Corporate Divestment as an Alternative Solution for Business Development and Sustainability in the Construction of the Kuala Tanjung-Tebing Tinggi-Parapat Toll Road

Selecting the most appropriate divestment strategy for toll road infrastructure is a critical decision, especially under fiscal constraints and incomplete asset development. This study proposes a structured decision-making framework to evaluate strategic divestment options for the Kuala Tanjung–Tebing Tinggi–Parapat Toll Road project. Using the Analytic Hierarchy Process (AHP), four alternatives—Partial Divestment, Joint Venture, Initial Public Offering, and Full Divestment—were assessed against five key criteria: market readiness, execution speed, public attractiveness, governance and regulatory fit, and going concern. The evaluation was based on expert judgment, supported by literature-informed validation and consistency analysis. Findings highlight Partial Divestment as the most appropriate strategy, offering a balance between external capital mobilization and continued public oversight. This framework provides a practical tool for infrastructure owners and policymakers to guide divestment decisions and prioritize funding strategies in public–private toll road development. 

Introduction

Infrastructure development is a cornerstone of economic growth and regional integration, especially in emerging economies like Indonesia. Toll roads are critical infrastructure assets that support logistics, investment flows, and tourism. The Kuala Tanjung-Tebing Tinggi-Parapat (Kutepat) Toll Road, part of Indonesia’s Trans-Sumatra corridor, connects industrial clusters and tourism hubs such as Lake Toba. However, the construction of Sections 5 and 6 has stalled due to funding constraints and delayed Viability Gap Fund (VGF) support, placing the project’s financial viability and completion timeline at risk (Badan Pengatur Jalan Tol, 2023). In response to these challenges, Indonesia has committed to asset recycling and divestment initiatives as part of broader state-owned enterprise (SOE) reforms, aiming to mobilize private capital and reduce fiscal pressure on infrastructure development (Asian Development Bank, 2022).

This paper explores corporate divestment as a viable funding strategy for the Kutepat Toll Road project. Four divestment models—Full Divestment (FD), Partial Divestment (PD), Initial Public Offering (IPO), and Joint Venture (JV)—are assessed using the Analytic Hierarchy Process (AHP), a structured multi-criteria decision-making method established by Saaty (1994). These alternatives are evaluated against five criteria: market readiness, execution speed, public attractiveness, governance and regulatory fit, and going concern. By applying a multi-criteria decision-making framework, this study contributes to the evolving discourse on sustainable infrastructure finance in Indonesia. The analysis focuses on the Kutepat Toll Road and offers practical insights for policymakers and infrastructure sponsors to identify the most appropriate divestment strategy aligned with institutional priorities and long-term goals.

Literature Review

Conceptual Foundation of Divestment

Corporate divestment has evolved into a strategic mechanism used by private firms and public-sector entities to enhance capital efficiency, optimize portfolios, and manage risk. In infrastructure contexts, it provides governments and state-owned enterprises (SOEs) a tool to recycle capital from mature assets to new or underfunded projects (OECD, 2021). Rather than relying on public funding or debt, divestment enables infrastructure operators to mobilize private investment through partial or full transfer of ownership rights (Weberet al., 2016).

Across Asia, divestment and asset recycling programs increasingly aligned with broader public-private partnership strategies, especially where fiscal constraints and delays affect infrastructure delivery. According to Yoshinoet al. (2018), these financing tools can address structural bottlenecks by attracting institutional capital, transferring operational risk, and improving service quality if properly designed and executed.

Divestment model

Divestment models vary in the benefits and trade-offs they offer, particularly in relation to ownership, control, and liquidity. The most commonly adopted models include Full Divestment, Partial Divestment, Initial Public Offering, and Joint Venture.

• Full Divestment entails the complete sale of an infrastructure asset to a private party. While this approach provides maximum capital inflow and shifts operational responsibility to the buyer, it also results in the loss of strategic control and long-term revenue streams (OECD, 2021).

• Partial divestment allows the original owner to retain a stake while transferring the remainder to investors. This model has gained traction in Indonesia’s toll road sector due to its ability to raise funds without entirely surrendering strategic influence. It is particularly effective when paired with operational partnerships align with national infrastructure goals. For example, PT Hutama Karya (Persero) adopted this approach during the Partial Divestment of the Terbanggi Besar-Pematang Panggang-Kayu Agung Toll Road (PT Hutama Karya (Persero), 2023).

