9. Pricing, Revenue Management and Profit Optimization

Introduction and Context

Pricing in hospitality is not merely the act of attaching a monetary value to a room, meal, event, or experience. It is a strategic decision about how a perishable capacity resource should be allocated among customers with different willingness to pay, booking horizons, service requirements, and acquisition costs. An unsold room tonight cannot be stored and sold tomorrow. This perishability makes hotel pricing fundamentally different from the pricing of durable goods.

Revenue management developed from the need to match the right inventory with the right customer at the right time and through the right channel. Contemporary hotel revenue management extends beyond room occupancy and average daily rate (ADR). It includes demand forecasting, market segmentation, dynamic pricing, length-of-stay controls, distribution economics, direct-booking strategies, loyalty investment, total revenue generation, and ultimately profit contribution.

A hotel may report strong occupancy and attractive gross revenue while producing weak profit if it relies heavily on expensive intermediaries, accepts low-value group business during peak periods, or sells rooms without considering food and beverage, spa, parking, and ancillary expenditure. The central managerial question is therefore not simply, “How much revenue was generated?” but “Which business produced the most valuable and sustainable contribution to profit?”

Learning Objectives

After studying this chapter, students should be able to:

1. Explain the purpose, principles, and evolution of hospitality revenue management.

2. Apply demand forecasting, segmentation, dynamic pricing, and inventory-control techniques.

3. Calculate and interpret occupancy, ADR, RevPAR, net RevPAR, TRevPAR, and contribution measures.

4. Use displacement analysis to evaluate group, contract, and transient business.

5. Assess the financial consequences of distribution costs and loyalty strategies.

6. Integrate rooms, food and beverage, meetings, spa, and other departments in total revenue management.

7. Evaluate pricing decisions ethically and identify operational, technological, and governance risks.

The Economic Logic of Hospitality Revenue Management

Revenue management rests on four conditions: relatively fixed capacity, variable demand, perishable inventory, and differentiated customer willingness to pay. A hotel with 200 rooms cannot increase capacity quickly during a sold-out night, and a room that remains vacant after midnight has no recoverable selling opportunity. At the same time, customers who occupy apparently identical rooms may have very different reasons for travel and price sensitivity.

The objective is to maximize expected contribution from available capacity rather than to maximize occupancy at any cost. A low rate may increase occupancy but reduce contribution; a high rate may increase ADR but leave too many rooms empty. The economically sound decision balances price and volume in relation to forecast demand and variable costs.

Segmentation and willingness to pay

Market segmentation divides demand into groups with distinguishable booking behavior and value characteristics. Common hotel segments include transient leisure, transient business, corporate negotiated, wholesale, online travel agency (OTA), group, government, long-stay, and local resident business. Segments may differ in booking lead time, cancellation probability, length of stay, ancillary spending, service expectations, and price sensitivity.

A rate fence is a condition that separates customers paying different prices for a similar product. Examples include advance purchase, minimum length of stay, non-refundability, membership status, age eligibility, package purchase, corporate qualification, or restriction to particular booking channels. Effective fences make lower prices available to genuinely price-sensitive customers without unnecessarily discounting customers willing to pay more.

Segmentation must be behaviorally meaningful. If every customer can obtain the lowest rate simply by asking, the hotel has not created a reliable price structure. Conversely, excessively restrictive fences can confuse customers and damage trust.

Inventory and room-type control

Hotel inventory is controlled at several levels: total rooms, room type, rate plan, date, channel, and length of stay. A room may be physically available but commercially unavailable under a particular rate plan. For example, a hotel may close its discounted weekend rate while continuing to sell premium flexible rates.

Overbooking is the deliberate acceptance of reservations beyond physical capacity to compensate for forecast cancellations and no-shows. It can improve expected occupancy, but it creates relocation costs, compensation obligations, reputational risk, and employee stress. Overbooking limits should be based on historical cancellation patterns, current booking pace, customer value, room-type availability, and the cost of walking a guest—not on a fixed percentage applied mechanically.

Performance Measures: From Occupancy to Profit

The interpretation of revenue-management performance depends on using consistent denominators and distinguishing gross from net revenue.

Occupancy percentage is:

Occupancy = Rooms sold ÷ Rooms available × 100

If a 200-room hotel sells 150 rooms, occupancy is 75 percent, assuming all 200 rooms were available for sale.

Average daily rate (ADR) is:

ADR = Room revenue ÷ Rooms sold

If room revenue is ₹1,800,000 from 150 rooms, ADR is ₹12,000.

