Evaluating the Sustainable Adaptive Reuse Alternative for Architectural Heritage Through the Multi-Criteria Decision Analysis (MCDA) Method—A Study of a National Monument of Nigeria

Abstract

Adaptive reuse has emerged to become a tool for implementing the understanding of sustainability in the domain of architectural conservation, as it encourages the continued usage of old buildings as means of reducing environmental impact, as well as preserving socio-cultural capital while generating economic income. However, in its practice, the decisions regarding granting meanings, interpretation, and preserving memories within adaptation processes are dominated by expert-driven approaches that inadequately incorporate stakeholder values or intangible heritage dimensions. To this end, this study aims to contribute to the current debate by adopting a participatory co-evaluation framework that integrates both authenticity perspectives and sustainability dimensions using Multi-Criteria Decision Analysis (MCDA) for evaluating adaptive reuse alternatives for an abandoned prefabricated wooden heritage building. Stakeholder priorities were drawn through a workshop and transformed into normalized weights using the Simos technique. Four design alternative typologies—namely, Continuity, Cultivation, Differential, and Optimization—were assessed and compared against 20 performance indicators across heritage, social, ecological, and economic criteria using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Indicator-level analyses and sensitivity tests (±10% and ±20% weight variations) were applied to confirm the robustness of rankings. The results from the best-performing alternative demonstrated the trade-offs between heritage authenticity and sustainability objectives, as well as demonstrating how combining participatory methods with quantitative evaluation can support evidence-based decision-making for adaptive reuse. The applied integrated framework helps bridge the gap between heritage theory and practice by combining authenticity, participation, and sustainability in one analytical approach, supporting evidence-based decisions for adaptive reuse.

1. Introduction

The adaptive reuse of architectural heritage simply refers to the renovation or restoration of buildings and giving them a new function, while ensuring that the inherent cultural values are not compromised by the proposed change in use or adaptation [1,2,3,4]. In recent years, adaptive reuse has emerged to become a tool for achieving sustainability, as it aims at the reduction in environmental impact through the conservation of non-renewable heritage resources. It also encourages the perpetual usage of old buildings while generating economic resources while maintaining social and cultural capital expressed through the human skill and creativity in heritage buildings [5,6,7]. This practice is recommended by several international conservation Charters and Guidance; for example, as early as 1933, the Athens Charter [8], and much later, in 1964, the Venice Charter [9], implicitly and explicitly advocated adaptive reuse as a sustainable option to ensure the continuity of architectural heritage to extent their longevity, safeguard their physical fabric, and thus prevent ruination [10].

However, in recent years, the debate has moved beyond staunch emphasis solely on the importance of authenticity of material fabric, thereby introducing ethical issues into the discourse of adaptive reuse. It has evolved to be about negotiating the transition from the past to the future while also meeting the needs of contemporary society [11,12]. Owing to these inevitable entanglements with social, scientific and political deliberations, several years of the practice of heritage adaptive reuse have demonstrated a handful of associated challenges. For example, there are the challenges associated with the political dimension of granting meanings and authenticity [10]. Furthermore, Lanz and Pendlebury [13] argued that there is currently a gap in knowledge regarding the consequences of adaptive reuse on identity and memory of a place and people. The decisions regarding the adaptation, restoration, and change in use are often fraught with multiple interpretations of what represents authenticity, and what the different actors assume to connote an authentic building [14]. This is particularly a conundrum in instances where the adaptive reuse process aims to be inclusive and go beyond simple authoritative intervention solely involving experts. As such, adaptive reuse of heritage buildings has emerged as a platform for stakeholder triangulations, the inclusion of sub-altern voices and aggregation of a diversity of perceptions regarding the uses of the past and the authenticity of heritage buildings for future uses.

It remains far from clear, however, by what means the diverse notions of authenticity can be negotiated and consensus determined on the usage of the past among the different stakeholders. In the literature, diverse evaluation tools have been positioned to support decision-making in arriving at a widely accepted option for the adaptive reuse of buildings [15,16]. Such approaches include valuation of buildings’ adaptive reuse, from a user experience perspective (for example see: [17,18,19]), comparing and combining diverse evaluation tools (for example see: [20,21,22]), climate perspectives (for example, [23]), and multi-criteria analysis [22,24]. Despite these frameworks, many adaptive reuse projects remain dominated by expert-driven approaches that inadequately incorporate stakeholder values or intangible heritage dimensions. Previous research has highlighted that conventional cost–benefit analyses or architectural evaluations often overlook the cultural and social functions of heritage assets and rarely employ multidimensional, participatory decision-making frameworks [25,26]. Therefore, a methodological gap persists in systematically balancing authenticity, social cohesion, Financial Viability, and environmental performance in adaptive reuse decisions.

As a contribution to the current debate, therefore, this paper aims to adopt a participatory evaluation methodology which combines both qualitative and quantitative data using Multi-Criteria Decision Analysis (MCDA). This framework premises the possibility of ensuring the engagement of different stakeholders, defining objectives, criteria and indicators, as well as assessing and comparing adaptive reuse options with the view of recommending the closest alternative to the ideal adaptive reuse strategy. The analysis uses two main techniques: (1) the Simos weighting method [27,28] to convert stakeholder preferences into measurable weights, and (2) the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate how closely reuse alternatives achieve an ideal balance of sustainability and authenticity. The proposed approach is applied on a prefabricated wooden architectural heritage—Egbo Egbo Bassey house in Calabar, a National Monument of Nigeria which is dilapidated, abandoned and on the verge of total collapse.

To achieve the drawn aim of the paper, it is structured into six main parts. Following this introduction is section two, which is a case context description of the study building—Egbo Egbo Bassey house. Section three is the research methodology. Here this paper highlights the data collection methods, tools, and the data analysis approach. Section four presents the results of the paper, and the data derived from the application of the methodology. Section five critically discusses the results derived from section four. This paper concludes in section six, with recommendations for future research.

2. Case Context Description

Egbo Egbo Bassey house is a colonial prefabricated wooden building in Old Calabar, Nigeria. The building was imported by an Efik trader in Old Calabar, through his trading contacts with British traders in 1883 during the European slave and palm oil trade in the Bight of Biafra. It is geographically located at between Latitude 4°57′41.393″ N and Longitude 8°18′57.033″ E in No. 19 Boko Street, Old Calabar, South-southern Nigeria (see Figure 1).

On 14 August 1959, Egbo Egbo Bassey house was identified and declared a National Monument of Nigeria as determined by the extant Antiquity Ordinance No. 17 of 1953 (now NCMM ACT, Cap 242 of 2000). On the 13th of December 1986, during the celebration of its first 100 years, this building was officially handed over to the National Commission for Museums and Monuments (NCMM) [30]. However, this building was abandoned in 2012 and since then it has decayed at an accelerated rate and is currently on the verge of complete collapse (see Figure 2, Figure 3 and Figure 4).

