Fix consumer subscription pricing exploit with perceived-value-based elasticity

Players could set astronomical prices and still retain subscribers because
price elasticity floored at 10% for any price above $100, satisfaction
ignored pricing entirely, and churn had no price component.

Introduces perceived value per tier (model quality × reputation), replaces
the broken linear formula with sigmoid decay, adds price-aware satisfaction
blending, and applies per-tier price-based churn multipliers.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

packages/game-engine/src/systems/market/consumerTierSystem.ts

@@ -8,6 +8,12 @@ import {
   NETWORK_DEGRADATION,
   REJECTION_CHURN_MULTIPLIER,
   QUEUE_CHURN_MULTIPLIER,
+  CONSUMER_TIER_BASE_PERCEIVED_VALUE,
+  PERCEIVED_VALUE_REPUTATION_RANGE,
+  PRICE_ELASTICITY_STEEPNESS,
+  PRICE_SATISFACTION_WEIGHT,
+  PRICE_CHURN_EXPONENT,
+  PRICE_CHURN_MAX_MULTIPLIER,
 } from '@ai-tycoon/shared';
 
 export interface ConsumerTickResult {
@@ -16,10 +22,23 @@ export interface ConsumerTickResult {
   totalConsumerTokenDemand: number;
 }
 
+function computePerceivedValue(
+  tierId: ConsumerTierId,
+  modelQuality: number,
+  reputation: number,
+): number {
+  const baseValue = CONSUMER_TIER_BASE_PERCEIVED_VALUE[tierId];
+  if (baseValue <= 0) return 0;
+  const repRange = PERCEIVED_VALUE_REPUTATION_RANGE;
+  const repMult = repRange.min + (Math.max(0, Math.min(100, reputation)) / 100) * (repRange.max - repRange.min);
+  return baseValue * Math.max(0, modelQuality) * repMult;
+}
+
 export function processConsumerTiers(
   tiers: ConsumerTierState,
   playerConsumerCustomers: number,
   modelQuality: number,
+  reputation: number,
   seasonalConsumerMultiplier: number,
   networkLatencyPenalty: number,
   consumerPaidMetrics: TierServingMetrics,
@@ -57,6 +76,7 @@ export function processConsumerTiers(
     team: 'pro',
   };
 
+  // --- Pass 1: Conversions only (no churn yet) ---
   for (const id of CONSUMER_TIER_ORDER) {
     if (id === 'free') continue;
     const tier = updated.tiers[id];
@@ -69,22 +89,26 @@ export function processConsumerTiers(
 
     const conversionKey = `${prevId}->${id}`;
     const baseRate = CONVERSION_RATES[conversionKey] ?? 0;
-    const priceAttr = tier.config.price > 0
-      ? Math.max(0.1, 1 - tier.config.price / 100)
-      : 1;
-    const convRate = baseRate * qualityFactor * priceAttr * seasonalConsumerMultiplier;
 
+    const perceivedValue = computePerceivedValue(id, modelQuality, reputation);
+    let priceAttr: number;
+    if (tier.config.price <= 0) {
+      priceAttr = 1;
+    } else if (perceivedValue <= 0) {
+      priceAttr = 0;
+    } else {
+      const ratio = tier.config.price / perceivedValue;
+      priceAttr = 1 / (1 + Math.pow(ratio, PRICE_ELASTICITY_STEEPNESS));
+    }
+
+    const convRate = baseRate * qualityFactor * priceAttr * seasonalConsumerMultiplier;
     const converting = prevTier.userCount * convRate;
     prevTier.userCount = Math.max(0, prevTier.userCount - converting);
     tier.userCount += converting;
     tier.conversionRateFromBelow = convRate;
-
-    tier.churnRate = TIER_CHURN_RATES[id];
-    const churnMultiplier = 1 + (1 - updated.satisfaction) * 2;
-    const churned = tier.userCount * tier.churnRate * churnMultiplier;
-    tier.userCount = Math.max(0, tier.userCount - churned);
   }
 
