interviewBinary + qualitative notesAlhawajreh et al. (2025) and Wolek Rocha (2024) 
Strategic planningUse of SWOT/IE matrix in decision-makingInterview and document reviewLikert 1–5van Wijngaarden et al. (2012) and Bryant (2024) 
Human resourcesTraining, certification and HR adequacyQuestionnaire and observationLikert 1–5; staff dataAlhawajreh et al. (2025) and Butt (2024) 
InfrastructureInpatient/outpatient, emergency room (ER) and IT facilitiesObservation and checklistChecklist scoringDevkaran et al. (2019) 
Clinical service qualitySOP compliance, infection control and patient surveyObservation and interviewsLikert 1–5Gurisch et al. (2024) and Alhawajreh et al. (2023) 
Accreditation complianceAudit records and feedback implementationDocument review and interviewGap scoring (0–3)Hussein (2025) and Devkaran et al. (2019) 
External regulatory fitAlignment with MoH and BPJS policiesPolicy analysis and interviewQualitative codingGurisch et al. (2024) and Hussein (2025) 
Community reachPatient load and referral networksInterview and secondary dataQuantitative + qualitativeAlhawajreh et al. (2023) 
Source(s): Adapted from KARS (2018) and WHO (2007) and further informed by prior empirical studies on hospital accreditation and organizational readiness (Devkaran et al., 2019; Alhawajreh et al., 2023; Gurisch et al., 2024; Hussein, 2025)
Table 2

Analytical framework mapping: From classical strategy formulation to work-applied adaptation

Classical stage (David et al., 2023)Work-applied adaptationAligned WALC elementSupporting theories
Input stage (IFE/EFE)WASM – Work-applied strategic mappingProblem identification1Organizational capability development
2Organizational readiness (Weiner, 2009)
Matching stage (SWOT/IE Matrix)OPM – Organizational positioning matrixCollaborative analysis1Dynamic capabilities: sensing and seizing (Teece et al., 2018)
2Dynamic capabilities: sensing and seizing (Teece et al., 2018)
Decision stage (QSPM)SPG – Strategic prioritization gridAction prioritization1Multi-criteria decision-making (Saaty, 2008; Ho, 2008)
2Recent AHP applications in healthcare (Park et al., 2023; Truong and Le, 2024)
Cross-cutting principleContinuous reflection and adaptationReflection and adaptation1Work-applied learning cycle (Bryant, 2024; Pederzini, 2019)
2Continuous quality improvement (Bergholt et al., 2022; Hussein, 2025)
Table 3

Work-applied strategic mapping (WASM) of accreditation readiness (see Appendix A1. Table A1 for detailed coding)

Internal enablers (strengths)Internal constraints (weaknesses)External enablers (opportunities)External constraints (threats)
Leadership commitment to quality improvementLimited specialist doctors and clinical staffMinistry of Health support programs for accreditationCompetition from established private hospitals
Staff motivation to pursue accreditationLimited facilities and medical equipmentJKN scheme ensures patient baseIncreasingly strict accreditation standards (KARS)
Potential collaboration with local government and puskesmasWeak SOP standardization and documentationGrowing public demand for affordable healthcareHigh patient expectations for advanced services
Affordable services supported by BPJSPoor IT infrastructure for health information systemsIntegration opportunities with regional health programsAccreditation failure risks if readiness gaps persist
Table 4

Internal factor evaluation matrix

Internal factorsWeightRatingScore
Leadership commitment0.1240.48
Staff motivation0.1030.30
Affordable services (BPJS)0.0830.24
Collaboration opportunities0.1030.30
Limited specialists0.1520.30
Limited facilities0.1520.30
Weak SOP standardization0.1520.30
Poor IT infrastructure0.1510.15
Total1.00 2.37
Table 5

External factor evaluation matrix

External factorsWeightRatingScore
MoH support for accreditation0.1540.60
JKN scheme ensures patient base0.1530.45
Public demand for affordable care0.1030.30
Regional integration programs0.1030.30
Competition from private hospitals0.2020.40
Increasing regulatory requirements0.1520.30
High patient expectations0.1020.20
Accreditation failure risk0.0510.05
Total1.00 2.60
Table 6

Strategic prioritization grid (SPG) for accreditation readiness

Work-applied strategy optionsLearning weight (from WASM)Applied relevance score (ARS)Strategic priority Index (SPI)Rank
Human resource training and SOP standardization0.358.252.8921
Governance reform and accountability practices0.307.102.1302
Facility and infrastructure improvement0.206.501.3003
IT system strengthening for accreditation0.156.000.9004

Supplements

Supplementary data

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