• IPO enables an infrastructure operator to raise capital by listing shares on a public exchange. A joint venture involves shared equity, governance, and risk between two or more entities.

• JVs are commonly used for complex, capital-intensive infrastructure projects that benefit from complementary capabilities—such as combining government-held concessions with private-sector funding and technical expertise (Deloitte, 2016).

Each of these models is context-dependent and should be evaluated not only by financial returns but also with alignment with regulatory constraints, investor appetite, and long-term strategic sustainability.

Criteria for Evaluating Divestment Alternatives

The divestment decision for the Kutepat Toll Road represents a high-stakes strategic initiative that demands evaluation beyond financial considerations. This study employs five key criteria drawn from policy reviews, academic literature, and industry practices, each capturing a distinct phase in the divestment lifecycle:

• Market Readiness (MR) assesses how favorable external conditions—investor appetite, capital market responsiveness, and macroeconomic stability—are for divestment, as favorable environments improve both feasibility and potential valuation.

• Execution Speed (ES) measures how efficiently a divestment can be implemented, including regulatory clearance and capital redeployment, critical in fast-changing markets.

• Public Attractiveness (PA) captures stakeholder perceptions, which are particularly important for SOEs where public trust and legitimacy affect acceptance.

• Governance and Regulatory Fit (GR) evaluates alignment with institutional norms and legal frameworks to reduce execution risks and ensure enforceability (Qiao, 2024).

• Going Concern (GC) emphasizes long-term operational and financial sustainability of the divested asset, especially in transitions from public to private control (Chow & Hamilton, 1993).

Together, these criteria provide a comprehensive framework for assessing divestment strategies, integrating strategic, financial, and institutional consideration.

Analytic Hierarchy Process (AHP) in Infrastructure Strategy

Divestment decisions for infrastructure assets often involve multiple, conflicting criteria. To address this complexity, this study adopts a Multi-Criteria Decision-Making (MCDM) approach, which enables structured evaluation across diverse attributes (Munieret al., 2019). MCDM is widely used in infrastructure planning and investment analysis due to its ability to integrate financial, regulatory, and operational factors. Among various methods, the Analytic Hierarchy Process (AHP), developed by Saaty (1994), is particularly suited for balancing such considerations. AHP breaks down complex decisions into a hierarchy of goals, criteria, and alternatives, supporting both qualitative and quantitative assessments in a transparent and logical manner (Mu & Pereyra-Rojas, 2017). The subsequent section describes the methodology used to implement AHP, including data sources, expert input, and the process of evaluating divestment options under public infrastructure constraints.

Methodology

Research Approach

To assess corporate divestment as an alternative solution for business development and sustainability in the construction of the Kutepat Toll Road, this study adopts a mixed-method approach, integrating both qualitative and quantitative analyses through the Analytic Hierarchy Process (AHP). The qualitative component is based on primary data obtained from four key stakeholders, while the quantitative component draws on secondary data, including business plans, valuation reports, regulatory frameworks, and prior research on infrastructure financing and divestment models. Together, this mixed-method approach offers a structured and transparent foundation for evaluating divestment strategies under public sector constraints.

Building on the mixed-method framework, AHP is applied in this study to rank the divestment alternatives based on the established evaluation criteria. The process begins with constructing a decision hierarchy (see Fig. 1), where the overall objective is placed at the top, followed by the relevant criteria and alternative strategies. This structure facilitates a systematic comparison of options, aligning with the strategic, operational, and regulatory priorities relevant to infrastructure project sustainability and stakeholder alignment.

Fig. 1. AHP decision hierarchy.

Data Collection Method

To support the AHP method, primary data were collected from four key stakeholders representing diverse roles in Indonesia’s toll road sector. These include a high-ranking government official (regulator), a project owner, a senior consultant, and a financier. Respondents were selected based on their strategic position, professional expertise, and direct relevance to divestment decisions-making. Judgment was obtained through pairwise comparison questionnaires, enabling the quantification of priorities across criteria and alternatives. The characteristics of the respondents are summarized in Table I.

