An Empirical Analysis of the Commercial Viability of Greenhouse Vegetable Farming in Ghana

Greenhouse agribusiness in Ghana: potential, constraints, and market context

Vegetable farming in Ghana is characterised by a dual structure: a large, predominantly smallholder open-field sector supplying domestic staple markets, and an emerging controlled-environment sector targeting premium urban, hotel, and export channels (Tuffour et al., 2024). The distinction is economically significant. Smallholder open-field production, which provides over 80% of Ghana's vegetable supply, operates on low margins, high price volatility, and substantial post-harvest losses (Aryeetey et al., 2021). Greenhouse production, by contrast, offers yield stability, quality consistency, and access to premium prices, but requires capital outlays that are orders of magnitude above the typical smallholder's capacity (MoFA, 2020).

The Akomadan–Afrancho corridor in the Ashanti Region has emerged as Ghana's most prominent greenhouse tomato zone, supported by favourable agro-climate, proximity to major markets (Kumasi, Techiman, Accra), and institutional backing from MoFA, GIZ, and USAID (Arimiyaw et al., 2020). However, the corridor's commercial greenhouse activity remains heavily constrained by: high capital costs for dome structures (predominantly USD-denominated imports); limited access to long-tenor agricultural credit; skills gaps in controlled-environment agronomy; and the absence of formal off-take agreements that stabilise revenue (MoFA, 2020; Henseler and Amoah, 2014).

Market conditions for premium greenhouse produce in Ghana are compelling. Imported greenhouse tomatoes from South Africa and Morocco retail at GH¢40–45/kg in Ghanaian supermarkets, compared to farm-gate prices of GH¢15–20/kg for open-field produce; sweet pepper and cucumber price premiums are similarly large (Henseler and Amoah, 2014). West Africa's regional markets, particularly Nigeria, Côte d'Ivoire, and Burkina Faso, exhibit seasonal supply gaps that Ghanaian greenhouse operators could profitably address. Accessing these markets, however, requires consistent quality, certification, and cold chain investment, all of which favour capital-adequate commercial enterprises over individual smallholders (Abdul-Rahaman et al., 2023; Meemken and Bellemare, 2020).

Financial risk in the sector is compounded by currency exposure (greenhouse structures are imported in USD), input cost inflation (12.1% per annum at the time of study), and land tenure fragility, approximately 70% of producers in the study area hold short-term rental agreements incompatible with the collateral requirements of formal agricultural credit (Alhola and Gwaindepi, 2024; Singirankabo and Ertsen, 2020). These structural factors substantially affect the risk-return profile of greenhouse investment and must be incorporated into any credible financial model.

Cooperatives and farmer-based organisations (FBOs) represent an important but underutilised institutional pathway for the adoption of greenhouse practices in Ghana. By pooling capital, sharing operational costs, and collectively negotiating off-take agreements, cooperatives can reduce the per-member investment threshold below the GH¢3.98 million level required for a full commercial-scale enterprise. The Power of Unity study by Donkor et al. (2025), published in the Agribusiness journal, demonstrates that collective action among smallholder farmers in West Africa significantly improves agricultural performance, productivity, and market access. In the Ghanaian greenhouse context, cooperative-based models would also mitigate land tenure fragility by enabling longer-term collective lease arrangements and strengthening bargaining power with lenders and input suppliers. However, cooperative greenhouse ventures face additional governance challenges, including equitable profit distribution, shared liability for loan repayment, and coordination of production schedules, constraints that must be accounted for in any financial appraisal. The present study models the single-investor enterprise as the primary analytical unit, as this represents the scale and ownership structure documented among existing commercial greenhouse operators in the study area. The implications for cooperative adoption are addressed in section Proposals.

Financial appraisal of agricultural enterprises: evidence and gaps

A growing body of agribusiness literature applies discounted cash flow (DCF) techniques to evaluate agricultural investment viability in developing-country contexts. Net present value (NPV), internal rate of return (IRR), and benefit-cost ratio (BCR) are the core tools, typically supplemented by payback period analysis and sensitivity modelling (Adams et al., 2019; Alam et al., 2022; Sánchez et al., 2022). For vegetable farming specifically, the evidence base spans multiple regions and enterprise types, but exhibits important gaps.