Revenue per available room (RevPAR) is:

RevPAR = Room revenue ÷ Rooms available

It can also be calculated as ADR × occupancy rate expressed as a decimal. In the example, RevPAR is ₹9,000, or ₹12,000 × 0.75. RevPAR combines price and volume, making it more informative than either ADR or occupancy alone, but it remains a rooms-revenue measure rather than a profit measure.

Net RevPAR deducts acquisition and distribution costs. A simplified expression is:

Net RevPAR = (Room revenue − channel commissions − transaction costs − relevant promotion costs) ÷ Rooms available

A hotel with a gross RevPAR of ₹9,000 may have a better economic result than another hotel with RevPAR of ₹9,300 if the first hotel sells primarily through direct channels and the second pays high commissions and discounts.

Total revenue per available room (TRevPAR) is:

TRevPAR = Total hotel revenue ÷ Rooms available

Total revenue may include rooms, food and beverage, meetings, spa, parking, transportation, and other departments. TRevPAR is valuable for resorts and full-service hotels, where a room booking generates substantial ancillary expenditure.

Other useful measures include gross operating profit per available room (GOPPAR), contribution per available room, revenue per occupied room, and departmental profit margins. GOPPAR is closer to profitability than RevPAR, although it is affected by departmental and undistributed operating expenses. Managers should avoid treating any single metric as a complete measure of performance.

Illustrative comparison

Hotel A records 80 percent occupancy at an ADR of ₹10,000. Its RevPAR is ₹8,000. Hotel B records 70 percent occupancy at an ADR of ₹12,000. Its RevPAR is ₹8,400. Hotel B therefore produces higher room revenue per available room despite lower occupancy. If Hotel B also has lower distribution costs and higher ancillary spending, the apparent advantage becomes stronger. If, however, Hotel B’s high rate generates complaints, cancellations, or weak repeat demand, management must evaluate the longer-term consequences rather than rely only on the current period’s RevPAR.

Forecasting Demand and Translating Forecasts into Decisions

Forecasting estimates the number, timing, segment mix, rate level, and value of future demand. It is not a prediction of what management wishes to sell; it is an evidence-based estimate of what the market is likely to produce under specified conditions.

A practical forecasting process begins with historical data and then adjusts it for current booking pace, cancellations, events, holidays, competitor actions, economic conditions, weather, transport capacity, renovations, and changes in distribution. Historical averages are useful but insufficient. A festival, airline schedule change, or major convention can make prior-year patterns misleading.

Important forecasting concepts include:

• Booking pace: reservations accumulated by a particular number of days before arrival.
• Pickup: additional reservations received between two observation dates.
• Wash: expected cancellations and no-shows deducted from booked business.
• Lead time: interval between booking and arrival.
• Denials: demand that could not be accepted because inventory was unavailable or a rate was closed.
• Regret: estimated lost value when a low-value booking is accepted instead of a later high-value booking.

Forecasts should be expressed by segment and rate category, not only as a total room count. A forecast of 120 rooms is incomplete if it does not indicate whether those rooms are expected to come from high-rated corporate travelers, discounted leisure customers, or a low-rated group with substantial ancillary spending.

Forecast accuracy should be measured using indicators such as mean absolute deviation or percentage error. More important than producing a single “perfect” number is identifying uncertainty and preparing alternative scenarios. A revenue manager may use conservative, expected, and optimistic forecasts, each linked to different pricing and inventory actions.

Dynamic Pricing and Rate Architecture

Dynamic pricing adjusts rates in response to demand conditions, booking pace, remaining capacity, competitor positioning, and customer behavior. It does not mean changing prices randomly or continuously. A sound rate architecture defines logical price levels and rules for moving between them.

A typical structure may contain entry, standard, premium, flexible, package, corporate, and luxury rates. The differences between levels should reflect meaningful product or purchase conditions. Rate changes should be coordinated with restrictions such as minimum length of stay, closed-to-arrival dates, cancellation rules, and room-type availability.

Price optimization can be represented conceptually as:

Expected contribution = Probability of sale × (Price − variable cost)

This expression is incomplete unless it also considers the opportunity cost of using inventory. A low-priced booking arriving on a peak night may prevent acceptance of a later booking with higher contribution. Thus, the relevant comparison is often not between price and variable cost alone, but between the expected contribution of competing uses of capacity.

