Accounting Discussion Questions

ASSIGNMENT OUTLINEAssignment title:
Financing for tourism
Weighting:
100%
Faculty responsible: John Ryan
Programme:
PGD
Course name:
(P5011) Hospitality Finance & Performace Management
Hand out date: January 27 2023
Hand-in date to Faculty:
February 15 2023
Assignment Overview:
Read the case and .answer the questions at the end.
Overall aim:
To have a complete understanding challenges and strategies to be successful in the current environment.
Organisation and methodology:
This is a individual assignment and should be presented through Turnitin in Moodle. Please beware Turnitin will
automatically detect plagiarism so please do not copy and paste.
Resources available:
Open book. All the work carried out during the course is expected to be included in the plan. The theory behind the
practical initiatives is to be explained to further enhance the credibility of the plan.
Questions:
Describe the annual seasonality of VCLA income or room demand.
1. View the Financial Statements.
Students can review historical profit and loss (P&L) records to develop or describe the seasonality over the year.
2. Why do VCLA’s revenue spikes not always occur at the same time as maximum room demand?
Students should understand the difference in timing between when the hotel collects the assessment and when the
city actually deposits it in the VCLA’s account.
Room demand is an example of a good indicator of when the hotel collects the income.
3. What is the average historical growth rate of VCLA revenue?
Review the Forecast. The average historical growth rate is ?. However, growth since the inception of the operation is
not sustainable. What should they do?
4. What would the sales growth rate be in an economic decline or upturn?
Review Scenarios. Analyse the four scenarios for growth rate and marketing spending adjustment.
5. What financial and economic assumptions must be considered to develop the forecast?
Review room supply may impact VCLA revenue and GDP data.
Assessment tasks & weighting:
10% of each section is based on the level of English demonstrated within the report.
Common skills: assessed (bold) or developed (italics):
MANAGING AND DEVELOPING
SELF
1.Manages own
role and
responsibilities
2. Manages own
time in achieving
objectives.
WORKING WITH AND RELATING
TO OTHERS
6.Treats others’
values, beliefs
and opinions with
respect
COMMUNICATING
9.Receives and
responds to a
variety of
information
MANAGING TASKS AND SOLVING
PROBLEMS
13.Uses
information
sources
BECOMING NUMERATE AND
USING TECHNOLOGY
16.Applies
numerical skills
and techniques
7.Relates to and
interacts
objectively with
individuals and
groups
10.Presents
information in a
variety of visual
forms
14. Deals with a
combination of
routine and nonroutine tasks
17.Uses a range
of technological
equipment and
systems
3.Undertakes personal
and career
development
4. Transfers skills
gained to new and
changing situations
and contexts.
5.Uses a
range of
thought
processes
8.Works effectively as
a member of a team
11.Communicates in
writing
12.Participates in oral
and non-verbal
communication
15.Identifies and
solves routine and
non-routine
problems
Plagiarism:
Plagiarism is the act of presenting another’s ideas or words as one’s own. Cheating includes, but is not limited to,
the intentional falsification or fabrication of any academic activity, unauthorized copying of another person’s work, or
aiding and abetting any such acts.
Particular care must be taken when presenting information that has been obtained from an internet site. Should this
information not be correctly referenced, then you are guilty of plagiarism and will be penalised accordingly.
With respect to projects/assignments, faculty reserves the right to randomly call upon any student and ask them to
defend their work orally.
Any assignment/exam which is found to contain plagiarism will automatically be awarded a grade of 0, and an e-mail
will be sent to the student or the student’s parents/tutors/sponsors. Depending on the circumstances, additional
penalties could be imposed (see LRM Academic Regulations, Section 11).
Statement of authorship
Following the title page of your assignment there should be a page on which you sign a statement that the work
included in the assignment is your own work except where appropriately referenced. The following statement should
be used:
Statement of authorship
I certify that this assignment is my own work and contains no material which has been submitted as part of an assignment in any
institute, college or university. Moreover, to the best of my knowledge and belief, it contains no material previously published or written by
another person, except where due reference is made in the text of the assignment.
Signed …………………………………………………………………….