The broader international literature confirms that greenhouse and controlled-environment agriculture consistently generate superior financial performance relative to open-field systems when properly capitalised and market-linked. Maghdalia et al. (2022) found positive NPV and BCR > 1 for urban greenhouse vegetable systems in Indonesia with improved irrigation and market access. Sánchez et al. (2022), in a global meta-analysis, reported that diversified farming systems, including greenhouse production, consistently outperform monocultures in risk-adjusted profitability. Melvani et al. (2023) documented net income improvements of up to 40% for intensified vegetable systems in Sri Lanka relative to conventional alternatives. These findings are encouraging for the Ghanaian context but derive from different institutional, climatic, and financial environments; their direct transferability is limited.

In Ghana, Wongnaa et al. (2019) conducted a cost-return profitability analysis of urban exotic vegetable production in the Kumasi metropolis and found positive financial performance. However, their study employed simple accounting-period profit calculations without DCF discounting and did not apply NPV, IRR, or sensitivity analysis, limiting its value for long-term investment decisions. Tham-Agyekum (2023) extended this work to examine irrigation technique choice in urban vegetable farming, incorporating some financial metrics, but stopped short of comprehensive investment appraisal. Adzawla et al. (2022) evaluated smallholder agricultural viability across Ghana's savannah and transitional zones using econometric models but aggregated across crop types, thereby obscuring crop-specific financial dynamics. Abdul-Rahaman et al. (2023) examined agri-food system participation and technical efficiency among Northern Ghana's vegetable farmers, finding that market integration improves efficiency. However, they focused on technical rather than financial performance, and did not model post-harvest loss impacts on net returns.

Four specific gaps in the existing literature motivate this study. Firstly, no published investment appraisal applies the full toolkit of NPV, IRR, BCR, payback period, break-even analysis, and scenario-based sensitivity analysis to a greenhouse enterprise in Ghana. Secondly, existing financially oriented studies are parameterised using secondary benchmarks or single-source data rather than multi-respondent primary surveys, a methodological limitation in environments characterised by high production heterogeneity. Thirdly, the role of the debt moratorium structure (a feature of agricultural project finance in Ghana) in shaping the risk-return profile has not been explicitly modelled. Fourthly, and critically for policy design, the price sensitivity threshold, the minimum price level below which investment viability collapses, has not been quantified for greenhouse enterprises in Ghana. As documented above, Ghana's vegetable markets are characterised by severe seasonal price volatility (Wongnaa et al., 2019), and the absence of price stabilisation mechanisms or formal off-take arrangements has been identified as the primary institutional barrier to sustained investment in the sector (Henseler and Amoah, 2014; Meemken and Bellemare, 2020). Quantifying this threshold is therefore not merely an analytical exercise but a direct input into the design of minimum price support policies and contract farming frameworks. This study addresses all four gaps.

Description of study area

The study was conducted in the Akomadan-Afrancho corridor within the Offinso North District of Ghana's Ashanti Region, located between latitude 7.4°N and longitude 1.8°W at 250–400 m above sea level. The corridor lies within the forest-savannah transitional zone and is widely recognised as one of Ghana's most productive commercial vegetable belts. The annual rainfall of 1,000–1,300 mm is distributed across two cropping seasons (March–July; September–November), and perennial access to the Afram River supplemented by motorised borehole irrigation enables year-round production. Its proximity to major urban markets, Kumasi (75 km), Techiman (45 km), and Accra (250 km), and sustained support from MoFA, GIZ, and USAID make this corridor representative of high-potential commercial vegetable zones in Ghana. The district population is approximately 90,000, with over 60% engaged in agriculture (Aryeetey et al., 2021).

Data collection

Primary data were collected via a mixed-methods approach. Quantitative data were gathered through face-to-face structured surveys of 120 smallholder vegetable farmers selected by stratified random sampling. Stratification criteria were farming system (open-field vs. irrigated/proto-greenhouse), land tenure status (owned vs. rented), and gender to ensure representativeness. The sample size was determined using the Cochran (1977) formula for finite populations at a 95% confidence level and 5% margin of error. The survey instrument, adapted from Adams et al. (2019) and Tham-Agyekum (2023), was translated into Twi and piloted in Abofour captured input costs, crop yields, selling prices, labour requirements, post-harvest loss rates, and market access arrangements.

Qualitative depth was provided by ten (10) key informant interviews (KIIs) conducted with agricultural extension officers (MoFA), representatives of GIZ and USAID-funded programmes, cooperative leaders, greenhouse equipment suppliers, and principal market traders. Interviews followed a semi-structured guide covering policy environment, input supply chains, market dynamics, and credit access constraints. Additionally, structured field observations on 30 randomly selected farms during both cropping seasons validated self-reported input use and post-harvest loss estimates, where recall bias is well documented (Quansah et al., 2020). Secondary data sources included MoFA annual reports (2020–2023), AgMark and local market records (24-month price series), Ghana Living Standards Survey (GLSS 8), and district agricultural statistics.