Table I. Value of Random Index (RI)

Respondent	Affiliation	Position/Role	Stakeholder category
A	Directorate General of Highway (BPJT)	High ranking official	Regulator
B	PT DC solution	Senior consultant	Consultant
C	PT Hutama Marga Waskita	Commissioner	Project owner
D	PT Bank Mandiri (Persero) Tbk	Senior officer-financing division	Financier/Institutional Stakeholder

Application of AHP

To operationalize the model, pairwise comparisons are conducted to assess the relative importance of each criterion and the performance of alternatives against them. These comparisons are made using the 1–9 scale, which captures the preference intensity from equal importance (1) to extreme importance (9). Based on these inputs, the comparison matrices are constructed and then processed through normalization and eigenvector analysis to derive the relative weights of both criteria and alternatives. To assess the logical consistency of these judgments, the Consistency Index (CI) and Consistency Ratio (CR) are employed, as proposed by Saaty (1994). The CI measures the deviation from consistency and is calculated using the (1), where $\lambda max$ is the principal eigenvalue of the comparison matrix and $n$ is the matrix size:

(1) $$\begin{array}{r}CI=\frac{{\mathrm{\lambda }}_{max}-n}{n-1}\end{array}$$

Consistency ratio (CR) is then obtained by dividing the CI by the Random Index (RI), a benchmark derived from randomly generated matrices of the same order, as shown in the following (2):

(2) $$\begin{array}{r}CR=\frac{CI}{RI}\end{array}$$

CR value of less than 10% is considered acceptable, indicating that the pairwise judgments are consistent and reliable. Table II presents the RI values for matrices of size 1 to 10, as proposed by Saaty (1994):

Table II. Value of Random Index (RI)

n	1	2	3	4	5	6	7	8	9	10
RI	0	0	0.58	0.9	1.12	1.24	1.32	1.41	1.45	1.49

Once consistency is confirmed with an acceptable CR value, the final step is to compute the global priority for each alternative. This is done using the weighted sum model, which aggregates each alternative’s local priority under each criterion, weighted by that criterion’s relative importance. The global score is calculated using (3):

(3) $$\begin{array}{r}{S}_i=\sum _{j=1}^n{w}_j\cdot a_{ij}\end{array}$$

where $S_i$ is global score of alternatives $i$, $w_j$ is weight of criterion $j$, $a_{ij}$ is local priority of alternative $i$ under criterion $j$ and $n$ is total number of criteria. The alternative with the highest global score is selected as the preferred option, reflecting a comprehensive and consistent decision-making process.

Analysis using AHP

The analysis phase applies the Analytic Hierarchy Process (AHP) to evaluate and rank divestment alternatives based on expert judgment. Four respondents conducted pairwise comparisons to assess the relative importance of each criterion and alternative. Each set of judgments was used to generate individual normalized matrices and local priority vectors. To produce consolidated results, the normalized weights were averaged across all respondents.

Consistency of the pairwise comparisons was tested using the Consistency Index (CI) and Consistency Ratio (CR), with a threshold of 0.10 applied to ensure the reliability of inputs. Final global scores were then calculated using the weighted sum method, aggregating the averaged priorities across all criteria. In addition, a sensitivity analysis is conducted to assess the robustness of the final rankings by varying the weights of key criteria. The results are discussed in Section 4.

Findings

Overview of AHP Results

This chapter presents the results of the Analytic Hierarchy Process (AHP) analysis conducted to identify the most suitable corporate divestment model for the Kutepat Toll Road project. The pairwise comparisons were derived from four expert respondents, whose judgments were aggregated using the geometric mean method to form a group comparison matrix. This matrix was then normalized to calculate the priority weights for five strategic evaluation criteria relevant to Indonesia’s toll road infrastructure sector. The complete pairwise and normalize comparison matrix, along with the resulting criterion weight, is presented in Table III.