As shown in the images above, the building has reached the end of its life cycle. From being prefabricated in Glasgow and shipped upon the request of Chief Egbo Egbo Bassey, to its arrival on the shores of Old Calabar in 1883, to the completion of the construction in 1886, the usage of the building started in 1886 when it was a private building of Chief Egbo Egbo Bassey until 1897 [30], (p. 14) and the usage ended in 2012 when the descendant family moved out following rapid dilapidation (see Figure 5).

From the year 2012, the building has been abandoned, and it started rapid dilapidation, which signified the end of its life cycle. However, there has been a renewed interest in the restoration and adaptive reuse of the building. Finally, in November 2025, Gerda Henkel Stiftung funded the restoration and adaptive reuse of this National Monument. The aim of the adaptive reuse project is to give the building a new usage and re-socialize it while re-starting its life cycle.

3. Material and Methods

The methodology for this study is structured into two phases (see Figure 6). The first phase is dedicated to gathering architectural data for the building—Egbo Egbo Bassey house and setting objectives. The second phase is dedicated to the comparison and evaluation of the objectives, criteria and indicators in which the ‘ideal’ solution for the adaptive reuse of the building emerges [31].

3.1. Phase 1: Data Collection, Objective Selection and Design Proposal

The primary purpose of this Phase 1 is to gather historical and architectural data for the abandoned building and set adaptive reuse objectives. Two sets of objectives were considered here: one specific objective relates to adaptive reuse purpose for the building and, secondly, specific objectives that meet sustainability standards. Against this background, this phase was structured into 4 steps, namely:

3.1.1. Step 1: Building Data Collection

In this step the collection and analysis of detailed information on the relics of Egbo Egbo Bassey house was carried out. Data collection was done through archival research and review of published literature.

3.1.2. Step 2: Defining the Adaptive Reuse Objectives

Following the collection of the building data, the first stakeholder meeting was organized to gather the general objective and criteria for the adaptive reuse of the building. The stakeholder meeting comprises 36 deliberately selected participants such as heritage professionals (n = 15), community residents (n = 7), descendant families (n = 4), organized interest groups (n = 3), students (n = 5), and members of the traditional council (n = 2). This stakeholder meeting was held in March 2024 at the National Museum, Calabar. The adaptive reuse objectives were expressed qualitatively, to guide the adaptive reuse process, where ideas were still being developed.

3.1.3. Step 3: Prioritization of Objectives

Adaptive Reuse Objectives

Questionnaires were administered both physically and online with diverse categories of local stakeholders involved. The stakeholders included heritage officers, policy makers, descendant families, organized interest groups, proximate local community and experienced professionals (see Figure 7 for respondent distribution). A total of 60 questionnaires were administered across the different stakeholder groups. A total of 45 were returned and retained for analysis, amounting to a 75% response rate.

According to [32,33], a response rate above 70% is considered sufficient to limit non-response bias and offers sufficient group response judgement. The questionnaires returned were further screened according to three inclusion criteria, namely: first, complete answers to all questions; second, demonstration of sufficient knowledge of Egbo Egbo Bassey house; and third, absence of inconsistencies such as duplication of ranking, etc. Questionnaires not meeting these criteria were excluded [33,34].

Through the two rounds of questionnaires, a set of 10 objectives were defined to guide both the alternative adaptive reuse by local stakeholders and to evaluate them. Stakeholders were asked to rank the objectives from the most important to the least important. This was to be done by designating a grade from 10 to 1, where 10 connotes the highly significant objective while 1 connotes the least significant objective. To assign weight to each objective, the Simos [27] method was applied. Therefore, the objectives linked were weighed in accordance with the expressed preferences by the stakeholders through an administered questionnaire during the study. The Simos technique converts ordinal rankings into cardinal weights through a four-step card exercise [27,28]. The Simos procedure followed four structured steps:

• Card Ordering: Stakeholders arranged objectives from least to most important.
• Equal Gaps: Spacing between cards represented perceived differences in importance.
• Card Counting: Scores were aggregated across participants.

Normalization: Aggregated scores were standardized so total weights summed to one, making them suitable for the subsequent Multi-Criteria Decision Analysis (MCDA).

The method’s transparency and ease of use have been validated in heritage and urban-planning MCDA studies [24,35], making it well suited to participatory weighting in adaptive reuse projects. After analyzing the characteristics of the objectives, set of criteria and indicators were determined through literature review and they were thematically organized into four main domains, namely:

• Heritage continuity
• Social cohesion
• Circular and creative economy
• Access and environmental resilience
• Sustainability objectives

Through the questionnaires that were administered, the stakeholders highlighted some of the sustainability dimensions for the proposed adaptive reuse. The sketchy points raised by the stakeholders were organized and reviewed against the four pillars of sustainable development. To do this, the paper draws significantly on the framework presented by Europa Nostra [36] and buttressed by the broad literature, i.e., cultural, social, economic and environmental sustainability [37]. Through development of indicators, a sensitivity analysis was carried out, identifying and assessing the compliance of the different alternatives with the indicators of sustainable development, namely:

• Ecologically friendly proposal
• Culturally sensitive proposal
• Socially viable proposal
• Economically viable proposal.

The comparison of all scenarios allowed the identification of crucial features for the success of the adaptive reuse solutions and, consequently, which characteristics of the various alternatives are less vulnerable to change.

3.1.4. Step 4: Development of Project Architectural Alternatives

According to the stated objectives, four alternative adaptive reuse designs were proposed. The derived objectives and the historical data of the building were architecturally translated into alternatives by drawing on the Ellen Braae [38] approach. This approach argues that adaptive reuse is a means to view architecture as a medium that can be altered and is always in transition [38,39]. On this account, four different approaches were distinguished (cited in [39], (p.134), [40], (p.130)), namely—Differential, Continuity, Cultivation and Optimization. These alternatives are distinguishable based on the following:

Differential (new prevailing over old): In this school of thought, a new architectural proposal prevails over the existing historic outlook. In this view, new interventions must be different from the existing building and must produce contrastive architecture. Therefore, the proposal for the study building, as well as its use and function will be distinguishable from the existing building, resulting in contrasting architecture.

Continuity (minimal intervention): In this approach, the proposal for adaptive reuse must be inferior or superficial in comparison to historic architecture. This approach aims at an adaptive reuse which must be subordinate to the existing building and is kept simple to ensure the continued functioning of the building. Here, the building was kept at its 1959 architectural outlook.