The primary data from the 120 farmers and ten (10) key informants directly parameterised the financial model through an explicit mapping procedure: (i) average input cost data from farmer surveys (seeds, fertiliser, agrochemicals, labour, packaging, irrigation fuel) were used to construct the variable operating cost schedule; (ii) median crop yields reported by farmers (validated against field observations on 30 farms) established the yield benchmarks of 15 kg/m² for tomatoes and sweet peppers and 150 fruits/m² for cucumbers in the financial model; (iii) prevailing market prices recorded through the 24-month AgMark and local market price series, cross-checked against key informant quotes from traders and institutional buyers, set the baseline price parameters; (iv) post-harvest loss rates observed in field surveys (validated against Quansah et al., 2020) informed the effective output volume calculations; and (v) capacity utilisation trajectories (40% in Year 0, 80% in Year 1, 100% from Year 2) were derived from key informant interviews with operational greenhouse unit managers and extension officers, who confirmed this ramp-up pattern as representative of new installations in the corridor. Capital costs (CAPEX) were obtained from supplier quotations for greenhouse domes, pack house, and vehicles, rather than secondary estimates. The financial model thus represents a comprehensive, field-validated bottom-up construction rather than a hypothetical or desk-based benchmark.

Financial model structure

The enterprise model covers a commercial-scale 20-greenhouse production system on a 4.05-hectare site, growing tomatoes, sweet peppers, and cucumbers under controlled conditions. The 20-dome scale was selected based on three convergent criteria: (i) it represents the minimum viable scale at which capital costs per unit of output fall to a level consistent with positive NPV under Ghanaian market conditions, as confirmed by iterative sensitivity runs during model development; (ii) it matches the operational scale of the most financially active commercial greenhouse clusters documented during field surveys in the Akomadan–Afrancho corridor; and (iii) it aligns with the facility sizes typically financed by agricultural development banks and DFIs operating in Ghana, making the appraisal directly actionable for investment decision-making. Smaller configurations (5–10 domes) were tested during model construction but produced IRRs below the 25% hurdle rate, confirming that 20 domes represent a commercially meaningful lower bound for viable greenhouse agribusiness at this location. Each greenhouse dome has a gross area of 135 m² and an effective production area of 120 m². The enterprise is modelled as a private commercial agribusiness, owned and operated by a single investor or a small partnership of investors (consistent with the institutional structure of similar greenhouse ventures in the Akomadan–Afrancho corridor), and financed through a blended structure of equity and long-tenor bank debt. This ownership model is deliberately distinct from cooperative or smallholder-pooled arrangements; however, the financial parameters derived here are equally applicable to greenhouse cooperatives or outgrower schemes that aggregate capital across multiple members, and section Proposals discusses cooperative-based adoption pathways. The financial analysis period is six periods: one 12-month moratorium year (Year 0, no loan repayment, interest capitalised at 25% per annum) followed by five repayment years (Years 1–5). This six-period structure reflects the standard agricultural project finance facility structure used by commercial banks in Ghana at the time of the study (see Assumptions 12 and 13, Table 1). All financial projections are in nominal Ghana Cedis (GH¢), with an exchange rate of GH¢11 per USD (i.e., USD 1 = GH¢11) applied to imported capital equipment.

The project timeline for capacity utilisation is as follows: 40% in Year 0 (moratorium, learning curve); 80% in Year 1 (first repayment year); 100% from Year 2 onwards. This ramp-up was validated by field evidence from operational greenhouse units in the study area, consistent with the experience documented for comparable agribusiness ventures in Ghana (Adams et al., 2019). Revenue projections incorporate an annual price escalation of 10%, aligned with prevailing inflation and the premium positioning of greenhouse produce relative to open-field alternatives.

Analytical methods

Six complementary investment appraisal and risk analysis methods were applied:

• Net present value (NPV). The NPV discounts projected net cash flows at the 25% cost of capital over the five-year repayment horizon. A positive NPV indicates returns exceed the opportunity cost of capital.

  (1)

  $$\mathit{NPV}={\displaystyle {\sum }_{t=1}^n\frac{R_t-C_t}{{(1+r)}^t}-I_0}$$
  where R_t and C_t are revenues and operating costs in year t, r = 0.25, n = 5 repayment years, and I₀ is the total initial outlay of GH¢3,982,361.

