1. Each Excel spreadsheet file corresponds to a hotel chain, labelled ch1, ch2 and ch3. Each file contains three sheets, for the establishment (est), rooms department (rooms dept), and food and beverage departments (f&b dept), respectively. 

2. The title of each variable is generally self-explanatory. Each variable is prefixed by the chain and department. For instance "ch1_est_total_hotel_revenue" is the total monthly revenue earned by chain 1's establishment.

3. The column labelled "size" takes the values 1, 2 and 3 denoting small, medium and large sized hotels respectively. Small hotels are defined as hotels with number of rooms in the least third of the rooms distribution for all hotels in the sample (for each chain). Hence, medium sized and large hotels are hotels in the middle and top third distributions respectively. Further, "small", "medium" and "large" are binary variables denoting whether or not a hotel is classified as small, medium or large respectively.

4. “occupancy_rate” is the percentage of rooms that are occupied during a specified period of time among all the rooms that are available.  

5. “departmental_transfer_hours” is the hours of inter-departmental employee transfers across all micro-departments in the hotel, in response to the uneven distribution of demand. 

6. “f&b_covers” is the actual number of meals served by the food and beverage (f&b) department over a month. Hence, “f&b_price”=”total_f&b_revenue”/”f&b_covers”.

7. For the rooms department, it follows that “room_price”=”total_room_revenue”/”room_nights”.

8. “financial_productivity” is defined as the ratio of total revenue to total labour hours at the establishment, rooms department, food and beverage (f&b) department levels. Total revenues result from room nights, food and beverage (f&b) sales, conference and banqueting, leisure etc. “financial_productivity” is calculated as “financial_productivity”=”total_hotel_revenue”/”total_working_hours”; “financial_productivity”=”total_room_revenue”/”total_working_hours”; “financial_productivity”=”total_f&b_revenue”/”total_working_hours”.

9. “revpar” is revenue per available room. It is measured as the product of mean room rate with occupancy, i.e., “revpar”=”room_price” × “occupancy_rate”, and is a key performance indicator of the efficiency of hotels in using demand management to fill their rooms. It is considered to reflect demand variations at the specific time period for the establishment and rooms department. Estimates for the food and beverage (f&b) department are based on occupancy rate and price of f&b covers.

10. “number_of_workers”: The number of employees recorded in the hotels’ and departments’ schedules without double counting. 

11. “numerical_flexibility” measures the extent an employee is numerically flexible on a monthly basis relative to their annual average monthly hours, aggregated over all employees and dividing by the number of employees. This is computed as: Σ[(xi-µi)/µi]/n, where xi, µi and n stand for an employee’s monthly working hours, yearly average monthly working hours and number of employees in the sample, respectively.

12. “functional_flexibility”. At the establishment level, this is the ratio of hours of inter-departmental employee transfers across all micro-departments in the hotel – front desk, bar, conference and banqueting, leisure, housekeeping etc. – to total employee hours. For rooms departments, this is defined as the ratio of hours of employee imports from all other departments to total hours in the rooms departments. An analogous index is computed for food and beverage departments. An index close to zero denotes a low level of inter-departmental employee transfers, hence flexibility. The variable is calculated as: “functional_flexibility”=”departmental_transfer_hours”/”total_working_hours”.

13. “zero-contract” means zero-hour contract. It is a type of employment contract where the employer purports the discretion to vary the employee’s working hours, usually anywhere from full-time to ‘zero hours’.

14. Wage cost is the total wages over certain working hours. It follows that 
“zero-contract_wage_cost”=”zero-contract_hourly_wage” × ”zero-contract_hours”; “permanent-contract_wage_cost”=”permanent-contract_hourly_wage” × “permanent-contract_hours”; “male_wage_cost”=”male_hourly_wage” × “male_hours”;    “female_wage_cost”=”female_hourly_wage” × “female_hours”;

15. “share_of_zero-contract_hours” is the share of zero contract employee hours to total hours by all staff. An analogous measure applies to share of permanent contract hours, “share_of_permanent-contract_hours”.

16. “share_of_female_hours” and “share_of_male_hours”: The share of female (male) hours to total hours by all workers in the establishment and two core departments controls for gendered employment.

17. “training_cost”: Total monthly expenditures on training programmes in the establishment, and departments, proxies for staff training.

18. Monthly dummies “month1”-“month12”: Demand for hotel services is expected to follow seasonal patterns. “financial productivity”, “revpar” and other regressors may also exhibit seasonal patterns. We define 11 monthly binary variables to control for seasonality. The base period is January, and the coefficients of the other 11 monthly dummies are intercepts capturing the differential in productivity between the base month and other months.