Table III. Pairwise and Normalize Comparison Matrix of Criteria

	Pairwise comparison matrix					Normalized comparison matrix						λmax	CI	CR
	MR	ES	PA	GR	GC	MR	ES	PA	GR	GC	Weight
MR	1	1.316	3.807	2.115	2.913	0.352	0.344	0.388	0.368	0.305	0.351	5.066	0.017	0.015
ES	0.760	1	2.711	1.520	2.060	0.268	0.261	0.276	0.264	0.216	0.257
PA	0.263	0.369	1	0.707	1.125	0.093	0.096	0.102	0.123	0.118	0.106
GR	0.473	0.658	1.414	1	2.449	0.167	0.172	0.144	0.174	0.257	0.183
GC	0.343	0.485	0.889	0.408	1	0.121	0.127	0.091	0.071	0.105	0.103
Sum	2.839	3.828	9.821	5.750	9.547

Evaluation of Criteria Weights

The paired comparison inputs from expert respondents were compiled into a group pairwise comparison matrix and normalized to derive the relative weights for each criterion. These weights will later be used to evaluate the divestment strategy alternatives. To test the consistency of the expert’s judgments, the CI and CR were calculated. The resulting CR value was 1.5%, which falls well below the acceptable threshold of 10% as proposed by Saaty (1994), thereby confirming the logical consistency and reliability of the assessment.

Among the five criteria, market readiness emerged as the most influential, with a normalized weight of 0.351. This reflects the dominant role of investor sentiment, capital availability, and market timing in shaping the success of divestment models in infrastructure sectors. According to Chen and Bartle (2017), public infrastructure projects—particularly toll roads—are highly dependent on stable regulatory frameworks and perceived project feasibility to attract private investment. This finding is consistent with recent Indonesian market cases, where Partial Divestments and IPOs were preferred under favorable liquidity conditions and strong investor demand (Investor Daily, 2023, September 8; Bisnis Indonesia, 2024, December 10). In the Kutepat Toll Road context, delays in Viability Gap Fund (VGF) disbursement and construction progress further elevate the relevance of investor confidence and project bankability.

Other criteria hold secondary yet still meaningful importance. Execution speed, with a weight of 0.257, reflects the need for rapid capital mobilization, particularly in urgent financing scenarios. Partial Divestment is noted for their swifter execution compared to IPOs or Full Divestments, which often involve longer due diligence and regulatory clearance (Asian Development Bank, 2022; Deloitte, 2016). Governance and regulatory Fit (0.183) and public attractiveness (0.106) are crucial for ensuring legal certainty and stakeholder transparency, although they are less critical when financing urgency dominates strategic considerations. The legal framework for toll road divestments in Indonesia has been strengthened by Law No. 2 of 2022 and its implementing regulation, Government Regulation No. 23 of 2024, which provide clear guidance on concession transfers, tariff policies, and clawback provisions (Pemerintah Republik Indonesia, 2022; Pemerintah Republik Indonesia, 2024). Going concern received the lowest weight (0.103), indicating that long-term sustainability, while important, is generally addressed after capital needs are met. As Weberet al. (2016) argue, financial closure typically precedes concerns around operational continuity and asset longevity.

Alternative Ranking under Each Criterion

After establishing the priority weights for each evaluation criterion, this section analyzes how each divestment alternative performs under individual criteria. For each criterion, a pairwise comparison matrix was developed to assess the relative performance of the four divestment strategies: Full Divestment (FD), Partial Divestment (PD), Initial Public Offering (IPO), and Joint Venture (JV). The results are presented in the following subsections (4.3.1 to 4.3.5), along with expert interpretations and contextual insights.

Market Readiness

Market Readiness emerged as the most influential criterion in evaluating the feasibility of divestment strategies. This subsection analyses how each alternative performs under this criterion, based on expert judgement. Table IV presents the group pairwise and normalize comparison matrix for four divestment strategies, constructed using geometric mean method. The resulting priority order is PD > JV > IPO > FD.