• Internal rate of return (IRR). The IRR is the discount rate at which NPV equals zero. It is computed as follows:

  (2)

  $${\displaystyle {\sum }_{t=1}^n\frac{R_t-C_t}{{(1+\mathit{IRR})}^t}-I_0=0}$$
  where all other variables are as defined in equation (1). An IRR exceeding the 25% hurdle rate indicates that the project delivers returns above the cost of capital. The IRR also identifies the maximum financing cost that the project can sustain.

• Benefit-cost ratio (BCR). The BCR compares the present value of all discounted benefits to the present value of all discounted costs. BCR > 1 confirms economic efficiency and is the preferred metric for donor-funded programme evaluation and public-sector cost-effectiveness analysis (Alam et al., 2022).

• Payback period (PBP). The PBP measures the time from the start of operations (Year 0) to full recovery of the initial investment from cumulative net cash flows. The PBP for even (constant) cashflows is computed as

  (3)

  $$\text{PBP}=\frac{\text{Initial}\hspace{0.17em}\text{Investment}}{\text{Annual}\hspace{0.17em}\text{Net}\hspace{0.17em}\text{Cash}\hspace{0.17em}\text{Flow}}$$
  while that for uneven cashflows is computed as

  (4)

  $$\text{PBP}=\text{Year}\hspace{0.17em}\text{before}\hspace{0.17em}\text{full}\hspace{0.17em}\text{recovery}+\frac{\text{Unrecovered}\hspace{0.17em}\text{cost}\hspace{0.17em}\text{at}\hspace{0.17em}\text{start}\hspace{0.17em}\text{of}\hspace{0.17em}\text{the}\hspace{0.17em}\text{year}}{\text{Cash}\hspace{0.17em}\text{flow}\hspace{0.17em}\text{during}\hspace{0.17em}\text{recovery}\hspace{0.17em}\text{year}}$$

  The PBP is a simple and widely used indicator of liquidity and risk, particularly among risk-averse smallholder farmers, who prioritize quick returns (Wongnaa et al., 2019). However, as it does not account for cash flows beyond the payback period or the time value of money, it is a supplementary rather than a standalone tool.

• Break-even analysis (BEA). BEA determines the minimum revenue (in value and in units by crop) at which total revenues equal total costs. The break-even quantity for each crop is:

  (5)

  $$Q_{\mathit{BE}}=\frac{\mathit{FC}}{(\text{P}-\text{VC})}$$
  where FC = fixed costs, P = average selling price per unit, and VC = variable cost per unit.

• Sensitivity analysis (SA). SA applies ±10% and ±20% shocks to selling prices and operating costs, individually and jointly, to evaluate how adverse market conditions affect NPV, IRR, and BCR. It identifies the price threshold below which the project becomes non-viable, a key parameter for minimum price support policy design.

Capital cost structure

The full capital and set-up cost structure is presented in Table 2. Total project cost is GH¢3,982,361, of which greenhouse infrastructure (CAPEX) accounts for GH¢3,065,000 (77%) and working capital and site development for the remaining GH¢917,361 (23%). The dominant single item is the 20 greenhouse domes at GH¢2,200,000 (55% of total cost), which are USD-denominated imports and represent the enterprise's primary currency risk exposure. All cost items were derived from supplier quotations and field survey data rather than secondary benchmarks, ensuring the cost structure reflects actual market conditions in the Akomadan–Afrancho corridor at the time of the study. Table 2 provides the full line-item breakdown.

Revenue projections

Projected revenues reflect the six-period capacity ramp-up and annual price escalation of 10% (Table 3). In Year 0 (the 12-month moratorium period), the enterprise operates at 40% capacity, yielding revenues of GH¢1,244,160 from 74,880 total output units. This figure comprises 28,800 kg of tomatoes (20 domes × 120 m² × 15 kg/m² × 2 cycles × 40%), 14,400 kg of sweet peppers (20 domes × 120 m² × 15 kg/m² × 1 cycle × 40%), and 172,800 cucumber fruits scaled to their revenue-weighted unit equivalent (see Table 3 for full crop-by-crop breakdown). At 100% capacity (Year 2 onwards), total output reaches 187,200 units. In Year 1, capacity utilisation is estimated to be 80%, resulting in a revenue of GH¢2,737,152. Full capacity (100%) is reached from Year 2 onwards, with revenues growing from GH¢3,763,584 in Year 2 to GH¢5,009,330 by Year 5. The compound annual growth rate (CAGR) over the full six-period horizon (Year 0 to Year 5) is 41.6%, reflecting the capacity ramp-up effect. Once full capacity is reached in Year 2, the steady-state annual revenue growth is 10%, which is identical to the assumed price escalation rate. This distinction prevents misinterpretation of the CAGR as an underlying market growth rate.