Name …………………………………………………………………….
Student number…………………………………………………….
Abstract
This case examines the financial reports for a tourism improvement district and discusses its
need to develop a revenue forecast. Assessment revenue is collected by tourism improvement
districts and is used to fund destination marketing initiatives. The Ventura County Lodging Association has identified an opportunity to more effectively manage a large cash reserve ac- count
and the expected revenue it may collect moving forward. Students are provided with the
resources to develop revenue forecast scenarios using tourism district and hotel performance
benchmarking data.
Case
Introduction
Video: https://sk.sagepub.com/cases/forecasting-assessment-revenue-
ventura-county-lodging-association#i59
After the Great Recession of 2008, the lodging industry and cities in Ventura County, southern California, experienced a loss of economic activity and revenue usually generated through tourist visitation to the area. Hotel operators in the cities of Camarillo, Oxnard, and Ventura decided to pool resources to promote awareness
of the area and thus increase demand for lodging accommodation. To accomplish this, the Ventura County
Lodging Association, or the VCLA, was formed in 2011; the city of Port Hueneme joined in 2015. This four-city
area is branded in marketing initiatives and functions as a tourism improvement district through the Ventura
County Coast (https://venturacountycoast.com/).
Video 1. Introduction to the VCLA
The four-city area is in the western coastal part of Ventura County, separated geographically by the Santa
Monica Mountains to the east and north. This area has several recreational areas including the Channel Islands National Park, beaches, and hiking trails that attract visitors seeking to escape to the outdoors. These
cities naturally joined together to promote the region and are adjacent to established tourism districts (Tucker,
2019c) serving the Santa Barbara area to the north and Conejo Valley to the West .
Figure 1. VLCA District Map
Source: VCLA
The VCLA mission is to drive tourism or room night demand through targeted marketing, event development,
sales, and public relations (Tucker, 2019b). The advisory board that oversees the association’s activities currently consists of operators of the lodging properties, such as hotel general managers, hotel sales directors,
and representatives from city level tourist boards. There are more than 60 lodging properties in the area, which
can be classified as hotels, motels, bed and breakfasts, and recreational vehicle (RV) resorts. The as-sociation
receives assessment revenue to fund its promotional activities through a 2% assessment collectedfrom the
four cities that are part of the VCLA. This assessment is collected proportionally on every room night a guest
stays at a lodging accommodation. Once the city has collected the assessment from the lodging prop-erties,
the funds are deposited in the VCLA’s bank account. Therefore, the revenue generated by the VCLA is
contingent upon hotel demand and the daily rate visitors to the area spend at lodging properties.
Since its inception in 2011, the VCLA has been building a cash reserve for emergencies and other short-term
needs. As a result of only depositing funds in the account, and never needing to make a withdrawal, the reserve had grown to over USD 2 million by late 2018. The funds had been held from the start in a simple money
market account at a regional bank.
At one of the VCLA board meetings, it was decided to investigate options to manage this reserve account
more effectively and to address two concerns. The first concern was that the VCLA funds were in a simple account that was not earning optimal interest rates which may be available through other financial institutions or
instruments. The second concern involved the Federal Deposit Insurance Corporation (FDIC), which insures
coverage only up to USD 250,000 per entity. In other words, if the bank failed, the VCLA would be at risk of
being unable to recover USD 1.75 million, since the funds were held at one institution. Hence, the VLCA desired a prudent short-term asset account management strategy that offered additional insurance protection,
competitive rates of return, and alignment with its financial goals. To determine the best financial instruments
to invest the USD 2 million already in the account, as well as the revenue it expected to receive in the coming
year, an assessment revenue forecast was required.
Assessment Districts
An assessment district is an entity “formed to finance improvements when no other source of money is available” and is created “by a sponsoring local government agency, such as a city or county” (California Tax Data,
2020). The Ventura County Coast is an assessment district that provides specific benefits to payers by funding marketing and sales promotion efforts for assessed businesses. The district was created in 2011 as the
Ventura–Oxnard–Camarillo Tourism Business Improvement District by Ventura City Council Resolution No.