Table IV. Pairwise and Normalized Comparison Matrix of Divestment Alternatives under Market Readiness

	Pairwise comparison matrix				Normalized comparison matrix					λmax	CI	CR
	FD	PD	IPO	JV	FD	PD	IPO	JV	Weight
FD	1.000	0.180	1.034	0.289	0.091	0.099	0.122	0.068	0.095	4.059	0.020	0.022
PD	5.566	1.000	4.472	2.449	0.506	0.552	0.528	0.577	0.541
IPO	0.967	0.224	1.000	0.508	0.088	0.123	0.118	0.120	0.112
JV	3.464	0.408	1.968	1.000	0.315	0.225	0.232	0.235	0.252
Sum	10.998	1.812	8.474	4.246

This ranking is supported by real-world developments in Indonesia’s infrastructure investment landscape and reinforced by a high degree of consistency in the expert judgment used to construct the matrix. The pairwise comparison yielded a CR of 2.2%, comfortably below the 10% threshold, indicating that the assessments are both reliable and logically coherent (Saaty, 1994). PD received the highest weight (0.541), reflecting its attractiveness in facilitating capital access while maintaining state ownership and strategic influence. Recent successful transactions, such as the sale of a 35% stake in PT Jasamarga Transjawa Tolroad to a consortium led by Metro Pacific Tollways Corporation (MPTC) and Global Institutional Investor (GIC), exemplify this model’s strong market appeal (Bisnis Indonesia, 2024, December 10). JV with a weight of 0.252, follows as a flexible mechanism for risk-sharing and collaborative development, although it typically requires longer negotiations and shared governance arrangements (World Bank Group, 2024). The preference for JV over more rigid structures reflects investors’ willingness to engage under shared control, particularly in projects still under construction.

At the lower end of the spectrum, FD (0.095) and IPO (0.112) received similarly low weights. This reflects common investor hesitation toward strategies involving complete asset transfer or public listing for incomplete toll roads. FD, while viable post-construction, is currently constrained by valuation uncertainty, construction risks, and the absence of proven revenue streams. It may become more attractive once the project reaches operational maturity. Similarly, IPO is considered the least market-ready option due to Indonesia's limited infrastructure IPO track record and the demanding requirements for listing, including robust governance and financial transparency—criteria not typically met by toll road SPVs during development (World Bank Group, 2024).

Execution Speed

Beyond market readiness, execution speed also plays a critical role in determining the practicality of divestment strategies, especially in projects requiring urgent capital mobilization. Table V shows that PD leads again, with the highest weight of 0.381, reflecting its ability to deliver capital swiftly through structured stake sales, particularly when investors are pre-identified. This pattern is evident in previous transactions involving Hutama Karya and Jasa Marga (Bisnis Indonesia, 2024, December 10; Investor Daily, 2023, September 8; PT Hutama Karya (Persero), 2023).

Table V. Pairwise and Normalized Comparison Matrix of Divestment Alternatives under Execution Speed

	Pairwise comparison matrix				Normalized comparison matrix					λmax	CI	CR
	FD	PD	IPO	JV	FD	PD	IPO	JV	Weight
FD	1.000	0.221	0.243	0.230	0.071	0.086	0.081	0.046	0.071	4.090	0.030	0.033
PD	4.527	1.000	1.107	2.213	0.323	0.388	0.370	0.442	0.381
IPO	4.120	0.904	1.000	1.565	0.294	0.351	0.335	0.313	0.323
JV	4.356	0.452	0.639	1.000	0.311	0.175	0.214	0.200	0.225
Sum	14.002	2.576	2.988	5.008

IPO ranked second with a weight of 0.323. While IPO procedures are clear and well-regulated, they remain time-consuming due to requirements such as audits, disclosures, and regulatory approvals. Nevertheless, the predictability of IPOs offers an edge in execution over more complex private transactions.

JV follows with a weight of 0.225, offering moderate execution speed. JV schemes can often advance based on early-stage memoranda of understanding and gradually evolve into full agreements, making them relatively efficient when interests are aligned (Deloitte, 2016). FD ranked lowest at 0.071. Despite being a private transaction, it typically requires comprehensive asset valuation, due diligence, and renegotiation of concession terms. These factors increase the timeline sensitive to investor interest and negotiation dynamics, raising the risk of delay. Empirical and case-based findings from Yescombe and Farquharson (2018) illustrate that full asset transfers consistently exhibit longer execution timelines in both developed and emerging market contexts. The resulting CR of 3.3% indicates strong logical coherence in the comparison matrix.