Cultivation (stratified dialogue): In this approach, the historical layer of the building is perceived as an infinite past. In this logic, there are multiple layers of the past, yet, from different perspectives. The architect can therefore select from this stratified historical past to design a current adaptive reuse proposal. While attempting to create something new, the new architecture thereby goes into dialogue with the past.

Optimization (idealized restoration): This approach assumes historic architecture as a repository of universal knowledge. The past and associated history are employed as pragmatic basis for development of optimized versions of a building. In this view, the material of the building is inferior to this story. Therefore, the transformation must exaggerate or underline this story to re-generate this for posterity.

3.2. Phase 2: Evaluation and Selection of Optimal Solution Using MCDA Approach

Having set the objectives, developed four design proposals and developed the prioritization indicator in Phase 1, the next step phase focuses on the systematic evaluation and selection of the optimal adaptive reuse solution using a Multi-Criteria Decision Analysis (MCDA) approach. The MCDA-TOPSIS evaluation approach is applied to compare these alternatives. Using weights from the Simos method, each alternative was scored against 20 performance indicators across heritage continuity, social, environmental, and financial dimensions. TOPSIS ranking and sensitivity analysis (±10% and ±20% weight variations) tested the stability of the results. To arrive at the selection of the optimal solution through a Multi-Criteria Decision Analysis (MCDA), the following steps were undertaken according to [27]:

• Step 1: Normalization of the Decision Matrix

To make values comparable across different scales:

$$r_{ij={\displaystyle \frac{x_{ij}}{\sqrt{\sum _{i=1}^m{x}_{ij}^2}}}}$$

where

• ${\mathrm{r}}_{\mathrm{i}\mathrm{j}}$ = normalized value of alternative $\mathrm{i}$ for criterion $\mathrm{j}$;
• ${\mathrm{x}}_{\mathrm{i}\mathrm{j}}$ = original performance score;
• $\mathrm{m}$ = number of alternatives.

• Step 2: Weighted Normalized Matrix

Weights were assigned to criteria using the Simos weighting method, which converts stakeholder ordinal rankings into cardinal weights. If $w_j$ is the weight of criterion $j$, the weighted normalized score is:

$$v_{ij}=w_j.r_{ij}$$

• $v_{ij}=Final weighted score$
• ($Weighted normalized value of alternative i on criterion j)$
• $w_j=weight from SIMOS$ ($Weight of criterion j from SIMOS$ in Phase 1)
• Step 3: Positive Ideal Solution (PIS)

$$A^{+}=\left\{v_1^{+},v_{2 , \dots ,}^{+} v_n^{+}\right\}, v_j^{+}=\mathrm{m}\mathrm{a}\mathrm{x}\left(v_{ij}\right)$$

• $A^{+}=Positive ideal solution \left(best performance for all criteria\right)$
• $v_1^{+}=Best value of criterion j across all alternatives$
• Step 4: Negative Ideal Solution (NIS)

$$A^{-}=\left\{v_1^{-},v_{2 , \dots ,}^{-} v_n^{-}\right\}, v_j^{-}=\mathrm{m}\mathrm{i}\mathrm{n}\left(v_{ij}\right)$$

• $A^{-}=Negative ideal solution \left(worst performance for all criteria\right)$
• $v_1^{-}=Worst value of criterion j across all alternatives$
• Step 5: Distance to Ideal Solutions

$$S_i^{+}=\sqrt{\sum _{j=1}^n{\left(v_{ij}-v_j^{+}\right)}^2,}{S}_i^{-}=\sqrt{\sum _{j=1}^n{\left(v_{ij}-v_j^{-}\right)}^2 }$$

• $S_i^{+}=Distance of alternative i from the ideal solution$
• $S_i^{-}=Distance from the negative ideal solution$
• Step 6: Closeness Coefficient (Final Ranking)

$${CC}_i={\displaystyle \frac{S_i^{-}}{S_i^{+}+S_i^{-}}} , 0\le {CC}_i\le 1$$

where ${CC}_i$ = relative closeness to the ideal solution. Alternatives are ranked based on decreasing ${CC}_i$, with higher values indicating preferred solutions.

• ${CC}_i=TOPSIS score of alternative i \left(0-1\right)$ (how close each alternative is to the ideal)
• $Higher=Better performance$

3.2.1. Scenario Evaluation: Sensitivity Analysis

Generally, sensitivity analysis is acknowledged as an important element of Multi-Criteria Decision Methods (MCDM). This is owing to its utility at determining how the results of decision models can be subject to variations by inputting parameter factors such as subjective judgements, cognitive biases and measurement errors [35]. To assess the robustness of rankings, weights were varied systematically (±10–20%) to reflect potential subjectivity and uncertainty. TOPSIS was re-applied to evaluate changes in alternative preference order, and lastly, to identify critical criteria influencing rankings were assessed to ensure stability of results and participatory evaluation.

3.2.2. Stakeholder Validation and Participatory Decision-Making

Following the TOPSIS ranking and sensitivity analysis, the stakeholders reviewed the alternative rankings in a workshop, reflecting on trade-offs between authenticity, sustainability, and functional objectives. This iterative feedback allowed refinement of criteria, weights, and final selection, enhancing social acceptance and legitimacy of the chosen adaptive reuse solution.

3.2.3. Why the Choice of TOPSIS Method and the Multidimensional Evaluation Framework

Different fields of scientific research have employed TOPSIS as a MCDA method to support decision-makers between different alternatives of specific projects [41]. Given the characteristics of available data available in the different phases, (i.e., qualitative and quantitative), the objectives and the aim, TOPSIS evaluation method is considered as ideal. It allows for comparison of the different alternatives using both qualitative and quantitative data. It also effectively supports the evaluation of multiple adaptive reuse alternatives across diverse criteria. Besides these, it also combines quantitative and qualitative information, allows stakeholder participation, and produces clear, reproducible results. Furthermore, it enables one to arrive at an unbiased conclusion regarding subjective indicators such as cultural values regeneration, as compared to other quantifiable criteria and indicators related to specific environmental impacts or economic performances.

4. Results

4.1. Proposed Architectural Alternatives Description

• Alternative 1: Differential (new prevailing over old):

In this proposed alternative 1, a new architectural proposal prevailed over historic outlook for Egbo Egbo Bassey house (see Figure 8 and Figure 9). The proposed alternative presents a hybridized architectural form that synthesizes traditional gabled roof with contemporary volumetric expressions. The foundation is constructed from concrete, while the building envelope for the ground floor retains the existing galvanized zinc material. In contrast, the upper floor employs a lightweight material system with extensive use of glazed curtain walls framed in blackened steel. The building is to be kept empty without any use and function. However, the building can be visited by tourists who will be granted access to the entire facility.

