Demand response programs provide customers with economic incentives for load reductions at times of high market prices and system reliability constraints. One type of demand response programs, price-based program, induces customers to respond to changes in product rates. However, some large-scale customers find it difficult to change their electricity consumption patterns, even with rate changes, because their electricity demands are commercial and industrial. This study proposes an adaptive in-house pricing model for large-scale customers, particularly those with multiple business facilities, for self-regulating price-based program. The adaptive in-house pricing model charges higher rates to customers with lower load factors by employing a peak-to-off-peak usage ratio in order to reduce usage at times of high prices at each facility. This study analyzes the daily electricity consumption patterns of large-scale customers through a field trial of the proposed pricing model at a telecom company with 447 offices and worksites for one month. The results show that the pricing model corresponds to average reductions of 3.54-28.69% during peak-demand times for four different types of workplaces. However, reductions in electricity consumption during off-peak periods did not show a significant difference. The results of this study prove that this proposed pricing model can be successfully applied to large-scale operations.