2011-023 (Hoffman, 2015). As a non-profit and assessment district, the VCLA cannot levy taxes itself but is
able to partner with city officials to create the tax required to fund its operations.
The assessment rate is 2% of gross short-term (stays less than 31 days) room rental revenue. Based on the
benefit received, assessments will not be collected on stays of more than 30 consecutive days. The cities
are responsible for collecting the assessment on a monthly basis (including any delinquencies, penalties, and
interest) from each lodging business located within their jurisdiction. The cities are expected to take all reasonable efforts to collect the assessments from each lodging business.
Transient Occupancy Tax
Taxes are levied by governments on their citizens at various levels, including federal, state, county, city, and
district level. The taxes generate revenue that is used to fund a variety of programs and initiatives, including
national defense, education, courts, highways, and other infrastructure projects, workforce development, and,
as with this case, bolstering a specific industry such as tourism. Taxes can be levied on specific industries or
sectors to further support economic development of an area.
Within the hospitality industry, one such tax developed to support city tourism and economic development
is a transient occupancy tax or TOT (Tucker, 2019a). Added to the city sales tax, a TOT is a tax levied on
guests for each night they stay at a hotel. The revenue from the taxes is then distributed to the entities which
proposed the tax to be collected. Depending on the organization and accounting capabilities of the city itself,
this revenue is provided to the assessment district in one to three months.
In the state of California, local tourism board assessments range from 1–4% of the nightly rate, depending on
the specific city (Civitas, 2017). It may also take the form of a flat rate per night ranging from USD 1–4.50. In
the City of Camarillo, for example, a hotel guest pays taxes of 13%, or an extra USD 13 on a USD 100 per
night rate. This rate is composed of 9% in city TOT taxes, 2% assessment to support the Camarillo Hotel and
Tourism Association, and 2% to support the VCLA. While a hotel may record a room sale in a given month, it
may not provide its tax receipts to the city until a month later, which in turn provides the VCLA with its assessment revenue a further two months later.
As occupancy rates and the daily rate increase, so too will the city TOT revenue. With stable public and private funding for tourism marketing efforts, annual occupancy rates should increase significantly as new marketing and sales promotion programs are implemented. Greater occupancy will also produce an increase in
TOT and assessment revenues from tourist spending. This represents a substantial return to cities and to
tourism improvement districts.
Effect of Seasonality in Hotel Demand
According to Kenton (2019), “Seasonality is a characteristic of a time series in which the data experiences
regular and predictable changes that recur every calendar year”. Hartman (1986) referred to this seasonality
related to tourism as the reliable and predictable recurrence of tourists. Seasonality for each destination is different, but they are commonly impacted by factors such as weather, public holidays, cultural traditions, leisure
or business events in the area, family behavior such as summer vacations, as well as their own local attractions (see Figure 2).
Although the number of visitors is a measurement for tourism seasonality, the seasonality of hotel demand
can be measured in terms of room nights or, as defined by Smith Travel Research (2020), “as the number of
rooms sold in a specified time period.”
Smith Travel Research (STR) provides its clients with various reports that detail key hotel performance metrics such as demand. One type of report that can capture this data for multiple cities is a trend report. This
report can provide performance data by month for multiple years, which can be analyzed to chart the seasonality of the destination. Reviewing this type of data for the four-city area can illustrate the seasonality during
the year, which naturally peaks during the summer months when the area’s beach attractions are most popular.
Figure 2. Seasonality Room Demand Chart
Source: Authors, based on VCLA data
Forecast Development
Any business entity that is accountable to stakeholders or shareholders tries to reduce uncertainty. Businesses plan to be prepared and to anticipate any challenge or opportunity to remain as financially stable as possible within the expected accuracy range (Chien, 2014a). Budgeting and forecasting vary based on the intention and frequency of use. Businesses prepare budgets toward the end of their fiscal year cycle to plan for the
following year’s strategies. For most companies, once the budget is finalized before the new fiscal year begins,
there is no further change. In contrast, a forecast is not set in stone (Chien, 2014a).
