PLANNING ART ~~SE~~ EXHIBITIONS

LINDA SPEAR and ERWIN SANIGA

Department of Business Administration, University of Delaware, Newark, DE 1971 I, U.S.A.

Abstract-In this paper, we develop an integer programming model for use by art museums to plan cost effective temporary special exhibitions. By using a model based plan for organizing the changing exhibitions, the museum’s professional staff can identify the timing and selection of exhibits to maximize attendance. We consider both the fixed and variable costs incurred in designing and organizing an exhibition as well as revenues generated by admission charges and museum shop sales after its installation.

INTRODUCTION

THIS paper explores the use of an integer programming model to determine which museum exhibits should be shown when in order to maximize profit. Our concern is with art museums, although similar applications could be made to both history and science museums. Our model takes into consideration both inherent fixed costs and certain variable costs associated with the design and installation of exhibits as well as specific revenues generated by both museum shop sales and exhibition catalogue sales.

BACKGROUND MATERIAL & PROBLEM DESCRIPTION

A distinguishing feature of the administration of art museums is their management by crisis [ 1, p. ZOO]. This resulting situation often exists either because there is both a lack of communication between the respective roles of the artistic director and the administrat- ive director as well as a lack of clearly-defined budgetary goals cl, pp. lOO-1011. Artistic budgets, when they can be operationally defined, often revolve around the financial breakeven point. The goal is usually minimizing the overall deficit rather than maximiz- ing the profits of the revenue-producing factors.

Because of the lack of forecasting methodology and data collection, it is easy for the artistic director to overestimate operational revenue and underestimate expenses incurred in producing that revenue. Also, the artistic director often “tends to procrasti- nate in decision-making and make frequent changes in attempting to improve his cre- ation” [ 1, p. 1001. Thus, many problems, some of which possibly could be anticipated by reference to a quantitative model, are individually treated as a crisis. We recognize that not all administrative decisions by an artistic director can be quantitatively-based; often, an artistic director has to make aesthetic decisions substantiated merely by his/her own creative impulses [2, pp. 654-6641.

In principle, the museum exists to provide an educational experience via its collec- tions and its related programs to the greatest number of people [3, p. 25-J. This was selected by 947; of all museum directors as their predominant aim. But underutilization of the facility is one of the greatest problems facing museums [4, p. 951, and there is often a fluctuation of attendance figures at a museum. A museum’s staff could exhaust its collective energies and the current budget pursuing higher attendance figures and a consistent publicity campaign about special exhibitions, perhaps even sacrificing their collecting and conserving duties. ’

Perhaps a better approach would be to forecast or predict the approximate attend- ance figures for different exhibits staged at various times during the calendar year. Certain historical facts such as attendance figures for previous shows of a similar nature to the ones being currently planned are readily available and could be included in the forecasting model?. Moreover, such a model, if successful in predicting profitable shows,

t The development of a linear regression model to determine the effect of prices and hours on museum utilization was conducted in a study at the Boston Museum of Fine Arts [S].

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128 LINDA SPEAR and ERWIN SANIGA

could help alleviate the financial strain of museums. Continuing inflation forces museums to be caught in a ‘cost reduction syndrome’ where budget equilibrium is achieved by sacrifices of important services and personnel rather than by income improvement [6, p. 11. In spite of the museum’s tax-exempt status which encourages public support, there is a “growing recognition that the traditional sources of financial support are no longer sufficient to carry on, let alone expand, the programs of the museum” [7, p. 111. Moreover, any profits which could be generated for the museum’s purchase fund are expecially important now since great works of art are competitively bargained for on the world’s art market.

Therefore, the need for additional funds appears axiomatic. One solution to this problem would be the museum’s attempt to increase revenues from its admission charges, a principal source of a museum’s unrestricted fund accounts [S, p. 73. Since the amount of funds generated is contingent upon the total annual attendance figures, it logically follows that where possible a museum should strive to maximize attendance figures for specific exhibitions.