• Alternative 2: Continuity (minimal intervention)

Alternative 2 maintains the distinctive colonial architectural form with layers of modifications. This alternative mirrors the historical images of the building in 1959. It features perfectionist plan configuration with typical neo-classic balance and proportion. The roof structure is characterized by steeply pitched gables (see Figure 10 and Figure 11). A key feature is the prominent central section containing an upper-level veranda or balcony, which is adorned with decorative elements such as spindled balusters and arched wooden trim.

The construction materials of the ground floor retain the same galvanized zinc material, and the first floor also retains the wooden panel wall material. The existing doors and Victorian-style-stained windows are retained on the first floor. Largely, the existing spatial configuration, morphology and dimension are maintained. For the proposed use and function, the building is to be used solely as a family house of the Egbo Egbo Bassey descendant and the Ekpo Abasi Royal House.

• Alternative 3. Cultivation (stratified dialogue):

In alternative 3, the history of the building is seen as an open-ended and layered historical past. Therefore, the 1886 building architectural outlook was reinvented and maintained (see Figure 12 and Figure 13). The proposal is built on the same classical geometry order from the Renaissance but implemented in a perfectionist manner and accomplished in using modular neo-classicist approach.

The construction materials of the ground floor retain the same galvanized zinc material. On the other hand, the first floor also retains the wooden panel wall material. The existing doors and Victorian-style stained windows are retained on the first floor. In terms of space morphology, largely, the existing spatial configuration, morphology and dimension are also maintained in this alternative. The building is proposed to be a museum and a community library.

• Alternative 4. Optimization (idealized restoration):

The alternative is developed on the philosophy that historic architecture is a repository of history. The proposed building design presents a deliberate hybrid character, where the original pitched-roof volume remains visually dominant while a contemporary glazed envelope wraps roughly half of the structure. Materially, the design combines contemporary and existing fabric to create a clear layering effect (see Figure 14 and Figure 15). The retained elements remain legible through the continued use of wooden panels on the first floor and zinc sheets on the ground floor, ensuring continuity with the building’s original material language while clearly expressing the newer intervention in contrast. This proposal aims to reuse the building as a museum.

4.2. Objectives, Indicators and Criteria

The following are the objectives thematically analyzed from the outcomes of the two rounds of questionnaires administered in step 2 of Phase 1. As shown in

Table 1. Final objectives, criteria, indicators and evaluation scales for adaptive reuse of abandoned and dilapidated wooden heritage.

Dimension	Objective (No.)	Criteria	Indicator Description	Evaluation Scale
Heritage Continuity	1. Safeguard and transmit the material authenticity of wooden and zinc fabric	1.1 Structural soundness of timber and zinc materials	1.1.1 Share of primary timber members (posts, beams, trusses) retained after intervention	Cardinal (%) of original building material retained
			1.1.2 The existing functional characteristics of the wooden members are retained	Cardinal (%) of original building material characteristics retained
		1.2 Functional compatibility with heritage values	1.2.1 Compatibility of new uses with character-defining wooden features (joinery, finishes, spatial order)	Ordinal (5-point expert panel)
	2. Revitalize knowledge of local wooden-building traditions	2.1 Community wooden heritage craft literacy	2.1.1 Participation rate in heritage carpentry demonstrations linked to the project	Ordinal (5-point expert panel)
	3. Valorize intangible carpentry heritage	3.1 Narrative interpretation and storytelling regarding values of carpentry heritage	3.1.1 Quality and depth of interpretation of timber craft (exhibits, signage, digital media)	Ordinal (5-point expert panel)
Social Cohesion	4. Strengthen social capital through reuse	4.1 Inclusivity breadth in the restoration process and reuse of building	4.1.1 Diversity of user groups (age, gender, ability) engaged in building construction	Cardinal (% diversity index)/Ordinal (5-point expert panel)
		4.2 Neighbourhood activity activation	4.2.1 Activation of community activities in the building construction process and building usage	Ordinal (5-point expert panel)
		4.3 Co-creation intensity	4.3.1 Stakeholders acting as co-producers (community artisans, school participants)	Ordinal (5-point expert panel)
Circular and Creative Economy	5. Stimulate local wood-based entrepreneurship	5.1 Job creation	5.1.1 Direct jobs created by the adaptive reuse (operation + maintenance + monitoring)	Cardinal (number of jobs)
		5.2 Leveraged local co-financing	5.2.1 Ratio of local/private contributions to total project cost	Local contribution (in Euros)
	6. Financial Viability	6.1 Economic value of proposal	6.2 Financial sufficiency and returns	Economic value (in Euros)
		6.1.1 Net Cost of Restoration	6.2.1 Payback period	In number of years
Access and Environmental Resilience	7. Improve universal access and urban connectivity	7.1 Physical and urban accessibility	7.1.1 Accessibility of interior and public interface (ramps, lifts, wayfinding; compliance with standards)	Ordinal (5-point expert panel)
	8. Increase operational energy self-reliance	8.1 Energy self-sufficiency and demand reduction	8.1.1 Share of annual electricity from on-site renewables energy	Ordinal (5-point expert panel)
			8.1.2 Reduction in final energy use versus pre-intervention baseline	Cardinal (kWh/m2·yr)/Ordinal (5-point expert panel)
	9. Reduce resource consumption and environmental impacts	9.1 Water efficiency	9.1.1 Reduction in potable water use via recovery/reuse systems	Cardinal (% reduction)
		9.2 Bio-/nature-based components	9.2.1 Area of green roofs/walls, rain gardens, or permeable vegetated surfaces delivered	Cardinal (m2)
		9.3 Timber reuse and waste avoidance	9.3.1 Mass of construction/demolition waste avoided through salvage and reuse of wood	Ordinal (5-point expert panel)
		9.4 Life cycle carbon reduction	9.4.1 Reduction in whole-life GHG emissions compared with a code-compliant new build	Cardinal (kgCO2e/m2 or %)
	10. Regenerate biocultural assets	10.1 Habitat and urban biodiversity	10.1.1 Area of new/restored habitat and biocultural features (e.g., bat boxes, native planting)	Cardinal (m2)

, the objectives were thematically grouped, and the evaluation scale was used for the analysis.