Price elasticity describes the responsiveness of demand to a change in price. Business travelers booking near a meeting may be relatively less price-sensitive, while leisure travelers booking far in advance may be more responsive. Elasticity is not constant across dates, segments, or competitive conditions. Managers should therefore use controlled tests and historical evidence rather than assuming that a price reduction will always generate enough additional volume to improve revenue.

Displacement Analysis and the Value of Group Business

Groups can provide volume, advance commitment, meeting revenue, and reduced selling effort. They can also occupy high-demand dates at low rates, require blocking of rooms that might otherwise sell individually, and create pressure on restaurants and public areas. Displacement analysis evaluates what the hotel gives up by accepting a piece of business.

A simplified displacement calculation compares the group’s expected contribution with the contribution from transient business displaced by the group. The analysis may include:

1. Group room revenue and room contribution.

2. Group food and beverage, meeting-room, spa, and other ancillary contribution.

3. Transient room revenue that could have been sold.

4. Transient ancillary spending.

5. Commission and acquisition costs for each segment.

6. Cancellation risk, wash, shoulder-night effects, and operational costs.

7. Strategic value, such as a repeat account or desirable market visibility.

Suppose a 100-room hotel receives an offer for 60 rooms for two peak nights at ₹7,000 per room. The group also promises ₹1,200 contribution per occupied room from meetings and food and beverage, making estimated group contribution ₹8,200 per room before additional costs. Forecast transient demand suggests that 50 of those rooms could sell at ₹11,000 with ₹1,000 ancillary contribution. If the group displaces 50 transient rooms, the transient opportunity contribution is ₹12,000 per room, or ₹600,000 in total, while the group contribution for 60 rooms is ₹492,000 before considering shoulder nights. On these assumptions, acceptance would be unattractive unless the group produces additional benefits, fills otherwise unsellable rooms, or generates sufficient shoulder-night demand. The decision should not be based on the group rate alone.

Displacement analysis is especially important for weddings, conferences, airline contracts, government business, and long-stay agreements. Its quality depends on the quality of the forecast. A poor forecast can make a profitable group appear unprofitable or allow low-value business to consume peak inventory.

Distribution Economics and Loyalty Decisions

Distribution expands market access but carries financial costs. Direct channels may involve website technology, payment processing, marketing, loyalty benefits, and staff costs. OTAs commonly involve commissions, promotional participation, and possible loss of direct customer data. Wholesale and bed-bank channels may offer volume but can create rate leakage, opaque resale, or conflict with direct pricing.

Managers should compare channels using net contribution rather than gross booking value. A useful channel statement includes:

Gross room revenue − commission − payment cost − marketing cost − loyalty cost − servicing cost − expected cancellation or fraud cost.

The comparison should also consider customer lifetime value. A direct guest who returns repeatedly, purchases ancillary services, and recommends the hotel may be worth more than a one-time OTA guest, even if both pay the same room rate. However, direct booking is not automatically more profitable. A direct booking generated through expensive paid advertising may cost more than an organic OTA booking. Channel economics must therefore be measured at reservation and customer levels.

Loyalty programs can stimulate repeat purchase, reduce price comparison, provide customer data, and support personalization. They also create costs through discounts, points, free nights, upgrades, technology, and program administration. A loyalty strategy should assess incremental revenue and contribution, not merely enrollment numbers. Benefits should be designed so that they protect rate integrity and encourage profitable behavior, such as direct booking, longer stays, off-peak travel, or ancillary purchases.

Total Revenue Management and Profit Optimization

Total revenue management integrates all revenue-generating departments. A rooms decision can influence restaurant demand, banquet utilization, spa appointments, parking, and labor requirements. A resort may accept a lower room rate from a guest who spends substantially on dining, activities, and wellness. A city hotel may prefer a corporate account with limited ancillary expenditure if it fills otherwise weak weekdays and reduces acquisition uncertainty.

The analysis should distinguish revenue from contribution. An additional restaurant sale may require food, labor, and payment costs; an incremental spa treatment may require therapist time that could have been sold to another guest. The question is whether the incremental contribution justifies the capacity consumed.

Cross-departmental coordination is essential. Revenue management, sales, marketing, front office, reservations, finance, food and beverage, and operations should share assumptions and performance information. If the revenue team raises prices while housekeeping cannot release rooms on time, the hotel may experience poor arrival satisfaction and operational failure. If sales promises complimentary upgrades without inventory controls, rate segmentation may collapse.

