Зеленская_резюме_англ (Оценка эффективности деятельности учреждений культуры (на примере театральных учреждений))

National Research University Higher School of EconomicsElena ZelenskayaPERFORMANCE MEASUREMENT OF CULTURAL ORGANIZATIONS:THE CASE OF THEATRICAL INSTITUTIONSPhD Dissertation Summaryfor the purpose of obtaining academic degreePhilosophy Doctor in Economics HSEAcademic supervisor:Professor Valery E. Gordin,Doctor of Science in Economics,JEL: С14, L82, Z11Moscow – 20182Problem DescriptionCultural services are merit goods that bring both individual and public benefits and play acrucial role in maintaining public well-being and ensuring social justice. Economic hurdles thatoccurred during the crisis period in the first decade of the XXI century concerned all spheres ofthe public sector and pushed cultural organizations to compete with other sectors for diminishingbudget funding and to confirm their right for receiving a share of public money.

As a result of adifficult economic situation sponsors and donors demand more sophisticated accounts aboutperformance of supported organizations. Competition in the cultural sphere is becoming moreintense: the number of cultural organizations of various scale and ownership type is growing, thescale of alternative entertainment services is getting wider and they are attracting consumerattention.

Development of creative industries that function according to the market rules also affectthe level of competition. At the same time, according to statistics, in most cultural spheres agrowing volume of supply does not lead to a growth in demand for cultural services.As a result nowadays cultural organizations face increased pressure of their keystakeholders – state and municipal authorities, sponsors, donors and consumers. This situationforces managers of cultural organizations find ways of increasing performance and gettingstandardized and transparent information about their achievements.State and municipal authorities that are responsible for cultural policy and overalldevelopment of the cultural sphere, while practicing result-oriented budgeting and programmebased funding, are in need of clear mechanisms of comparison of cultural organizations’performance for grounded decision-making.According to some researchers [Gordin, Khoreva, 2012], currently in Russia there is a lackof an integrated performance measurement system of cultural organizations and regionalsubsystems in the cultural sphere.

In this study we focus on one side of performance – efficiency– which is understood here as comparison of outputs with inputs required for getting a particularlevel of outputs.So far mostly international scholars rather than the Russian ones have studied the problemof relative efficiency of cultural organizations. Efficiency measurement of Russian culturalorganizations has not been investigated deeply in existing scientific literature. Methodologicalissues also remain underexplored. The presence of a wide range of insufficiently studiedtheoretical and practical issues concerning performance measurement of cultural organizationsexplain for the necessity of this kind of study.3Literature ReviewAn economic approach to culture was incepted in the works by W.

Baumol and W. Bowenwho studied performing arts organizations and were the first to draw attention to economic hurdlesin the cultural sphere related to unique production processes of cultural services. They introducedthe notion of “cost disease” into scientific discourse. Later on, key problems in the field of culturaleconomics were investigated by Russian and international scholars, namely by T. Abankina,Y.

Avtonomov, D. Bukovinsky, V. Gordin, L. Khoreva, M. Matetskaya, V. Muzychuk,A. Rubinshtein, V. Tambovtsev, D. Throsby, R. Towse, L. Weinstein, and others.The study of culture as a part of the social sphere, research of trends in production ofcultural services and specific features of cultural consumption was done in the works by I. Blagova,B. Frey, R. Grinberg, L.

Jakobson, D. Maslova, R. Musgrave, V. Radaev, B. Rudnik, andB. Weisbrod.Approaches to the notion of performance in the cultural sphere were discussed by thefollowing scholars: F. Badia, C. Camarero, A. Dolgin, F. Donato, G. Evans, M. Garrido,I. Gilhespy, M. Koshkina, K. Lindquist, G. Smentsarev, R. Smith, A.

Street, A. Tochilkina,E. Vicente, L. Zan, and A. Zorloni.Several scholars have studied the problem of efficiency measurement of culturalorganizations using the balanced scorecard, as well as unbalanced systems of indicators. Theseresearchers are: E. Khaunina, K. Krug, K.

Laurine, V. Muzychuk, O. Paulus, G. Smentsarev,J. Turbide, and C. Weinberg.The study of relative efficiency of cultural organizations based on econometric methodswas done primarily by international scholars, such as A. Last, A. Basso, P. Bishop, S.

Brand,M. Castro, M. del Barrio, S. Funari, C. Guccio, L. Herrero, P. Hughes, F. Marco-Serrano, I. Rizzo,H. Wetzel, M. Zieba.Taking into account the contribution of the above-mentioned authors, we should emphasizethat the problem of performance measurement of cultural organizations remains insufficientlystudied. In particular this fact concerns research on Russian cultural organizations: to the author’sknowledge there are no studies made by Russian scholars on the problem of relative efficiency ofcultural organizations based on econometric methods.