The selection of criteria and indicators was done by drawing on similar studies in the context of cultural heritage adaptive reuse. Specific publications on indicator-based adaptive reuse on colonial wooden heritage in post-colonial Africa remains scarce. For this reason, the criteria and indicators were deduced and adapted based on publications such as [24,42,43]. It is important to mention that these publications were done in different contexts; nonetheless, the criteria and indicators were valuable as a basis for adaptation in this project. Furthermore, the Venice Charter [9], particularly, core principles that govern authenticity in restoration according to Articles 9–11 (e.g., minimal intervention and identifiability) were also drawn upon for selection of comparison indicators. In the end, a total of 20 indicators were retrieved and adapted to the context of the case study at hand. The selected indicators were also compared to the information received during workshop and their significance for the assessment in the context of the adopted dimensions, namely: heritage continuity, social cohesion, circular and creative economy and access and environmental resilience.

The heritage continuity indicators are necessary to assess material authenticity, craftmanship valorization and transmission (both tangible and intangible). Some indicators may overlap (e.g., proportion of timber components preserved and authenticity of other architectural heritage materials). The distinction is necessary owing to the vast variation in materials in the building, for example, the McFarlane steel columns, the Corinthian order columns, the wrought iron railings and other cast-iron decorative elements. The main building envelopes timber remains; the vertical structural elements are steel columns while the decorative elements range from glass to other materials such as Plaster of Paris (POP). Therefore, a distinction is made between the timber component and the other architectural heritage materials.

On the other hand, social indicators are aimed at social targets and goals. These indicators also enable the evaluation of the social impact of the interventions in the different alternatives. Such indicators include access to social services, inclusion of citizens and people, participation in construction process, and increase in quality of life and well-being. Furthermore, circular and creative economic indicators are necessary to determine the self-sustainability and Financial Viability of the proposed adaptive reuse options. Also, it is used to assess the potential contribution of the different partners to the proposal through local co-financing. Lastly, the environmental indicators are used to compare energy usage and reliance, greenhouse gases emission, material consumption, biodiversity loss, pollution among others.

Both qualitative and quantitative scale and units were used to evaluate these indicators (see Appendix B for the complete data on the four alternatives). Qualitative indicators were expressed using a five-point scale, while quantitative indicators were expressed through diverse units of measure (based on [24]).

Step 2: Prioritization of the Objectives

To analyze the stakeholder’s prioritization of the objectives, Simos method was applied. This participatory card-ranking technique transforms ordinal rankings provided by stakeholders into normalized cardinal weights, enabling quantitative integration into the subsequent Multi-Criteria Decision Analysis [27,28].

Table 2. Normalized weights of the ten objectives derived from the Simos method.

Objective	Score	Weight
1. Safeguard and transmit the material authenticity of wooden and zinc fabric	8.40	0.153
2. Revitalize knowledge of local wooden-building traditions	6.08	0.111
3. Valorize intangible carpentry heritage	5.61	0.102
4. Strengthen social capital through reuse	6.16	0.112
5. Stimulate local cooperation and independent financing	4.31	0.078
6. Financial Viability	6.12	0.111
7. Improve universal access and urban connectivity	3.63	0.066
8. Increase operational energy self-reliance	4.68	0.085
9. Reduce resource consumption and environmental impacts	6.01	0.109
10. Regenerate biocultural assets	4.00	0.073

presents the score and weights of each objectives following Simos approach (see Appendix A for the complete computation process).

The data shown in Table 2 above shows that “safeguard and transmit the material authenticity” has the highest weight (0.153), which implies it was considered as the most important objective. This underscores stakeholders’ interest in preserving the material integrity of the building. Furthermore, “strengthening social capital” and “revitalizing local carpentry knowledge,” which are socially oriented objectives, weighted considerably. This also reflects the recognition of intangible heritage values and community identity. Other objectives such as the financial and environmental objectives weighted moderately, connoting a balanced consideration of environmental and economic priorities. “Regenerating biocultural assets,” received the lowest weight. This implies that while ecological regeneration was considered important, it was identified as a lesser concern in the immediate reuse context. These derived weights were used as the quantitative foundation for the TOPSIS evaluation which followed. This is to ensure that the final ranking of reuse alternatives is informed by the stakeholder priorities across social, cultural and environmental sustainability dimensions.

4.3. TOPSIS Evaluation Results

The analysis of all four proposed adaptive reuse alternatives using TOPSIS incorporated the weighted objectives derived from the Simos procedure. TOPSIS analysis allows for multi-criteria assessment by deciding each alternative’s distance from the Negative Ideal Solution (NIS) and the Positive Ideal Solution (PIS). Based on these distances, the calculation of the Closeness Coefficient (CC) is possible, thereby presenting the degree to which each alternative is closer to the ideal solution. Stronger alignment with desired objectives is determined through higher CC value across all the authenticity and sustainability dimensions.

The results of the TOPSIS evaluation are presented in

Table 3. TOPSIS evaluation results by alternatives.

Alternative	S+ (Distance to PIS)	S− (Distance to NIS)	Closeness Coefficient (CC)	Rank
Continuity	0.1675	0.2097	0.5560	2
Cultivation	0.1331	0.2656	0.6662	1
Differential	0.2589	0.1294	0.3332	4
Optimization	0.2656	0.1331	0.3338	3

below. This includes the calculated distances to the NIS and PIS, related CC values, and the final ranking of the four alternatives. As shown by the data presented in Table 3, the S⁺ and S⁻ represent the Euclidean distances of each alternative from the Positive Ideal Solution (PIS) and Negative Ideal Solution (NIS), respectively [44]. The data demonstrates that Cultivation attained the highest CC value (0.6662). This is the closest alignment with the ideal sustainability and authenticity objectives. This was closely followed by the Continuity alternative with a moderate CC value (0.5560). Optimization and Differential alternatives scored lower (0.3338 and 0.3332, respectively). These results demonstrate that the Cultivation alternative balances community engagement, cultural preservation and environmental efficiency.

Comparison of TOPSIS Scores and Stakeholder Preferences

A comparison was conducted between the TOPSIS-derived CC scores and stakeholder preference rankings to validate the analytical outcomes. To ensure direct comparability, the stakeholder rankings were rescaled. The higher values represent stronger preference. This was done to determine the degree of alignment between the TOPSIS results and stakeholder expectations. This provided an additional verification layer to determine if the stakeholder values are accurately reflected in the results of the multi-criteria decision process. The result of the comparative analysis is shown in Figure 16. The results indicate a correlation between the stakeholder preferences and TOPSIS evaluation outcomes. Cultivation approach was ranked as the preferred alternative in both cases. This was closely followed by Continuity, Optimization, and Differential, respectively. This confirms consistency with the stakeholder perceptions and aligns closely with the quantitative evaluation. This also validates the robustness and participatory relevance of the assessment framework.