Public Attractiveness

While execution speed addresses how quickly a divestment strategy can be implemented, public attractiveness focuses on the degree of stakeholder support, particularly from the public, political actors, and civil society groups. This criterion is especially significant in divestments involving state-owned infrastructure, where perceived legitimacy, transparency, and alignment with public interest directly influence social and political feasibility. In contrast to market readiness, which considers “Can we sell this now, and to whom?”, public attractiveness concerns itself with “Will the public and political stakeholders be OK with us selling this?” Table VI presents the group pairwise comparison results under this criterion. The comparison matrix yields a CR of 2.3%, which remains within the acceptable threshold, indicating logical coherence in the expert judgments.

Table VI. Pairwise and Normalized Comparison Matrix of Divestment Alternatives under Public Attractiveness

	Pairwise comparison matrix				Normalized comparison matrix					λmax	CI	CR
	FD	PD	IPO	JV	FD	PD	IPO	JV	Weight
FD	1.000	0.144	0.537	0.190	0.066	0.069	0.095	0.052	0.071	4.062	0.021	0.023
PD	6.928	1.000	2.523	1.861	0.460	0.481	0.445	0.507	0.473
IPO	1.861	0.396	1.000	0.620	0.124	0.191	0.176	0.169	0.165
JV	5.264	0.537	1.612	1.000	0.350	0.259	0.284	0.272	0.291
Sum	15.054	2.078	5.672	3.672

The results show that PD (0.473) and JV (0.291) are considered the most publicly acceptable options. PD maintains partial public ownership, which aligns with national interest narratives and enables the government to retain strategic control. This is evident in past transactions involving Jasa Marga, where the Ministry of State-Owned Enterprises (SOE) explicitly endorsed a strategic partnership scheme for Jasa Marga Transjawa Tolroad (Bisnis Indonesia, 2024, December 10).

JV arrangements are similarly favored because they emphasize collaboration and shared development, rather than outright privatization (Grimsey & Lewis, 2002). In contrast, FD (0.071) and IPO (0.165) are perceived as less attractive. FD often invites public resistance over concerns about the sale of strategic assets, especially to foreign buyers. IPOs, while transparent and regulated, are frequently critiqued for favoring institutional investors over the general public and for potentially shifting public services toward profit-oriented motives (Ng & Loosemore, 2007; Qiao, 2024). These findings underscore the need to align divestment approaches not only with financial feasibility but also with broader public and political acceptance.

Governance and Regulatory Fit

In addition to stakeholder perception, the alignment of each divestment strategy with the prevailing governance and regulatory framework is a critical determinant of feasibility. This criterion assesses how well each alternative conforms to existing legal structures, institutional processes, and required approvals within Indonesia’s toll road divestment landscape. Unlike public attractiveness, which focuses on stakeholder perception, Governance and regulatory fit evaluates procedural clarity and compliance risks. Table VII presents the group pairwise comparison matrix under this criterion, with a CR of 4.6%, indicating that the expert’s judgments are logically sound and within the acceptable threshold.

Table VII. Pairwise and Normalized Comparison Matrix of Divestment Alternatives under Governance and Regulatory Fit

	Pairwise comparison matrix				Normalized comparison matrix					λmax	CI	CR
	FD	PD	IPO	JV	FD	PD	IPO	JV	Weight
FD	1.000	0.221	0.241	0.263	0.074	0.072	0.093	0.052	0.073	4.124	0.041	0.046
PD	4.527	1.000	0.707	2.213	0.336	0.324	0.273	0.439	0.343
IPO	4.141	1.414	1.000	1.565	0.307	0.458	0.386	0.310	0.366
JV	3.807	0.452	0.639	1.000	0.283	0.146	0.247	0.198	0.219
Sum	13.475	3.087	2.588	5.041

The results show that IPO ranks highest (0.366) under governance and regulatory fit. This reflects its strong legal grounding, structured approval processes through OJK and IDX, and well-established compliance protocols, making it the most regulatorily aligned option. PD follows with a weight of 0.343, supported by successful precedents involving SOEs such as Hutama Karya and Jasa Marga. Although PD offers flexibility, it still requires alignment with ministerial oversight and asset valuation mechanisms. JV with a score of 0.219, is considered moderately aligned but often requires bespoke arrangements, which can complicate regulatory compliance. FD ranks lowest (0.073), due to its higher risk of triggering clawback provisions or scrutiny over state asset sales—especially given that Sections 1–4 of the Kutepat Toll Road were funded through state capital injection (PMN) via the parent company PT Hutama Karya (Persero) (Bisnis Indonesia, 2023, September 29). These findings highlight the importance of not only strategic fit but also institutional readiness when selecting a divestment model.