The process of budget preparation often involves different types of forecasting. After a business’s strategies
are prioritized and set for the following fiscal year, the next step is to forecast revenue (Besley & Brigham,
2018). Revenue forecast determines the resources required for the operations needed to meet the strategies,
as shown schematically in Figure 3. Hence, a business often uses three years of a historical revenue less
expenses (R−E) statement to determine how to adjust past spending trends to support the new strategies
(Sowa, 2017). However, the operation budget cannot be fully in place until the capital expenditure budget
(CAPEX) is complete and available (Besley & Brigham, 2018). Therefore, businesses often examine necessary investment projects to meet their strategies (Chien, 2014b).
The CAPEX involves three types of cash flow forecast: (a) initial outflow of the investment; (b) operational
cash flow during the length of the project; and (c) terminal cash flow at the end of the investment project period
(Besley & Brigham, 2018). Once the CAPEX cash flow is in place, the finance department evaluates whether
the investment project meets specific pre-set criteria. Each business defines criteria based on in- dustry
specifics. Examples of criteria measurement tools include payback period, net present value, modifiedinternal
rate of return, and economic value add (Matias & Hutchinson, 2016).
Figure 3. Forecasting Process
Source: Modified by the authors from Besley & Brigham (2018) and Chien (2014a).
When the management team approves the investment project(s), the finance department determines the additional funds needed (AFN) while forecasting the balance sheet statement. Once the AFN are in the balance
sheet, the amount of the capital cost circles back to the R−E to finalize the new year’s budget (Besley &
Brigham, 2018). However, the process continues throughout the fiscal year to re-forecast when the management team monitors the budget compared to the actual spending. Re-forecast can occur weekly, monthly, or
as frequently as needed in the business (Chien, 2014b).
Revenue Forecast Application
A revenue forecast is needed to determine the expected income for the VCLA accounts. The development
of a revenue forecast and the accuracy of the forecast starts with various assumptions. There are several
assumptions that VCLA needed for a five-year revenue forecast. Both macroeconomic and microeconomic
indicators of future hotel demand should be evaluated. There are three types of assumptions to consider: (a)
industry growth rate benchmark; (b) overall U.S. economic indicators; and (c) internal historical sales trend.
Industry Growth Rate Benchmark
Two hotel performance benchmarks in the hospitality industry are the reports produced by STR and Coldwell
Banker Richard Ellis (CBRE). STR produces various hotel performance reports that allow hoteliers to benchmark their performance relative to competitors on key performance indicators, and to understand how a market is performing overall. The CBRE report provides information on real estate market conditions.
Both STR and CBRE reports provide local data and historical trends to help establish local industry benchmarks. Analyzing these local industry benchmarks helps lodging properties to set their sales goals. Hence,
the first key assumption is the local industry growth rate, which can be used in forecasting VCLA revenue.
The STR and CBRE reports can provide occupancy and average daily rates, room demand, and room revenue for properties that report their data. Room demand and revenue are particularly valuable in illustrating
historical trends. The average local industry growth rate trend is determined by averaging monthly changes in
demand and revenue using the last five years of data; that is, by taking the five years of monthly changes in
demand and averaging them into one number. The result represents the average growth rate for forecasting
purposes. Additionally, the average growth rate can be used to determine how the VCLA is performing relative to the local industry and where it will be in the future—and thus how to account for future projects that
VCLA will need to implement to meet any further demand.
Overall U.S. Economic Indicators
Besides industry growth rates, firms need to consider more broadly the current health of the U.S. economy by
using the Federal Reserve interest rate, inflation, unemployment, and wages growth figures. These macroeconomic indicators are often used in forecasts in the context of understanding how the U.S. economy may
affect demand within the cities of the VCLA. Macroeconomic indicators ultimately affect how much revenue
the VLCA will generate in the next few years.
Historical Sales Trends
The last assumption arises from analysis of the historical R−E. The historical R−E illustrates the trend of
growth (or loss) in the sales and net profit margin. In a not-for-profit organization, the net profit is added to the
assets in the balance sheet. Net profit margin is net income divided by sales. Unlike for-profit organizations,
the net income of not-for-profit organizations is recorded in the assets (or reserve) in the balance sheets,
rather than as retained earnings. The historical R−E trend informs us about the average monthly operating
expenses needed to support the growth of the sales trend. The average monthly operating expenses also
determine the need for how much liquid short-term assets need to be set aside in case of emergency.