“Attendance figures are one measure of the museum’s success in discharging its obligations to the public” [3, p. 471. According to the NEA (National Endowment for the Arts) survey findings, the total art museum annual visitation has been estimated to be 43,024,OOO for the year 1971-1972 [4, p. 741, but there is difficulty in determining actual attendance levels in museums because there is a low priority for keeping accurate records-this points to one of the main obstacles in fact finding. Similar to “the lack of standardization and reconcilability of a museum’s accounting system,” only about 30% of the museums interviewed (by the NEA survey which included all museum types) were able to base their responses to attendance questions on actual counts [3, p. 473. With regard to the operating revenues of art museums, 29% was contributed by admissions and shop-sales [4, p. 851.

“When attendance increases, there are added demands placed on the museum’s staff and facilities. Yet, 9 out of 10 of the nation’s museum directors reported that they are interested in attracting more visitors to their museums” [6, p, 47). Granting the difference between the intention and its realization, the integer programming model soon to be introduced in this paper could aid the director’s efforts to increase the museum’s attend- ance figures.

DEVELOPMENT OF THE MODEL

In formulating the model it is important to recognize some of the major problems confronting museum directors. Questions that are often raised when exploring opportu- nities for art exhibitions are (1) what type of exhibition should be shown; some alterna- tives include, (a) in-house exhibitions where the objects displayed are taken from the museum’s permanent collection; (b) consortium-based exhibitions, objects taken collec- tively from various collections within the United States, and (c) international exhibitions, based upon the co-operative diplomatic exchange or borrowings from foreign museums and/or private collections; (2) when to schedule these exhibitions during the calendar year; (3) which exhibitions are the ‘crowd drawers’; (4) whether exhibitions can be reflec- tive of current events or areas of sociological significance: and (5) exhibitions which will appeal to a broad segment of the public en masse.

The core of the programming model must take into account certain costs which are associated with any exhibit. By taking into consideration specific costs incurred (what the system demands) as well as the revenues generated (what the system supplies), the model can allow for more cost efficient use of museum facilities.

The costs associated with organizing an exhibition can be subdivided in one of two types; fixed and variable. To a large extent, the fixed costs have to be considered in relation to a specific museum. Some costs which might be termed variable for a small art museum would be part of the fixed cost of operations in a large museum, such as the Metropolitan Museum, New York. For example, a small museum might have to increase its security staff for a special exhibition and thereby incur additional salary expense,

Planning art museum exhibitions 129

while no additional staff would be necessary for a major museum, perhaps only a differ- ent allocation or assignment of the guards.

In general, certain fixed costs might include: the cost of heating and/or air condition- ing the exhibition rooms, the costs incurred in lighting and maintaining normal environ- mental controls (humidity check), the costs of designated guard positions, museum staff salaries and fringe benefits.

The various components of the variable costs attributed to any temporary exhibition are outlined below [93.

Variable costs of an e~~ibitio~: Organizing and administration:

0 Selector’s .fee. 0 Selector’s expenses. l Gallery organizer’s expenses. l Attendants’ wages. 0 Catalogue sellers’ wages.

Insurance 0 Premiums calculated according to the value of the work as well as the ‘transit’ and

‘stay’ risks.

Transport, packing and handling l Packing, casemaking, crating.

f~?sta~~ation (moderate to extensive as in “Treasures of Tutankhamen” exhibit at the Metropolitan Museum).

0 Repainting and refurnishing. l Labels. 0 Exhibition contractor’s fees. 0 Exhibition designer’s fees. 0 Materials.

Pri?~t~ng 0 Catalogue typesetting and print~ost/distribution costs, l Author’s fee. l Photography. 0 Color plates. l Copy typing. 0 Translator’s fee (if applicable). 0 Overprinting costs.

Publicity 0 Advance notices. 0 Mailing lists. 0 Media advertising. 0 Press view.

Balancing the costs, there are specific forms of revenue generated. For any financial year, the operating income (revenues minus expenses or costs) of a museum “has a rhythm of its own, set largely by the number of visitors, (and) major special exhi- bitions. . . ” [2, p. 681. Many museums consistently depend on receipts from various activities for a cash flow to keep them operating [4, p. 90-J; these receipts may take the form of admission charges from special exhibitions having great popular appeal, as in the exhibitions of Van Gogh paintings or more recently the sensationalism aroused by the Treasures of Tutankhamen.