Baseline prices are set at GH¢38.00/kg for tomatoes, GH¢50.00/kg for sweet peppers, and GH¢9.00 per cucumber fruit in Year 0, rising to GH¢61.20/kg, GH¢80.53/kg, and GH¢14.49/fruit, respectively, by Year 5. These prices are 5–10% below the prevailing imported greenhouse produce prices in Ghana's supermarkets (GH¢40–45/kg for imported tomatoes), providing a competitive advantage while preserving profitability. International market prices offer further upside, reinforcing the export diversification case.

Profitability

The profitability trend reflects the V-shaped trajectory characteristic of capital-intensive agribusiness enterprises structured around a loan moratorium. During the moratorium year (Year 0), the enterprise records a net loss of GH¢543,476. This loss results from the combination of below-capacity revenues (GH¢1,244,160 at 40% utilisation), full operating cost exposure, and GH¢996,912 in capitalised interest, a burden that underscores the importance of adequate working capital sizing before commissioning. This finding is consistent with the wider agricultural finance literature, which identifies capitalised interest during pre-revenue phases as a primary driver of start-up financial distress in developing-country agribusiness ventures (Adams et al., 2019).

By Year 1 (the first loan repayment year, 80% capacity), the enterprise returns to profitability, with profit before interest and tax (PBIT) of GH¢1,437,968 and net profit after tax of GH¢266,807. The V-shaped recovery is driven by the revenue step-change from 40% to 80% capacity, the five-year corporate tax holiday for agricultural ventures under Ghanaian law, and declining real debt service costs as the reducing balance loan is repaid. By Year 5 (full capacity, fifth repayment year), net profit after tax reaches GH¢2,810,772, a 955% improvement over Year 1, and the net profit margin rises from 10% to 56%. PBIT grows from GH¢1,437,968 in Year 1 to GH¢3,051,898 in Year 5. These results are consistent with comparable international evidence on the financial performance trajectory of commercial greenhouse enterprises (Sánchez et al., 2022; Maghdalia et al., 2022).

Total farm costs increased moderately from GH¢948,984 in Year 1 to GH¢1,406,385 in Year 5, driven by proportional increases in variable costs (seeds, fertiliser, packaging, labour) and stable depreciation charges. The cost trajectory confirms that operating leverage is high, fixed capital costs constitute the majority of total expenditure, meaning that revenue improvements flow disproportionately into net profit once the break-even revenue threshold is exceeded. Administrative expenses rise from GH¢350,200 in Year 1 to GH¢551,047 in Year 5, reflecting incremental staffing and overhead needs.

Liquidity

The enterprise's liquidity position strengthens dramatically over the projection period. Current assets rise from GH¢1.16 million in Year 1 to GH¢5.77 million in Year 5, driven by cash and cash equivalents growing from GH¢932,755 to GH¢5,351,029. Current liabilities remain minimal (GH¢38,016 to GH¢69,574), reflecting the enterprise's cash-sales model and conservative creditor payment policy. The current ratio consequently improves from 30.5:1 to 82.9:1, far exceeding the 2:1 benchmark for general business sustainability. These elevated ratios are characteristic of agribusiness enterprises operating on a largely cash-sales basis with minimal trade creditor obligations, a pattern documented in comparable Ghanaian agribusiness studies (Wongnaa et al., 2019). In the context of a development-stage enterprise managing active loan repayment, this exceptional liquidity reflects prudent working capital management and confirms the absence of short-term solvency risk throughout the projection period.

Investment appraisal

The study conducted an investment appraisal using the enterprise's five-year projected cash flows. A discount rate of 25% was chosen to account for the comparatively high cost of capital and perceived risks in Ghana's agriculture industry. At the 25% discount rate, the NPV of the enterprise is GH¢838,548 (positive), indicating that present-value returns exceed the initial capital outlay and the cost of capital. The IRR is 33%, substantially exceeding the 25% hurdle rate. The margin between the IRR and the hurdle rate is 33% − 25% = 8 percentage points, meaning the enterprise could sustain additional financing costs of up to 33% before becoming non-viable, providing a meaningful buffer against future interest rate increases. Furthermore, the BCR is 1.21, which confirms that every unit of discounted cost generates GH¢1.21 in discounted benefits. For donor-funded programme evaluators and development finance institutions assessing portfolio-level cost-effectiveness, the BCR result provides direct evidence of economic justification (Alam et al., 2022; Adzawla et al., 2022).