4.4. Sensitivity Analysis

A sensitivity analysis was conducted to determine the robustness of the TOPSIS evaluation. This was done by perturbing the objective weights by ±10% and ±20% from their original Simos-derived values. This step aimed to test whether small changes in stakeholder-assigned priorities would significantly influence the ranking of adaptive reuse alternatives. Sensitivity analysis serves two key purposes: (a) to verify the stability of the multi-criteria decision results under varying weight assumptions and (b) to confirm that stakeholder-driven preferences do not overly bias the final ranking outcomes. Specifically, it aims to determine whether the Cultivation approach, which is the top-ranked alternative in the baseline scenario, maintains its leading position when input weights fluctuate. The results of this sensitivity analysis are presented in

Table 4. Sensitivity analysis of TOPSIS Closeness Coefficient under ±10% and ±20% weight perturbation.

Perturbation	Continuity	Cultivation	Differential	Optimization
−20%	0.4300	0.4851	0.3381	0.3124
−10%	0.4300	0.4851	0.3381	0.3124
0%	0.4300	0.4851	0.3381	0.3124
10%	0.4300	0.4851	0.3381	0.3124
20%	0.4300	0.4851	0.3381	0.3124

. The table also shows Closeness Coefficients for each alternative under ±10% and ±20% perturbation of objective weights. The Closeness Coefficients for all four alternatives across five weight perturbation levels (−20%, −10%, 0%, +10%, and +20%) are also illustrated in Table 4.

The results reveal that Cultivation consistently achieved the highest Closeness Coefficient across all scenarios, followed by Continuity, while Differential and Optimization remained the lowest ranked alternatives. These results imply an unchanged ranking pattern even under moderate variations in stakeholder priorities.

The results in Figure 17 also demonstrate that the rankings remain consistent under these perturbations. Minimal fluctuation in the Closeness Coefficients is demonstrated in the line plot across all perturbation levels. This confirms the robustness of the multi-criteria decision-making (MCDA) results. The Cultivation alternative remains the highest-performing alternative in every case. This underscores its balance between authenticity and sustainability objectives.

The robustness of the MCDA results is confirmed by the line plot which demonstrates that rankings are stable across ±20% weight variations. The top-ranked alternative remains the Cultivation approach in all scenarios. This highlights its superior performance across sustainability and authenticity criteria.

Individual Evaluation of Indicators per Alternative

Further examination was conducted to explore the distributional trends of the indicator-level weighted scores to identify patterns of strength and weakness across the four proposed alternatives. The distribution of indicator weights per alternative is illustrated in boxplot in Figure 18. This Figure 18 illustrates how the individual indicators contribute to the overall heritage authenticity and sustainability outcomes.

The results in Figure 18 demonstrate that the Cultivation alternative remains the most consistent and balanced alternative. It demonstrates the distribution of weighted indicator values, with a relatively high median and narrow interquartile range. On the other hand, Continuity demonstrates a slightly wider distribution. This suggests variability in how its indicators contribute to the overall performance. Furthermore, both the Differential and Optimization alternatives show lower median values and clusters tightly near the lower bound. This indicates narrow contribution to the key sustainability objectives.

The results visualized in Figure 18 are derived from data presented in

Table 5. Score evaluations for all the 20 indicators across all the alternatives.

Indicator No.	Indicator Name	Continuity	Cultivation	Differential	Optimization
1.1.1	Share of primary timber members (posts, beams, trusses) retained after intervention	0.1	0.1	0.04	0.03
1.1.2	The existing functional characteristics of the wooden members are retained	0.1	0.1	0.04	0.04
1.2.1	Compatibility of new uses with character-defining wooden features (joinery, finishes, spatial order)	0.09	0.11	0.04	0.04
2.1.1	Participation rate in carpentry demonstrations linked to the proposal	0.07	0.08	0.02	0.02
3.1.1	Quality and depth of interpretation of timber craft (through restoration and new construction)	0.06	0.08	0.02	0.02
4.1.1	Diversity of user groups (age, gender, ability) engaged in building construction	0.08	0.08	0.02	0.02
4.2.1	Activation of community activities in the building construction process	0.08	0.08	0.02	0
4.3.1	Stakeholders acting as co-producers (community orgs, artisans, schools)	0.08	0.08	0.02	0.02
5.1.1	Direct jobs created by the adaptive reuse (operation + maintenance + monitoring)	0.04	0.06	0.01	0.01
5.2.1	Ratio of local/private contributions to total project cost	0.04	0.07	0	0
6.1.1	Net Cost of Restoration	0.09	0.11	0.03	0.02
6.2.1	Payback period	0.07	0.11	0.01	0.01
7.1.1	Accessibility of interior and public interface (ramps, lifts, wayfinding; compliance with standards)	0.04	0.04	0.02	0.02
8.1.1	Share of annual electricity from on-site renewables or renewable PPAs	0.06	0.06	0	0
8.1.2	Reduction in final energy use versus pre-intervention baseline	0	0	0	0
9.1.1	Reduction in potable water use via recovery/reuse systems	0	0	0	0
9.2.1	Area of green roofs/walls, rain gardens, or permeable vegetated surfaces delivered	0	0.11	0	0
9.3.1	Mass of construction/demolition waste avoided through salvage and reuse of wood	0.08	0.08	0	0
9.4.1	Reduction in whole-life GHG emissions compared with a code-compliant new building	0	0	0	0
10.1.1	Area of new/restored habitat and biocultural features (e.g., bat boxes, native planting)	0	0.07	0	0

and

Table 6. Top-contributing indicators and best-performing alternatives by objective.

Objective	Top-Contributing Indicator	Highest Weighted Value	Best-Performing Alternative	Interpretation
Safeguard and transmit the material authenticity of wooden and zinc fabric	Feature compatibility	0.109 (Cultivation)	Cultivation	Strong emphasis on compatible material integration and preservation of authentic wooden fabric.
Revitalize knowledge of local wooden-building traditions	Carpentry participation	0.084 (Cultivation)	Cultivation	High engagement of artisans and local trainees reflects cultural transmission of craftsmanship.
Valorize intangible carpentry heritage	Craft interpretation	0.078 (Cultivation)	Cultivation	Effective narrative and interpretive reuse of traditional carpentry techniques.
Strengthen social capital through reuse	Community activation	0.078 (Cultivation and Continuity)	Cultivation/Continuity	Active community participation and social inclusion during the reuse process.
Stimulate local cooperation and independent financing	Local contribution	0.070 (Cultivation)	Cultivation	Greater reliance on local/private co-financing enhances project ownership.
Financial Viability	Payback period	0.111 (Cultivation)	Cultivation	Balanced economic return and cost recovery potential ensure long-term feasibility.
Improve universal access and urban connectivity	Accessibility	0.043 (Cultivation and Continuity)	Cultivation/Continuity	Both alternatives perform equally, showing consistent attention to inclusive design.
Increase operational energy self-reliance	Renewable energy share	0.060 (Cultivation and Continuity)	Cultivation/Continuity	Renewable energy integration remains moderate but balanced.
Reduce resource consumption and environmental impacts	Green surfaces	0.109 (Cultivation)	Cultivation	Cultivation excels in integrating green infrastructure and waste reuse strategies.
Regenerate biocultural assets	Habitat restored	0.073 (Cultivation)	Cultivation	Incorporates ecological and cultural restoration features (habitat and biodiversity).