The overall returns for the museum sales shop is likewise affected by general attend- ance figures and the popularity and frequency of special exhibitions [lo, p. 911. The cash flow may be augmented by the revenues collected from the sales of photographs, posters,

130 LINDA SPEAR and ERWIN SANIGA

prints, slides, and notecards. More importantly, the exhibition catalogue accounts for a significant portion of the general sales.

The integer programming model

Suppose there are i = 1,2,. . . , n candidate exhibitions, some of which may be assigned over j = 1,2, . . . , m periods in a horizon. Define the following terms:

pij = Total profit for a particular exhibit shown in a particular period. Pi = Admission charge per person-price estimated on past exhibits (taking into

consideration student discounts and senior citizens discounts). Nij = Number of people attending a particular i-th show in a particular j-th period.

(This number will have to be estimated from previous exhibits of a similar nature.)

cij = Fixed costs associated with that particular i-th shown in period j. Cij = Possible variable costs of the i-th show which depend on Ni attending (such as

extra security guards, inc. a/c and heating) in period j. KflS = Museum sales’ associated with the sale of visual material, i.e. post cards, prints,

IJ

etc., associated with a particular exhibit in period j. Xi = The fraction of people who buy this visual material who have come to this

particular exhibit. KY = The production costs associated with the manufacture and marketing of this

material in period j. K~j = The sale of the exhibition catalogue associated with the particular i-th show in

period j. ~j = The production costs associated with the manufacture and marketing of this

catalogue in period j.

Let the variable Qij = iO,l I; if Qij = 1 we will assign the i-th exhibit to the j-th time period. Moreover, we require that no special exhibit will be repeated in some finite horizon of length m; this is in accord with standard museum practice. In addition there is usually some upper limit 1 on the number of special exhibits shown simultaneously and this depends upon the size of the museum. For example, the Metropolitan Museum in New York may have 3 special exhibits shown simultaneously while the Brandywine River Museum, Chadds Ford, Pennsylvania, has an upper limit of one. The two con- straints discussed above can be written as:

i$l Qij I 1, j = 1,2,...,m

j$l Qij 5 1, i = 1,2,. . . , n (2)

Suppose attendance goals are Aj for the j-th period. Then,

i$i QijNij 2 A,, j = 1,2,. . . , m (3)

The objective is to maximize profit over the finite horizon of length m. And for any exhibit i shown in period j, the total profit is:

Hij = PiNij - (i - CijNij + [Xi(K~S - RgS) + (KS - R$)Nij]i (4)

The complete problem can be stated over the horizon as:

:y f i HijQij

i=l j=l

ST i QijIl, j= I,2 ,..., m i=l

Planning art museum exhibitions 131

jiI Qij s 1, i = 1,2,. . . , n

ii1 QijNij 2 Aj, j = 1,2,...,m

Qij= IO, 1)

While it is common to schedule exhibits considering attendance goals such as described in the last set of constraints, it may be more reasonable to state these in terms of net profit goals per period, say NPj. Here. we could substitute for the last set of m constraints

iit QijPij 2 NPj, j = 1,2,...,m

We are constructing a case example of the above model based on data collected from the Metropolitan Museum in New York. It may be of interest to note that the major problems we find involve accurate determination of costs and attendance figures for past exhibits; even though this data is available it is usually on an aggregate basis.

CONCLUSIONS

Because of inflation, there is an increasing need for museum management to explore opportunities for maximizing the profits of its revenue-producing areas rather than mini- mizing its overall deficit. A museum’s professional staff could easily deplete its energies to pursue increased attendance by not knowing what data would be useful to forecast, which particular exhibitions should be installed when to attract the widest possible audience.

The integer programming model we develop in this paper proposes a possible sol- ution to the above-mentioned problems. The model based plan provides an organiz- ational framework for the museum director by defining what data needs to be collected and how it can be used for specific calendar dates to predict and schedule successful future exhibitions.

Though some might argue that it is inappropriate to apply objective models for aesthetic decisions, our model based plan provides a framework against which a museum director can critically analyze his/her own professional judgment in planning a successful exhibition schedule.

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