Going Concern

The going concern criterion further reinforces the preference for PD, which ranks highest with a priority weight of 0.465 (Table VIII). This reflects its ability to maintain long-term operational and financial sustainability even during transitions from public to private control. PD ensures that the government retains a degree of strategic oversight, reducing the risk of service disruption or neglect of life-cycle maintenance. JV follows with a weight of 0.309, benefiting from its collaborative nature and mutual accountability structure, which supports continued asset management after divestment. IPO, with a score of 0.182, is considered less favorable under this criterion due to its profit-maximization incentives and market-driven nature, which may deprioritize reinvestment in long-term infrastructure upkeep. FD ranks lowest (0.045), as it fully transfers control to private hands, raising concerns over sustained service delivery and capital reinvestment, particularly if the asset is incomplete or still reliant on public subsidy mechanisms. These judgments are validated by the CR of 3.5%, well below the 10% threshold, confirming logical coherence in the expert’s pairwise assessments.

Table VIII. Pairwise and Normalized Comparison Matrix of Divestment Alternatives under Going Concern

	Pairwise comparison matrix				Normalized comparison matrix					λmax	CI	CR
	FD	PD	IPO	JV	FD	PD	IPO	JV	Weight
FD	1.000	0.118	0.202	0.139	0.046	0.058	0.034	0.039	0.045	4.095	0.032	0.035
PD	8.452	1.000	2.449	2.000	0.392	0.493	0.418	0.557	0.465
IPO	4.949	0.408	1.000	0.452	0.229	0.201	0.171	0.126	0.182
JV	7.172	0.500	2.213	1.000	0.332	0.247	0.377	0.278	0.309
Sum	21.573	2.027	5.865	3.591

Global Ranking of Alternatives

After establishing the priority weights for each alternative under every criterion, the next step involves integrating these values using the overall importance of each criterion. Table IX presents the group weighted evaluation of all divestment alternatives, combining group local scores and criteria weights to generate the final global scores and rankings.

Table IX. Weighted Evaluation of Divestment Alternatives Based on Criteria Scores

Objectives	Criteria	Criteria weight	Local priority score per alternative				Global weight per alternative
			FD	PD	IPO	JV	FD	PD	IPO	JV
Selecting Corporate Divestment Strategy for Kutepat Toll Road	MR	35.1%	0.095	0.541	0.112	0.252	0.033	0.190	0.039	0.089
	ES	25.7%	0.071	0.381	0.323	0.225	0.018	0.098	0.083	0.058
	PA	10.6%	0.071	0.473	0.165	0.291	0.008	0.050	0.018	0.031
	GR	18.3%	0.073	0.343	0.366	0.219	0.013	0.063	0.067	0.040
	GC	10.3%	0.045	0.465	0.182	0.309	0.005	0.048	0.019	0.032
	Sum	100%				Sum	0.077	0.449	0.225	0.249
						Rank	#4	#1	#3	#2

To derive the overall ranking of divestment alternatives, the local priority scores from each criterion were aggregated using the weights established in Table III. These criteria weights reflect the relative importance of Market Readiness, Execution Speed, Public Attractiveness, Governance and Regulatory Fit, and Going Concern. The local priority scores per alternative were drawn from Tables IV–VIII, which represent how each strategy performed under each criterion. By multiplying these scores by their respective criterion weights, the global weights for each alternative were calculated. As shown in Table IX, this process yields the final prioritization of alternatives based on a comprehensive and structured evaluation framework.

Sensitivity Analysis

To assess the robustness of the final rankings, a sensitivity analysis was conducted by adjusting the weights of the three most influential criteria: Market Readiness (Table X), Execution Speed (Table XI), and Governance and Regulatory Fit (Table XII), each by ±10%. This analysis evaluated whether the priority order of divestment alternatives would hold under varying strategic emphases. The results show that despite minor shifts in the relative importance of the criteria, the overall ranking remains stable. Partial Divestment (PD) is confirmed as the most favorable strategy, consistently followed by Joint Venture (JV) in second place.