These metrics compare favourably with the agribusiness investment landscape in Ghana. For instance, Wongnaa et al. (2019) and Tham-Agyekum (2023) note that most comparable smallholder agricultural ventures in Ghana fail to achieve IRRs above 20%. Hence, the 33% IRR reported in this study positions the commercial greenhouse model as a high-performing investment within the sector. The strong financial performance is attributable to the premium price positioning of greenhouse produce relative to open-field alternatives, the tax holiday benefit, and the declining debt service trajectory as the reducing balance loan is repaid over five years.

The payback period is approximately 2.4 repayment years, or 3.4 years from project inception if the 12-month moratorium is included. Thus, full capital recovery occurs between 2 and 3 years. This relatively short recovery period, less than half the five-year repayment horizon, reflects the high revenue ramp-up from 40% to 100% capacity, making the enterprise financially attractive even to risk-averse investors who prioritise capital liquidity.

Break-even analysis

The break-even analysis determines the minimum revenue threshold at which total revenues equal total costs. The break-even quantity for each crop is computed using QBE = FC / (P − VC), where FC – fixed costs allocated pro rata to each crop by its share of total revenue, P – average selling price per unit, and VC – variable cost per unit. Applying this formula across the three-crop mix yields an aggregate break-even output of 27,582 units: 4,243 kg of tomatoes, 2,122 kg of sweet peppers, and 21,217 cucumber fruits (Table 4). Multiplying each crop's break-even quantity by its average selling price gives per-crop break-even revenues of GH¢207,354 for tomatoes, GH¢136,417 for sweet peppers, and GH¢245,550 for cucumbers, which together total GH¢589,321. This threshold represents approximately 47% of the enterprise's Year 0 (moratorium) revenue of GH¢1,244,160, confirming that even at the lowest production capacity (40%), the enterprise generates revenues well above the cost-recovery threshold. The break-even revenue is thus not a binding constraint under normal operating conditions but becomes critical during adverse scenarios (10%+ price reductions), where it signals the minimum market price floor below which operations become financially destructive.

Sensitivity analysis

The sensitivity analysis quantifies how adverse deviations in selling prices and operating costs affect NPV and IRR (Table 5). The results confirm that the enterprise is substantially more sensitive to price changes than to equivalent cost changes, a direct consequence of the high operating leverage inherent in capital-intensive greenhouse production.

A 10% price reduction alone, the most plausible near-term market shock, given documented seasonal price collapse patterns for tomatoes in Ghana (Wongnaa et al., 2019), is sufficient to render the investment non-viable (NPV = −GH¢549,623; IRR = 20%, below the 25% hurdle). This is the single most important finding of the study from a policy perspective. Thus, the entire financial viability of the enterprise rests on maintaining prices within 10% of baseline levels. By contrast, a 10% cost increase, while reducing NPV substantially from GH¢838,548 to GH¢139,644, still yields a positive NPV and IRR above the hurdle rate, therefore indicating meaningful resilience to moderate input cost inflation.

Combined adverse scenarios of price reduction and cost increase are particularly destructive. For instance, a simultaneous 10% price reduction and 10% cost increase produces an NPV of −GH¢1,239,367 and an IRR of 12%, representing a severe departure from viability. These results confirm that risk mitigation must prioritise revenue stability over cost control. The practical implication that the enterprise requires guaranteed price floors, formal off-take agreements, or contract farming arrangements to be investment-grade under realistic market conditions is a direct, quantifiable input into policy design, and distinguishes this study's contribution from earlier qualitative discussions of greenhouse farming challenges in Ghana.

The asymmetric price-cost sensitivity is consistent with international evidence. For instance, Sánchez et al. (2022) and Alam et al. (2022) both document how capital-intensive agricultural enterprises with high fixed-cost ratios are disproportionately vulnerable to revenue-side shocks relative to cost-side shocks, and that risk mitigation instruments targeting price stability generate larger viability improvements than equivalent cost-reduction interventions. The present findings confirm this pattern in the Ghanaian greenhouse context and provide a quantitative boundary condition of 10% price floor that is directly actionable for agricultural policy design.