. The Cultivation alternative continues to dominate as the best-performing alternative across eight of the ten objectives. This confirms its strong interaction between Economic Feasibility, material authenticity, and community engagement. The Continuity alternative demonstrates comparable performance in objectives such as accessibility and social inclusion. This aligns with its conservative preservation approach.

4.5. Sustainability Dimension

The following are the objectives thematically analyzed from the outcomes of the two rounds of questionnaires administered in step 3 of Phase 1. As shown in

Table 7. Sustainability dimensions, themes, indicators and supporting literature.

Sustainability	Categories/Factors/Themes	Indicators	Supporting Literature
Economic sustainability	Financial Viability and business model	1.1 Project net present value (NPV) (cost criterion)	[45]
		1.2 Payback period (cost criterion)	[45]
	Market activation and mixed-use intensity	1.3 Annual revenue diversification index	[46]
	Local value chains and procurement	1.4 Share of spend to local timber/heritage SMEs	[47]
	Employment and enterprise	1.5 Direct jobs created (operation + heritage programming)	[48]
	Risk and financial resilience	1.6 Debt-service coverage ratio (DSCR)	[49]
Environmental sustainability	Energy performance of timber building	2.1 Reduction in final energy use vs. pre-intervention (cost criterion)	[50]
	On-site renewables/self-sufficiency	2.2 Share of annual electricity from renewables	[51]
	Timber conservation and fabric retention	2.3 Percentage of primary timber members retained	[52]
	Material circularity (wood salvage and reuse)	2.4 Mass of salvaged timber reused on site	[53]
	Construction and demolition waste diverted	2.5 C&D waste diversion rate	[54]
	Water performance	2.6 Potable water reduction via reuse/recovery	[55]
	Whole-life carbon	2.7 Life cycle GHG emissions (cost criterion)	[56]
	Nature-based solutions and biodiversity	2.8 New/rehabilitated green area and habitat features	[57]
Social sustainability	Inclusion and equitable access	3.1 Diversity of users/beneficiaries	[58]
	Health, safety and comfort	3.2 post-occupancy comfort and perceived safety	[59]
	Accessibility and connectivity	3.3 Universal access compliance	[60]
	Community engagement and co-production	3.4 Stakeholders acting as co-producers	[61]
	Education and skills	3.5 Heritage carpentry apprenticeships/training	[62]
Cultural sustainability (heritage)	Material authenticity of wooden fabric	4.1 Compatibility of interventions with character-defining timber features	[55]
	Intangible heritage and craft continuity	4.2 Depth/quality of interpretation of carpentry traditions	[63]
	Reversibility and minimal intervention	4.3 Proportion of reversible additions	[9,64]
	Fit-for-purpose (use–heritage coherence)	4.4 Functional compatibility score	[65]

, the objectives were thematically grouped, and the evaluation scale was used for the analysis.

Therefore, the performance of the four adaptive reuse alternatives was examined across four key sustainability dimensions, i.e., Ecological Friendliness, Cultural Sensitivity, Social Viability and Economic Feasibility. The purpose is to identify trade-offs, determine how each alternative contributes to balanced sustainability outcomes and assess the robustness of these dimensions under varying conditions.

4.5.1. Relative Contribution Across Sustainability Dimensions

As illustrated in Figure 19, the Cultivation alternative scores highest consistently across nearly all sustainability dimensions. Particularly, for Ecological Friendliness it scores 0.86, and for Economic Feasibility it scores 0.820. Furthermore, the Continuity alternative performs better in the realm of Social Viability by scoring (0.676), and scores 0.616 in Cultural Sensitivity. This indicates its affinity for social cohesion and heritage-preservation. On the other hand, the Differential and Optimization alternatives show comparatively lower contributions, demonstrating strategies that emphasize selective interventions or efficiency optimizations over holistic sustainability gains.

4.5.2. Comparative Weights of Criteria by Sustainability Dimension

How the individual sustainability dimensions contribute to each alternative’s total score is demonstrated in Figure 20. The comparative bar plot further clarifies that Cultural Sensitivity and Social Viability have relatively balanced weight distributions across the alternatives (≈ 0.61–0.70). On the other hand, Ecological Friendliness shows greater disparity. It rises under Cultivation, with a score of 0.865 but dropping to 0.063 under Optimization.

According to the data shown in Figure 20, the Cultivation alternative integrates ecological design principles through the usage of bioclimatic features and energy-efficient materials without compromising social or cultural aspects. On the other hand, the Optimization alternative tends to marginalize ecological values while emphasizing efficiency gains.

4.5.3. Sensitivity of Overall Sustainability Rank by Dimension

How ±20% variations in dimension weights influence the composite sustainability scores was demonstrated through a sensitivity plot test. The results shown in Figure 21 indicate that Cultural Sensitivity (mean = 0.453) and Social Viability (0.418) are the most stable dimensions. Furthermore, Ecological Friendliness with the score of 0.376 shows greater volatility. This validates the robustness of the MCDA results; that is, even under moderate weight changes, the relative rankings of alternatives remain unchanged. Therefore, the sustainability performance of Cultivation and Continuity is not an artefact of weight bias; rather, they reflect the strengths in community engagement and heritage retention.

4.5.4. Sustainability Composition of Each Adaptive Reuse Alternative

The internal sustainability composition of each alternative is depicted in Figure 22. The results demonstrate that Cultivation maintains the most balanced structure. It shows relative shares across all four dimensions: ecological = 30%, cultural = 20%, social = 25%. and economic = 25%). Continuity demonstrates more affinity for Social Viability (32%), while Optimization leans more toward cultural (41%) and economic (19%) performances.

How each adaptive reuse strategy negotiates trade-offs among sustainability pillars was provided by this composition analysis. It further buttresses how the Cultivation alternative offers the most integrated model, as it combines ecological efficiency and Economic Feasibility with community engagement and cultural authenticity.

5. Discussion

The MCDA-TOPSIS evaluation of the adaptive reuse alternatives shows that the Cultivation alternative performs better than the other three alternatives—Continuity, Optimization and Differential. This buttresses some of the existing arguments in the literature; for example, [66,67] argued that best adaptive reuse alternatives are those which benefits community participation and engagement and promotes integration of both cultural and social values. The Cultivation alternative contributes significantly to existing material retention (as expressed in indicator 1.1.1), it ensures local carpentry participation (as expressed in indicator 2.1.1), as well as ensuring that interventions are compatible with existing historical features (as expressed in indicator 1.2.1).