Profit optimization may involve a broader objective function:

Expected hotel contribution = room contribution + ancillary contribution − acquisition costs − incremental operating costs − service recovery and risk costs.

This objective encourages managers to evaluate the entire customer journey rather than a single transaction.

Technology, Analytics, and Automation

Property-management systems, central reservation systems, channel managers, customer relationship management platforms, point-of-sale systems, and business-intelligence tools provide the data infrastructure for revenue management. Integrated systems can connect reservations, room status, guest profiles, rates, cancellations, channel costs, and ancillary expenditure.

Revenue-management systems use statistical models and, increasingly, machine-learning techniques to estimate demand, cancellation probability, price response, and optimal availability controls. Automated recommendations can identify unusual booking pace or suggest rate changes. Nevertheless, automation does not eliminate managerial judgment. Algorithms may reproduce historical bias, misunderstand extraordinary events, or optimize revenue while damaging guest fairness and brand positioning.

Data governance is therefore important. Hotels should define data ownership, access rights, retention periods, privacy safeguards, and procedures for correcting inaccurate guest information. Personalization must comply with applicable privacy and consumer-protection law. Prices should not be manipulated using sensitive personal characteristics or presented in a misleading manner.

An Illustrative Case: The Harbor Grand’s Peak-Season Decision

Background

The Harbor Grand is a 180-room independent hotel in a coastal destination. It earns substantial revenue from rooms, a restaurant, weddings, and small conferences. Its direct booking share has declined as OTA bookings increased. Management historically focused on occupancy and monthly ADR.

Situation

For a three-night holiday weekend, the hotel is 112 rooms booked at an average rate of ₹9,500, 21 days before arrival. A tour operator offers 50 rooms at ₹7,000 per night, with a guaranteed minimum of 45 rooms. The operator also estimates ₹900 per occupied room in food and beverage contribution. Forecast transient demand indicates that 40 additional rooms may sell at an average rate of ₹12,500. OTA commission is 18 percent; direct booking acquisition cost averages 6 percent. The hotel’s variable room cost is ₹1,800 per occupied room.

Analysis

The tour operator’s room contribution per room is ₹7,000 − ₹1,800 = ₹5,200. Adding estimated ancillary contribution produces ₹6,100. A transient direct booking contributes ₹12,500 − ₹1,800 − ₹750 acquisition cost, plus expected ancillary contribution. If ancillary contribution is estimated at ₹1,000, transient contribution is ₹10,950 per room. The operator would therefore be unattractive if it displaced 40 or more transient rooms.

However, the group’s guaranteed minimum may fill rooms on the shoulder night, and its booking certainty reduces forecast risk. The operator also requests a flexible release date, which could preserve some inventory for transient demand. The hotel should not accept the full block automatically. It could offer a smaller block, a higher rate, a tighter release period, or a package that shifts some value into paid breakfast and activities. The hotel should close the lowest public rate, monitor pickup daily, and retain inventory for high-contribution transient demand.

Strategy and outcome

Management accepts 25 rooms at ₹7,800, requires a two-night minimum stay, and sets a release date 14 days before arrival. The remaining rooms are protected for transient demand. Direct members receive a value-added offer rather than a deep discount, and the restaurant promotes pre-arrival dining reservations. The hotel also creates a dashboard showing gross revenue, net revenue by channel, ancillary contribution, cancellations, and total contribution per available room.

The case illustrates that a group decision should be based on displacement and total contribution, not on the apparent security of volume. It also shows how rate, restrictions, channel economics, and ancillary revenue can be combined into one decision.

Risks, Limitations, and Common Managerial Errors

Revenue management is vulnerable to inaccurate data, excessive reliance on historical patterns, poor segmentation, rate leakage, and conflicting departmental objectives. Common mistakes include measuring success only through occupancy, changing prices without a coherent rate ladder, ignoring commissions, accepting groups without displacement analysis, overbooking without relocation capacity, and discounting when the actual problem is weak product value or poor communication.

Forecasts can fail during crises, sudden transport disruptions, regulatory changes, extreme weather, or unexpected events. Managers should use scenario planning and establish decision thresholds rather than treating model outputs as facts. Another limitation is metric distortion: a hotel may improve RevPAR by restricting low-rated business while damaging total revenue, guest loyalty, or long-term market share.

Price transparency is an ethical and commercial requirement. Rate differences should be explainable through legitimate conditions such as flexibility, purchase timing, membership, or product attributes. Hidden charges, misleading “discounts,” discriminatory pricing, and involuntary upselling can undermine trust and attract regulatory scrutiny. Staff should be trained to explain rate conditions accurately.