Table X. Sensitivity Analysis of Global Weights under ±10% Market Readiness Adjustment

Criteria	MR +10%					MR − 10%
	Criteria weight	Global weight per alternative				Criteria Weight	Global weight per alternative
		FD	PD	IPO	JV		FD	PD	IPO	JV
MR	45.1%	0.043	0.244	0.051	0.114	25.1%	0.024	0.136	0.028	0.063
ES	23.2%	0.016	0.088	0.075	0.052	28.2%	0.020	0.107	0.091	0.063
PA	8.1%	0.006	0.038	0.013	0.024	13.1%	0.009	0.062	0.022	0.038
GR	15.8%	0.011	0.054	0.058	0.034	20.8%	0.015	0.071	0.076	0.045
GC	7.8%	0.003	0.036	0.014	0.024	12.8%	0.006	0.059	0.023	0.039
Sum	100.0%	0.080	0.461	0.211	0.248	100.0%	0.074	0.436	0.240	0.250
	Rank	#4	#1	#3	#2		#4	#1	#3	#2

Table XI. Sensitivity Analysis of Global Weights under ±10% Execution Speed Adjustment

Criteria	ES +10%					ES − 10%
	Criteria weight	Global weight per alternative				Criteria Weight	Global weight per alternative
		FD	PD	IPO	JV		FD	PD	IPO	JV
MR	32.6%	0.031	0.176	0.037	0.082	37.6%	0.036	0.203	0.042	0.095
ES	35.7%	0.025	0.136	0.115	0.080	15.7%	0.011	0.060	0.051	0.035
PA	8.1%	0.006	0.038	0.013	0.024	13.1%	0.009	0.062	0.022	0.038
GR	15.8%	0.011	0.054	0.058	0.034	20.8%	0.015	0.071	0.076	0.045
GC	7.8%	0.003	0.036	0.014	0.024	12.8%	0.006	0.059	0.023	0.039
Sum	100.0%	0.077	0.441	0.237	0.245	100.0%	0.077	0.456	0.214	0.253
	Rank	#4	#1	#3	#2		#4	#1	#3	#2

Table XII. Sensitivity Analysis of Global Weights under ±10% Governance and Regulatory Fit Adjustment

Criteria	GR +10%					GR − 10%
	Criteria weight	Global weight per alternative				Criteria Weight	Global weight per alternative
		FD	PD	IPO	JV		FD	PD	IPO	JV
MR	32.6%	0.031	0.176	0.037	0.082	37.6%	0.036	0.203	0.042	0.095
ES	23.2%	0.016	0.088	0.075	0.052	28.2%	0.020	0.107	0.091	0.063
PA	8.1%	0.006	0.038	0.013	0.024	13.1%	0.009	0.062	0.022	0.038
GR	28.3%	0.021	0.097	0.103	0.062	8.3%	0.006	0.028	0.030	0.018
GC	7.8%	0.003	0.036	0.014	0.024	12.8%	0.006	0.059	0.023	0.039
Sum	100.0%	0.077	0.436	0.242	0.244	100.0%	0.077	0.461	0.208	0.254
	Rank	#4	#1	#3	#2		#4	#1	#3	#2

Conclusion

Partial Divestment emerges as the most suitable strategy for the Kutepat Toll Road project, achieving the highest global priority score of 0.449. This model enables external capital mobilization while preserving government control, a balance that has been effectively demonstrated in recent Indonesian transactions involving Jasa Marga and Hutama Karya. Joint Venture, ranked second with a score of 0.249, offers a flexible alternative in scenarios where market readiness or investor appetite may constrain PD implementation. With its potential for staged investment and shared risk, the JV model is particularly well-suited for partially developed infrastructure like Kutepat.

These findings are based on structured input from four diverse stakeholders—representing regulatory, operational, financial, and advisory roles—and supported by literature-based validation. Sensitivity analysis confirms the robustness of the rankings across variations in key criteria weights. While limited to a single case, this study provides actionable insights for policymakers and infrastructure owners in identifying fiscally sound and strategically aligned divestment pathways. Future research should expand stakeholder representation and explore multi-case comparisons to strengthen generalizability.

Conflict of Interest

Conflict of interest: The authors declare that they do not have any conflict of interest.