+  // --- Revenue & token demand ---
   let totalUsers = 0;
   let subscriptionRevenue = 0;
   let totalTokenDemand = 0;
@@ -98,6 +122,7 @@ export function processConsumerTiers(
 
   updated.totalUsers = totalUsers;
 
+  // --- Serving penalties & serving-based extra churn ---
   const paidDemand = consumerPaidMetrics.demandTokens;
   const freeDemand = consumerFreeMetrics.demandTokens;
   const totalDemand = paidDemand + freeDemand;
@@ -140,6 +165,7 @@ export function processConsumerTiers(
     }
   }
 
+  // --- Price-aware satisfaction ---
   let headroomBonus = 0;
   if (totalDemand > 0) {
     const totalServed = consumerPaidMetrics.servedTokens + consumerFreeMetrics.servedTokens;
@@ -152,10 +178,63 @@ export function processConsumerTiers(
   }
 
   const netLatencyPenalty = networkLatencyPenalty * NETWORK_DEGRADATION.satisfactionPenaltyPerLatency;
-  updated.satisfaction = Math.min(1, Math.max(0,
+  const qualityServingSatisfaction = Math.min(1, Math.max(0,
     0.3 + modelQuality * 0.5 + headroomBonus - servingPenalty - netLatencyPenalty,
   ));
 
+  let priceSatNumerator = 0;
+  let priceSatDenominator = 0;
+  for (const id of CONSUMER_TIER_ORDER) {
+    if (id === 'free') continue;
+    const tier = updated.tiers[id];
+    if (tier.userCount <= 0) continue;
+    const pv = computePerceivedValue(id, modelQuality, reputation);
+    let tierPriceSat: number;
+    if (tier.config.price <= 0) {
+      tierPriceSat = 1;
+    } else if (pv <= 0) {
+      tierPriceSat = 0;
+    } else {
+      tierPriceSat = Math.min(1, pv / tier.config.price);
+    }
+    priceSatNumerator += tierPriceSat * tier.userCount;
+    priceSatDenominator += tier.userCount;
+  }
+  const priceSatisfaction = priceSatDenominator > 0
+    ? priceSatNumerator / priceSatDenominator
+    : 1;
+
+  const w = PRICE_SATISFACTION_WEIGHT;
+  updated.satisfaction = Math.min(1, Math.max(0,
+    (1 - w) * qualityServingSatisfaction + w * priceSatisfaction,
+  ));
+
+  // --- Pass 2: Churn (using price-aware satisfaction) ---
+  for (const id of CONSUMER_TIER_ORDER) {
+    if (id === 'free') continue;
+    const tier = updated.tiers[id];
+
+    tier.churnRate = TIER_CHURN_RATES[id];
+    const satisfactionChurnMultiplier = 1 + (1 - updated.satisfaction) * 2;
+
+    const pv = computePerceivedValue(id, modelQuality, reputation);
+    let priceChurnMultiplier = 1;
+    if (tier.config.price > 0 && pv > 0) {
+      const ratio = tier.config.price / pv;
+      if (ratio > 1) {
+        priceChurnMultiplier = Math.min(
+          PRICE_CHURN_MAX_MULTIPLIER,
+          Math.pow(ratio, PRICE_CHURN_EXPONENT),
+        );
+      }
+    } else if (tier.config.price > 0 && pv <= 0) {
+      priceChurnMultiplier = PRICE_CHURN_MAX_MULTIPLIER;
+    }
+
+    const churned = tier.userCount * tier.churnRate * satisfactionChurnMultiplier * priceChurnMultiplier;
+    tier.userCount = Math.max(0, tier.userCount - churned);
+  }
+
   updated.viralCoefficient = modelQuality > 0.5 ? 1 + (modelQuality - 0.5) * 2 : 0;
 
