{'fraction_non_alphanumeric': 0.01863932898415657, 'fraction_numerical': 0.0, 'mean_word_length': 5.7974683544303796, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Valuation of performance-based contracts for capital equipment: A stochastic programming approach

ABSTRACT Evaluating performance-based contracts (PBCs) for capital equipment can be a challenge because it is difficult to map service-level improvements to operational availability. This article considers scenario-based stochastic programming models for the evaluation of PBC alternatives for capital equipment consisting of a single-component system. In particular, PBC alternatives are evaluated for robustness under uncertainty in mean time between failures and mean downtime. The models measure expected deviation of implied contract operational availability and realized operational availability, and robustness is measured by the extent of improvement in service quality under a budget constraint. Optimal contract service levels are also computed that can be compared to service levels offered in a contract alternative. Value at risk (VaR) and conditional value at risk (CVaR) values for contracts are generated to gain insight into the readiness risk of contracts.