Short-Term Reserve Accounts Management Strategy
The short-term reserve accounts management strategy of the VCLA is shown schematically in Figure 4 and
is as follows:
• Operation account is for daily operations such as fixed or variable expenses.
• Emergency funds account is liquid and provides necessary cash in case of deficiency of the operation account.
• Short-term reserve account is a short-term reserve that houses an investment time horizon of less
than one year.
• Long-term reserve account is a long-term reserve that houses an investment time horizon greater
than one year.
Figure 4. Schematic Illustration of the Short-Term Accounts Management
Strategy
Source: Developed by the authors
Each of the accounts houses 3 months’ worth of average monthly operating expenses. The strategy of four
separate accounts was included in the request for proposal (RFP) for local financial institutes to bid for the
account management. Five of the 16 bidders were selected to present their plans to the VCLA board. Two
firms were selected to implement their short-term reserve account management strategy for VCLA.
Table 1 illustrates four accounts and the appropriate insurance. The Securities Investor Protection Corporation (SIPC) protects in the event that a brokerage firm fails. SIPC insurance covers deposits up to USD
500,000 per entity and per financial institution. Some financial institutions offer extended SIPC coverage to
their customers.
Table 1. Type of Accounts, Related Insurance, and Financial Institutes
Accounts
Insurance
Financial institutes
Operation
FDIC
Current regional bank
Emergency
FDIC
New regional bank
Short-term
FDIC and SPIC
New local fee-based wealth management firm
Long-term
SPIC
Competition and Risk Scenarios
The neighboring counties of the VCLA area, such as Santa Barbara and Los Angeles, are also competing for
tourism and lodging business, as are all other counties in California. This competition was part of the impetus
for the VCLA to form originally, because even though the hotels within the association compete with each
other, their goal is to increase aggregate demand such that all members benefit.
The 2008 Great Recession was integral in spurring the creation of the VCLA. Economies experience cycles,
so it is only a matter of time before the next downturn, which could once again severely impact demand for
VCLA member business. When another downturn occurs, the VCLA would likely increase its spending on
marketing activities with the hope of increasing, or at least maintaining, market demand.
To anticipate competition and macroeconomic risk, it is necessary to develop scenarios for sensitivity testing
of the forecasts. To execute multiple scenarios, assumptions for demand growth need to be established to
reflect changes or the impact on the R−E.
The revenue available to the VCLA for direct marketing activities is contingent on the amount received through
assessment collections, which governs how large its budget will be for the year. Should demand sig-nificantly
fall, the VCLA would need to use its short-term assets to supplement its funding for annual market-ing projects
to help increase demand and drive more revenue. By examining the effects of demand swings, such as a 10%
increase or decrease, strategies can be formed for how to address such scenarios. The VCLAoccupancy rates
are between 75% and 80%, so if they drop into the percentage range of low 70s to high 60s, they would likely
begin to start withdrawing from their reserves to try to increase demand. If they were to increase demand so
occupancy rates were in the 80%+ range they would view this as a very healthy signal and would focus on
identifying what marketing strategies helped lead to that success.
Since the four short-term assets accounts have been identified, it is necessary to forecast three years of expected revenue so that it can be defined how these are funded. Additionally, baseline, worst, and best-case
scenarios are required to reduce uncertainty and determine allocation to the short-term assets accounts.
Further Reading
Association for Financial Professionals. (2014, June). AFP financial planning and analysis learning system (
2nd ed.). Association for Financial Professionals.
Davidson, W. N. (2017). Financial forecasting and decision making. American Institute of Certified Public Accountants.
Sacks, A. , & Ryan, A. (2017). Lodging tax burden assessment. Oxford Economics.
Samonas, M. (2015). Financial forecasting, analysis, and modelling: A framework for long-term forecasting
(Wiley finance series). John Wiley & Sons.
Smith Travel Research. (2019). Trend report: Ventura, CA area selected properties. Hendersonville, TN.