   return {

packages/game-engine/src/systems/market/index.ts

@@ -188,6 +188,7 @@ export function processMarketV2(
     state.market.consumerTiers,
     playerConsumerCustomers,
     modelQuality,
+    state.reputation.score,
     seasonal.multipliers.consumer,
     state.infrastructure.networkLatencyPenalty,
     sm.tierMetrics['consumer-paid'],

packages/game-engine/src/systems/market/tamSystem.ts

@@ -15,6 +15,8 @@ import {
   ATTRACTIVENESS_WEIGHTS,
   OBSOLESCENCE_PENALTY_WEIGHT,
   NEW_MODEL_BOOST_VALUE,
+  CONSUMER_TIER_BASE_PERCEIVED_VALUE,
+  PERCEIVED_VALUE_REPUTATION_RANGE,
 } from '@ai-tycoon/shared';
 
 export interface ParticipantProfile {
@@ -27,6 +29,16 @@ export interface ParticipantProfile {
   hasFreeTier: boolean;
 }
 
+function computeTamPriceScore(price: number, qualityScore: number, reputation: number): number {
+  if (price <= 0) return 1;
+  const repRange = PERCEIVED_VALUE_REPUTATION_RANGE;
+  const repMult = repRange.min + (Math.max(0, Math.min(100, reputation)) / 100) * (repRange.max - repRange.min);
+  const refPV = CONSUMER_TIER_BASE_PERCEIVED_VALUE.plus * qualityScore * repMult;
+  if (refPV <= 0) return 0;
+  const ratio = price / refPV;
+  return 1 / (1 + ratio * ratio);
+}
+
 export function buildPlayerProfile(
   qualityScore: number,
   chatPrice: number,
@@ -36,8 +48,7 @@ export function buildPlayerProfile(
   obsolescence: ObsolescenceState,
   hasFreeTier: boolean,
 ): ParticipantProfile {
-  const avgPrice = (chatPrice + apiOutputPrice) / 2;
+  const priceScore = computeTamPriceScore(chatPrice, qualityScore, reputation);
-  const priceScore = Math.max(0, Math.min(1, 1 - avgPrice / 100));
 
   let freshness = obsolescence.playerModelFreshness;
   if (obsolescence.newModelBoostRemaining > 0) {
@@ -56,8 +67,8 @@ export function buildPlayerProfile(
 }
 
 export function buildCompetitorProfile(c: Competitor): ParticipantProfile {
-  const avgPrice = (c.products.chatPrice + c.products.apiOutputPrice) / 2;
+  const compQuality = Math.min(1, c.estimatedCapability / 100);
-  const priceScore = Math.max(0, Math.min(1, 1 - avgPrice / 100));
+  const priceScore = computeTamPriceScore(c.products.chatPrice, compQuality, c.reputation);
 
   return {
     id: c.id,

packages/shared/src/constants/gameBalance.ts

@@ -873,6 +873,21 @@ export const TIER_CHURN_RATES: Record<ConsumerTierId, number> = {
 
 export const FREE_TIER_ADOPTION_RATE = 0.10;
 
+// --- Consumer Perceived Value ---
+
+export const CONSUMER_TIER_BASE_PERCEIVED_VALUE: Record<ConsumerTierId, number> = {
+  free: 0,
+  plus: 40,
+  pro: 120,
+  team: 80,
+};
+
+export const PERCEIVED_VALUE_REPUTATION_RANGE = { min: 0.5, max: 1.0 };
+export const PRICE_ELASTICITY_STEEPNESS = 3.0;
+export const PRICE_SATISFACTION_WEIGHT = 0.3;
+export const PRICE_CHURN_EXPONENT = 1.5;
+export const PRICE_CHURN_MAX_MULTIPLIER = 10.0;
+
 // --- API Tier Defaults ---
 
 export const API_TIER_DEFAULTS: Record<ApiTierId, { monthlyFee: number; inputPrice: number; outputPrice: number; rateLimit: number }> = {