Moreover, most existing internationalresearch focuses on one type of cultural organizations – museums, is characterized by relativelysmall samples and as a rule was conducted in the European context. This may limit the theoreticalcontribution of existing studies.4Thus, it seems important, firstly, to propose a standardized and transparent methodologicalapproach that allows for efficiency measurement and comparison of a large number of culturalorganizations of various types, and secondly, to test the suggested methodology on empirical dataabout Russian cultural organizations.Objectives of the ResearchThe main aim of the research is to propose a methodological approach for measuringefficiency of cultural organizations and to test the proposed methodology on the case of Russiantheatrical institutions.In order to reach the main aim, we should fulfill the following objectives:1.

To analyze existing approaches and methodologies of performance measurement in thecultural sphere;2. To develop a set of performance indicators applicable to measuring relative efficiency ofcultural organizations;3. To outline existing groups (clusters) of Russian theatres and to describe their distinctivefeatures;4. To conduct relative efficiency measurement within the outlined clusters of theatres;5. To distinguish internal factors that affect efficiency of cultural organizations;6. To analyze the impact of efficiency on consumer satisfaction level.MethodologyUsing the case of Russian theatres the author develops a multi-stage methodology forrelative efficiency measurement of cultural organizations based on a set of econometric methodsthat are not typical for the cultural sphere.

The main source of empirical information is statisticaldata on theatrical institutions gathered by the Ministry of Culture of the Russian Federation inyears 2012-2016 (3182 observations). The author also uses data from www.tripadvisor.com,namely the overall ranking of cultural organizations that is viewed in this study as consumersatisfaction level. For data processing we use STATA 11 and Efficiency Measurement System(EMS).Empirical study consists of several stages.Firstly, we analyze a set of 49 theatre performance indicators using principal componentanalysis (PCA).

We identify a set of latent constructs (principal components) that represent a useful5research tool for measuring performance in the cultural sphere. We use this set at later stages ofempirical research. PCA helps to reduce the number of variables while losing little informationthat explains the variance of the sample. The author distinguishes three types of indicators: inputs,outputs and outcomes.Secondly, we analyze the whole population of Russian theatres using k-means clusteranalysis based on the principal components that are previously distinguished. The clustersrepresent theatres having similar characteristics, however they are very much heterogeneouscompared to theatres in other clusters.

This stage of empirical analysis aims to identify theatreprofiles that are important for performance measurement, and to describe their key characteristics.Moreover, we use clusters at further research stages. We assess relative efficiency within clustersthat represent relatively homogeneous groups of objects.Thirdly, we measure relative efficiency of theatrical institutions within the clusters using anon-parametric tool – data envelopment analysis (DEA). Principal components describing inputsand outcomes are used as variables here.

We use DEA input-oriented model. There is also anothermodel that maximizes the results, the so-called output-oriented model. These specifications implydifferent types of efficiency measurement that depend on the mission and aims of the objects underanalysis. We believe that in a study that investigates theatres or other non-profit organizations inthe cultural sphere, input-oriented model is more suitable due to the following reasons:Key outcome indicators (for example, attendance) depend on some external factors such asarea and population size, touristic appeal, ease of reach, infrastructure, etc.Some outcome indicators have a natural maximum limit that is explained by venuecapacity, opening hours or time when performances are staged (usually in the evenings).Input-oriented model complies with current trends in the public sector, such as tighterrestrictions on budget spending and increased accountability.In the study we use different performance indicators to create several efficiency modelsbecause we assume that a cultural organization may be efficient in one aspect (for instance, interms of revenues) and inefficient in another one (for instance, in terms of attendance).

Thus weuse several DEA models (Table 1).6Table 1. Performance indicators used in efficiency measurementIndicatorInputsNon-financial resourcesFinancial resourcesOperating expendituresCapital expendituresOutcomesTotal attendanceLocal attendanceGenuine popularityRevenuesAmount of spectators at children performances*Revenues from children performances*Model 1‘Attendance’Model 2‘Revenues’Model 3‘Work withchildren’♦♦♦♦♦♦♦♦♦♦♦♦♦♦♦♦♦♦*original indicators; in all other instances principal components are usedSource: own elaborationThree research stages represent a consecutive chain of data analysis.

The use of the abovementioned methods is not a random choice. Scientific literature [Del Barrio, Herrero, Sanz 2009;Sarkis, 2007] validates implementation of cluster analysis as a tool for data pre-processing forfurther efficiency measurement using DEA. Cluster analysis helps to maximize homogeneitywithin sub-samples and heterogeneity between different sub-samples. A joint use of principalcomponent analysis and data envelopment analysis helps to increase DEA discriminatory powerbecause the method is sensitive to the ratio between the number of investigated objects (decisionmaking units, DMUs) and variables [Adler, Golany, 2007].