Visit California. (2019). California travel and tourism: Overview of key drivers and outlook. Tourism Economics. https://industry.visitcalifornia.com/research/report/california-travel-tourism-forecast-state-2019-october
References
Besley, S. , & Brigham, E. (2018). CFIN (6th ed.). South-Western.
California Tax Data. (2020). California property tax information. https://www.californiataxdata.com/pdf/AssessmentDistrict.pdf
Chien, C.-L. (2014a, August 24). Budgeting vs. forecasting: What’s the difference? https://vgi168.com/2014/
08/28/budgeting-vs-forecasting-whats-the-difference/
Chien, Chia-Li . (2014b, August 24). Meet your business goals with forecasting: Creating a forecasting system.
https://vgi168.com/2014/08/28/meet-your-business-goals-with-forecasting-creating-a-forecasting-sys-
tem/
Civitas. (2017). Global tourism improvement district tax assessments. http://www.civitasadvisors.com/globaltid-matrix-10-14-2019/
Hartman, R. (1986). Tourism, seasonality and social change. Leisure Studies, 5(1), 25–33.
Hoffman, G. (2015). Ventura County West Tourism Business Improvement District. http://oxnard.granicus.com/MetaViewer.php?view_id=46&clip_id=3063&meta_id=150269
Kenton, W. (2019). Seasonality. Investopedia: economics. https://www.investopedia.com/terms/s/seasonality.asp
Matias, D. B. , & Hutchinson, M. (2016, October). AMA’s advanced financial forecasting and modeling. American Management Association.
Smith Travel Research (2020). Glossary. https://str.com/data-insights/resources/glossary/d
Sowa, L. (2017, September). Financial forecasting. American Management Association.
Tucker, B. (2019a). 2018/2019 VCC annual report video. Ventura County Coast. https://www.youtube.com/
watch?v=fcAF2vtWa-4&feature=youtu.be
Tucker, B. (2019b). 2019/2020 marketing plan. Ventura County Coast.
https://venturacountycoast.com/ventu- ra-county-coast-tourism-impact-summit-resources/
Tucker, B. (2019c). Marketing plan. Ventura County Coast.
https://venturacountycoast.com/wp-content/uploads/2019/09/VCLA_MarketingPlan_8.5X11_092319_WEB.pdf
https://dx.doi.org/10.4135/9781529758184
108.5
1.Review and analyse
the company
performance through
the Financial
Statements.
2. Why do VCLA’s
revenue spikes not
always occur at the
same time as
maximum room
demand?
Clearly and explicitly
analyses the performance
of the company over time,
using horizontal and
vertical analysis, variance
analysis and using
constant reference to the
case and external
resources to provide a
wider insight.
Students should clearly
demonstrate a clear
understanding of the
difference between
events and payments,
explaining how they do
not necessarily occur at
the same time.
Reference to the case
and external examples.
3. What is the
average historical
growth rate of VCLA
revenue?
Review the Forecast.
The average historical
growth rate is ?.
However, growth
since the inception of
the operation is not
sustainable. What
should they do?
Well-structured, detailed
and thorough analysis
and projections are
explained as a further
step from year to year
projections. All
assumptions should be
explained in terms of
changes in variances as
opposed to solely
numerical explanations.
4. What would the
sales growth rate be
in an economic
decline or upturn?
Review Scenarios.
Analyse the four
scenarios for growth
rate and marketing
A clear and accurate
analysis of the four
scenarios in conjunction
with a detailed
understanding of the
current economic climate
and reflect on how the
macro factors, combined
with their marketing
8.498
7.9-7
6.9-6
5.9-1
Clearly and explicitly
analyses the
performance of the
company over time,
using horizontal and
vertical analysis,
variance analysis and
using constant reference
to the case.
A strong analysis of the
performance of the
company over time, using
horizontal and vertical
analysis, variance
analysis and using
constant reference to the
case.
Clearly and explicitly An
analysis of the
performance of the
company over time, using
horizontal and vertical
analysis, variance
analysis and using
constant reference to the
case.
The numbers are not
adequately or reasonably
explained and / or either
horizontal, vertical of variance
analysis has not been included.