Best-Practice Framework for Managers

A disciplined revenue-management cycle can be organized as follows:

1. Establish clean, integrated data and consistent metric definitions.

2. Segment demand according to behavior, value, and booking conditions.

3. Forecast demand by date, segment, room type, channel, and ancillary potential.

4. Set a logical rate architecture with transparent fences.

5. Control availability, minimum stays, overbooking, and room-type inventory.

6. Evaluate groups and contracts through displacement and contribution analysis.

7. Compare channels using net rather than gross revenue.

8. Coordinate rooms with food and beverage, events, spa, and operations.

9. Monitor pickup, cancellations, price response, channel cost, and profit measures.

10. Review outcomes, learn from forecast errors, and update assumptions.

The most effective organizations treat revenue management as a cross-functional management system rather than a narrow reservations activity. Finance supplies contribution analysis, operations confirms capacity, marketing communicates value, sales qualifies accounts, and leadership sets acceptable risk and service standards.

Current Developments and Emerging Directions

Hospitality firms are increasingly moving from rooms revenue management toward customer-value and profit-oriented optimization. This includes personalized offers, real-time ancillary selling, demand-based staffing, and integrated forecasting across departments. Machine learning is improving pattern recognition, but explainability and governance remain important. Sustainability is also entering pricing decisions: hotels may use incentives to shift demand to lower-impact periods, reduce resource-intensive services, or communicate the value of responsible operations.

Another development is the growing importance of direct customer relationships. Mobile check-in, digital keys, loyalty applications, first-party data, and personalized pre-arrival offers can reduce dependence on intermediaries. Yet the financial test remains incremental contribution after technology, marketing, and benefit costs. The future of profit optimization will depend less on maximizing a single headline rate and more on understanding the complete economic value of each customer, stay, channel, and use of capacity.

Chapter Summary

Hospitality revenue management allocates perishable capacity among demand segments to maximize expected contribution. Its major tools include segmentation, rate fences, demand forecasting, dynamic pricing, overbooking controls, displacement analysis, and channel-cost evaluation. Occupancy and ADR are useful but incomplete; RevPAR combines them, while net RevPAR, TRevPAR, contribution measures, and GOPPAR provide a more economically meaningful perspective.

Group and contract decisions must account for displaced transient business, ancillary contribution, acquisition cost, and risk. Distribution and loyalty strategies should be evaluated through net contribution and customer lifetime value rather than gross bookings or enrollment totals. Total revenue management integrates rooms with food and beverage, meetings, spa, parking, and other departments. Technology and AI can improve forecasting and automation, but they require human judgment, data governance, transparency, and ethical controls. Ultimately, profit optimization is a coordinated organizational process linking analytics, pricing, operations, finance, marketing, sales, and guest value.

Key Terms

Revenue management: The disciplined allocation and pricing of perishable capacity to maximize expected revenue or contribution.

Occupancy: The proportion of available rooms sold during a specified period.

ADR: Average room revenue earned per room sold.

RevPAR: Room revenue earned per available room.

Net RevPAR: RevPAR after relevant distribution, acquisition, and transaction costs.

TRevPAR: Total hotel revenue per available room.

GOPPAR: Gross operating profit per available room.

Market segmentation: Division of demand into groups with distinguishable behavior and value.

Rate fence: A condition that separates customers eligible for different prices.

Dynamic pricing: Adjustment of prices according to demand, capacity, timing, and market conditions.

Booking pace: The rate at which reservations accumulate before arrival.

Pickup: Additional reservations received between two observation dates.

Wash: Expected cancellations and no-shows deducted from booked reservations.

Overbooking: Accepting reservations beyond physical capacity to offset expected cancellations or no-shows.

Displacement analysis: Evaluation of the opportunity cost of accepting one business segment instead of another.

Channel cost: The commission, marketing, payment, servicing, and related cost of acquiring a booking.

Total revenue management: Coordinated optimization of revenue and contribution across hotel departments.

Customer lifetime value: Expected future contribution from a customer relationship.

Price elasticity: The responsiveness of demand to a change in price.

Contribution: Revenue remaining after relevant variable and acquisition costs.