From the point of view of sustainability also, the Cultivation adaptive reuse alternative also demonstrated the best performance across the different sustainability dimensions, that is: Ecological Friendliness, Cultural Sensitivity, Social Viability and Economic Feasibility. First, it is more socially viable as demonstrated by its total score of 0.709 under this panel of sustainability. This reflects robust community participation, co-restoration actions and encourages users’ diversity. This is illustrated in indicators 4.1.1, 4.2.1 and 4.3.1. Second, this alternative is the most culturally sensitive. This is demonstrated by its total score of 0.708. This score was achievable by its contributions across cultural indicators such as retention of original timber elements and feature compatibility, which was in robust alignment with the preservation of material and intangible heritage. Third, this Cultivation adaptive reuse alternative was the most economically feasible. This is also demonstrated by its highest rank of 0.820. This was possible through its contributions to local/private economy, better cost efficiency and an improved payback period. Lastly, the Cultivation alternative achieved the highest score—0.865—in the context of Ecological Friendliness. This was demonstrated through its adoption of renewable energy sources, inclusion of green surfaces, and through waste reduction (as expressed in indicators 8.1.1, 9.2.1, 9.3.1). Thus, this further suggests that adaptive reuse strategies that incorporate ecological considerations often outperform alternatives with only conservative approaches.

However, despite the performance of the Cultivation approach across all criteria, objectives and all sustainability indicators, there were some specific trade-offs. There were cultural and social value preferences versus lower technical optimization. Two of the other alternatives, Differential and Optimization, demonstrated technical efficiency but were generally poorer in the context of community engagement and heritage authenticity preservation [67,68]. This demonstrates the tension between preservation of socio-cultural values and technical–economic optimization. Therefore, while the Cultivation alternative integrates green infrastructure and renewable energy sources, these considerations can lead to an increased total cost of construction. The trade-offs realized in this study further prove the values of MCDA tools, as it helps highlight the strength and weaknesses of each of the evaluated adaptive reuse alternatives. Thus, this provides a basis for re-consideration and possibility for proffering potential means of ensuring balance between strategies.

Furthermore, drawing on Article 9 of the Vernice Charter [9], the Cultivation alternative prioritizes the minimal intervention and identifiability through the retention of the original timber, zinc and other decorative elements used in the monument. On the other hand, the Continuity alternative retains the palimpsest intervention over the years, albeit with non-compatible interventions. By contrast, the Differential and Optimization alternatives demonstrate the strongest contrast against the Venice Charter principles by being completely distinguishable to the historical baseline.

The result of this paper further reinforces the existing positions in a recent body of works on MCDA in adaptive reuse contexts [69,70,71,72]. In the African context, however, the result of this paper contributes to an under-research domain of colonial wooden heritage in Africa, thereby invigorating the incremental value of the study in international scholarly contexts.

Recent studies from China and Macau demonstrate that adaptive reuse alternatives that are embedded with more social functions may be preferable to those with more affinity for stronger technical considerations [73,74]. Comparative results in Africa, for example in Egypt and broader cross-regional studies, demonstrate that adaptive reuse rankings are driven by how the weights are distributed across the economic panel versus environmental and socio-cultural criteria [75,76]. Therefore, situating the Egbo Egbo Bassey house adaptive reuse results within these contexts allows one to deductively argue the Cultivation alternative, which favours socio-cultural and heritage criteria, aligns with the broader international trend in adaptive reuse. The Cultivation alternative is a heritage conservation-friendly and socially acceptable alternative which outperforms the more technically viable alternatives.

Finally, based on the results, the Cultivation adaptive reuse alternative is positioned as the recommended alternative for the studied National Monument—Egbo Egbo Bassey house. Through the evaluation of its performance across all objectives, criteria, indicators and sustainability panels, the results demonstrate that; first, the Cultivation alternative attained the highest weighted TOPSIS Closeness Coefficient value—0.666. Second, across the sustainability dimensions, it outperformed the other alternatives. That is, it ensures the appropriate balance between Cultural Sensitivity, Ecological Friendliness, economic viability and social acceptability. Third, the correlation analysis also proves that the TOPSIS evaluation results were in tandem with stakeholder preferences. This confirms both social acceptability and technical feasibility. Lastly, through the sensitivity analysis conducted, the ranking of the Cultivation alternative remains stable despite the ±20% weight perturbation.

6. Conclusions

This study adopted a MCDA approach, specifically the TOPSIS method for the evaluation of four proposed adaptive reuse alternatives for an abandoned and dilapidated National Monument of Nigeria—the Egbo Egbo Bassey house in Old Calabar, Nigeria. The adaptive reuse alternatives, namely—Continuity, Cultivation, Differential and Optimization were conceptually developed based on the Ellen Braae [38] approach. This approach argues that adaptive reuse is a means to view architecture as a medium that can be altered and is always in transition [38,39]. By drawing on objectives, criteria and indicators developed by stakeholders, the alternatives were compared using an MCDA method, with the view of selecting the most appropriate adaptive reuse strategy for the dilapidated architectural heritage. The analysis thereby incorporated 20 indicators across specific objectives, as well as the four pillars of sustainable development.

The results demonstrated that the Cultivation alternative was the closest to the ideal adaptive reuse strategy for the National Monument. This was highlighted through its performance in relation to indicators such as community participation, heritage authenticity retention, and material preservation, among others. It was also the most ecologically friendly, socially acceptable, culturally sensitive and economically viable. The robustness of the ranking of the Cultivation approach as the best alternative was also tested through a ±20% weight perturbation. This proves the value of MCDA methods in negotiating stakeholder preference in the processes of adaptive reuse strategies.

Based on the results from the analysis, this study thereby recommends the adoption of the Cultivation alternative as the adaptive reuse strategy for the studied National Monument. This recommendation is based on its closeness to being the ideal solution, as proven by its holistic integration of cultural, ecological, social and economic considerations. However, this study is aware of its limitations. For example, the analysis and conclusions are drawn based on 20 indicators. Further studies in the future could consider incorporating a wider spectrum of indicators and metrics, such as yearly carbon footprints assessment, social impact assessment and life cycle cost assessments, among others. Furthermore, environmental factors such as climate changes, and other factors such as urban development pressure could be incorporated, as these factors could affect the outcomes of the analysis. Lastly, future research could refine the adaptive reuse alternative development and incorporate a wider spectrum of options.