Students should
adequately
demonstrate a an
understanding of the
difference between
events and
payments, explaining
how they do not
necessarily occur at
the same time.
Reference to the
case and external
examples.
Well-structured, analysis
and projections are
explained as a further step
from year to year
projections. All assumptions
should be explained in
terms of changes in
variances as opposed to
solely numerical
explanations.
Students should
adequately demonstrate a
an understanding of the
difference between events
and payments, explaining
how they do not
necessarily occur at the
same time. Reference to
the case.
Students should
adequately demonstrate a
an understanding of the
difference between events
and payments. at the
same time. Reference to
the case and external
examples.
No understanding or adequate
explanation of the variance
between transactions and
payments or inadequate
examples from the case.
Adequate and reasonable
analysis and projections
are explained as a further
step from year to year
projections. All
assumptions should be
explained in terms of
changes in variances as
opposed to solely
numerical explanations.
All projections are
explained as a further step
from year to year
projections. All
assumptions should be
explained in terms of
changes in variances as
opposed to solely
numerical explanations.
The numbers are not
represented as variance and /
or the changes are adequately
explained.
A clear and accurate
analysis of the four
scenarios and reflect on
how the macro factors,
combined with their
marketing approach can
affect performance.
Reference to the case and
external information should
A clear and accurate
analysis of the four
scenarios and reflect on
how the macro factors,
combined with their
marketing approach can
affect performance.
Reference to the case is
imperative.
A good understanding of
the four scenarios and to
reflect on how the macro
factors, combined with
their marketing approach
can affect performance.
References to the case.
Failure to use the 4 scenarios
or demonstrate an
understanding of business
impact of either marketing and
/ or economic indicartors.
spending adjustment.
approach can affect
performance. Reference
to the case and external
information should be
used.
be used.
5. What financial and Review how room supply Review how room supply
Understand the
economic
may impact VCLA revenue may impact VCLA revenue relationship between
assumptions must be and GDP data, reflecting and GDP data, reflecting on room supply and GDP
considered to develop on the relationship
the relationship between
reflecting on how both
the forecast?
between room supply and room supply and GDP
situations may impact
GDP reflecting on how
reflecting on how both
the market. Reference
both situations impact the situations may impact the
to the case and external
market. Reference to the market. Reference to the
sources.
case and external sources case and external sources.
is a must..
Show an understanding of
No clear understanding of the
the relationship
between room supply
and GDP reflecting on
how both situations
may impact the market.
Reference to the case
and external sources.
relationship between room
supply and GDP reflecting
on how both situations may
impact the market and / or
no reference to the case
and / or external sources.
Forecasting tourism tax receipts: the case of Ventura County Lodging Association
Developed by:
Chia-Li Chien, PhD, CFP®, PMP®
John F Thiel, CFP®, MBA
Stefan W Cosentino, Ph.D.
Version:
Tabs in This File:
2020.3
3/18/2020
Description
FinancialStatements VCLA Financial Statements from 2013 to 2017
Benchmark
STR Summary Benchmark from 2012 to 2019
RevenueBenchmark Revenue Benchmark
DemandBenchmark Demand Benchmark
Demand_Re_Bench Demand Relative to Benchmark
Revenu_Re_Bench Revenue Relative to Benchmark
Historical Analysis
2013
2014
2015
2016
2017
Assumptions
Information were obtained from Tax Returns from 2013 through 2017
IRS publication 598 (Rev. February 2019) Tax on Unrelated Business Income (UBI or UBTI) have no cap & exclusions of interestes, dividends, etc.