Review Questions

Short Answer Questions

1. Why is hotel room inventory considered perishable?

2. Distinguish between ADR and RevPAR.

3. What is the purpose of a rate fence?

4. Define displacement analysis.

5. Why is net RevPAR often more informative than gross RevPAR?

Long Answer Questions

1. Explain the economic foundations of hospitality revenue management and discuss their managerial implications.

2. Describe a systematic demand-forecasting process for a full-service hotel.

3. Explain how dynamic pricing, rate architecture, and inventory controls work together.

4. Discuss the role of distribution economics and loyalty programs in profit optimization.

5. Explain how total revenue management extends conventional rooms revenue management.

Analytical / Application Questions

1. A 250-room hotel sells 190 rooms at an ADR of ₹8,500. Calculate occupancy and RevPAR. Explain why these figures alone cannot establish profitability.

2. A group offers 70 rooms at ₹6,500, while forecast transient demand could sell 55 of those rooms at ₹10,500. Identify the additional information required before accepting the group and explain the displacement logic.

3. A hotel’s OTA bookings produce higher gross ADR than direct bookings but incur an 18 percent commission and lower ancillary spending. Design a performance dashboard to determine whether the OTA channel is genuinely more profitable.

22. Multiple Choice Questions with Answers

Question 1

A hotel sells 150 rooms from 200 available rooms and earns room revenue of ₹1,800,000. Which pair correctly represents occupancy and ADR?

A. 75% occupancy and ₹9,000 ADR

B. 75% occupancy and ₹12,000 ADR

C. 80% occupancy and ₹12,000 ADR

D. 80% occupancy and ₹9,000 ADR

Correct Answer: B. 75% occupancy and ₹12,000 ADR

Question 2

Why may net RevPAR be more useful than gross RevPAR when comparing distribution channels?

A. It excludes all ancillary revenue

B. It incorporates occupancy but not ADR

C. It reflects acquisition and distribution costs

D. It measures only loyalty-member bookings

Correct Answer: C. It reflects acquisition and distribution costs

Question 3

Which situation best illustrates displacement analysis?

A. Comparing this year’s ADR with last year’s ADR

B. Estimating the transient contribution lost by accepting a low-rated group

C. Calculating the number of rooms cleaned by housekeeping

D. Determining the average length of stay of loyalty members

Correct Answer: B. Estimating the transient contribution lost by accepting a low-rated group

Question 4

A rate fence is primarily designed to:

A. Make every customer pay the same price

B. Separate customers eligible for different prices using meaningful conditions

C. Eliminate the need for demand forecasting

D. Guarantee that all rooms are sold through OTAs

Correct Answer: B. Separate customers eligible for different prices using meaningful conditions

Question 5

Which measure combines room price and room volume while remaining a rooms-revenue measure?

A. ADR

B. RevPAR

C. Customer lifetime value

D. Channel contribution

Correct Answer: B. RevPAR

Question 6

A hotel accepts a group because it fills many rooms, but the group occupies peak dates at a rate below the expected contribution from transient guests. What managerial error has occurred?

A. Failure to use displacement analysis

B. Excessive use of direct distribution

C. Incorrect calculation of occupancy

D. Overinvestment in loyalty benefits

Correct Answer: A. Failure to use displacement analysis

Question 7

Which decision best reflects total revenue management?

A. Selecting a room rate without considering other departments

B. Evaluating a resort guest’s room, restaurant, spa, and activity contribution together

C. Maximizing occupancy regardless of channel cost

D. Closing all discounted rates during low demand

Correct Answer: B. Evaluating a resort guest’s room, restaurant, spa, and activity contribution together

Question 8

Why can a direct booking be less profitable than an OTA booking in some situations?

A. Direct bookings never generate ancillary revenue

B. Direct bookings may involve substantial advertising and loyalty costs

C. OTAs do not charge commissions

D. Direct bookings always require overbooking

Correct Answer: B. Direct bookings may involve substantial advertising and loyalty costs

Question 9

Which practice is most appropriate when using automated revenue-management recommendations?

A. Accept every recommendation without review

B. Ignore data governance because the system is automated

C. Combine model output with managerial judgment and ethical controls

D. Use sensitive personal characteristics to set prices

Correct Answer: C. Combine model output with managerial judgment and ethical controls

Question 10

A hotel has 80% occupancy at an ADR of ₹10,000, while a competitor has 70% occupancy at ₹12,000. Which hotel has the higher RevPAR?

A. The first hotel, at ₹8,000

B. The second hotel, at ₹8,400

C. Both hotels, at ₹8,000

D. The first hotel, at ₹12,500

Correct Answer: B. The second hotel, at ₹8,400