Therefore, tax-exempt status not jeopardized: : https://www.irs.gov/pub/irs-pdf/p598.pdf
(Jul 1 – June 30) Fiscal year
Income Statement
Program Service Revenue
Total Expenses
Gross Profit
1,571,211
1,605,842
(34,631)
1,938,969
1,635,219
303,750
2,538,303
2,230,334
307,969
2,900,151
2,447,184
452,967
2,923,280
2,474,605
448,675
Assets
Cash – non interest bearing
Total Current Asstes
449,213
449,213
754,953
754,953
1,067,884
1,067,884
1,522,646
1,522,646
1,977,413
1,977,413
Non-Current Assets
Land, buildings, & Equipment
Less: accumulated depreciation
Land, buildings, & Equipment, net
Other assets (due from credit card)
Total Assets
5,948
740
5,208
2,346
456,767
6,855
2,312
4,543
1,021
760,517
6,855
3,974
2,881
1,070,765
6,855
4,841
2,014
1,524,660
6,855
5,320
1,535
1,978,948
Liabilities & Net Assets
Other Liabilities (credit card payable)
Total Liabilities
–
–
2,279
2,279
3,207
3,207
8,820
8,820
456,767
760,517
1,068,486
1,521,453
1,970,128
369,510
4,300
7,639
37,610
9,894
7,337
10,970
15,965
1,572
4,689
1,132,833
19,390
5,442
4,533
3,535
1,635,219
1,622,677
372,555
5,700
11,452
4,098
15,320
2,169
15,074
15,426
10,068
1,662
5,775
1,732,275
25,383
6,120
5,400
1,857
2,230,334
2,213,598
246,333
9,400
18,958
3,500
7,667
5,161
18,133
17,248
3,430
867
6,481
2,072,005
29,002
4,277
4,245
477
2,447,184
2,428,184
180,560
27,475
23,911
246,506
11,357
7,421
17,124
12,287
635
479
5,084
1,897,613
29,233
7,292
7,355
273
2,474,605
2,457,002
straight line
502,386
straight line
498,059
MACRS
375,179
MACRS
576,992
Balance Sheet
Net Assets
Expenses Claimed on Tax Returns
Expenses
Mangement
Legal
Accounting
Other Fees & Services Expenses
Office Expenses
Information Technology
Occupancy (rent)
Travel
Payments for travel or entertainment for any federal, state, or local public officials
Confferences, conventions, & meetings
Depreciation, depletion, & amortization
Insurance
Marketing & Sales Promotion
Collection Fees
Dues & Subscriptions
Telephone
All other expenses
Total Functional Expenses (Federal)
Total Functional Expenses (State) separate lines for rents & depreciation
Menu
Source: 1084466_Ventura CA Area Se spreadsheet
Demand By Revenue By
% Demand % Revenue
Measure
Measure Average by Measure by Measure
Average
Monthly
(change)
(change)
Monthly
2012
96,050
9,126,951
2.1
4.7
2013
97,896
9,556,567
6.0
13.1
2014
103,543
10,782,144
3.5
11.3
2015
106,887
11,981,718
4.2
12.3
2016
111,209
13,405,411
(0.9)
1.8
2017
109,689
13,492,306
(2.3)
2.3
2018
106,725
13,674,462
(4.8)
(2.2)
2019
100,073
12,151,451
2.1
7.6
Source: Smith Travel Research (2019). Trend Report – Ventura, CA Area Selected Properties. Hendersonville, TN.
Average Revenue by Month – STR Trend Report
18000000
17000000
16000000
15000000
14000000
13000000
12000000
11000000
10000000
9000000
8000000
January
February
March
April
May
June
July
August
September
October
November
December
Average Demand For Rooms by Month – STR Trend Report
130000
125000
120000
115000
110000
105000
100000
95000
90000
85000
80000
January
February
March
April
May
June
July
August
September
October
November
December
Demand Relative to Average Demand by Month – STR Trend Report
140000
140,000
120000
120,000
100000
100,000
80000
80,000
60000
60,000
40000
40,000
20000
20,000
0
0
January
February
March
April
May
June
Demand Benchmark
July
August
2019 Demand
September
October
November
December
Revenue Relative to Average Revenue By Month – STR Trend Report
$18,000,000.00
16,000,000
$16,000,000.00
14,000,000
$14,000,000.00
12,000,000
$12,000,000.00
10,000,000
$10,000,000.00
8,000,000
$8,000,000.00
6,000,000
$6,000,000.00
4,000,000
$4,000,000.00
2,000,000
$2,000,000.00
$-
0
January
February
March
April
May
June
Revenue Benchmark
July
August
2019 Revenue
September
October
November December