Technical and Scale Efficiency in Nursery Enterprises in an Area of Significant Widespread Horticulture in Italy

The aim of this work is to identify the factors that influence the level of efficiency in horticultural nurseries and to estimate their impact on productivity as well as the direction and intensity with which they act. The investigation was focused on table tomatoes (Solanum lycopersicum L.), a species widely cultivated in horticultural greenhouses and in the open field, for which the recourse to transplantation represents a normal operation to the point that nurseries activate a large number of productive cycles for this species throughout the year with the aim of obtaining ‘‘ungrafted seedlings’’ or ready-to-use ‘‘grafted seedlings’’. This study used the methodological approach of data envelopment analysis (DEA) and Tobit regression and was able to identify which of the factors linked to management choices, professionalism, and the motivation of entrepreneurs have a notable influence on the level of efficiency reached by nurseries and which of these factors offer possibilities for increasing their levels of production. The results of this investigation reveal that in the nurseries, the possibilities for achieving increasing economies of scale are limited by the structural relationships between capital and land and between land and labor, by the production strategies in place, and by the degree of utilization of materials and labor. Nursery activities hold a significant importance in the construction of the value chain of the horticultural sector (Source: European Nursery Stock Association—ENA on European nursery stock sector available on www.enaplants.eu; European Horticulture Network—EHN and U.S. Department of Agriculture National Agricultural Statistics Service, 2012 Census of Agriculture). Their importance is increasing for a country such as Italy, in which horticulture both in the open field and under shelter contributes significantly to the creation of income and employment and the socioeconomic sustainability of entire territories. The favorable performance of this sector, along with studies in the scientific literature related to technicaleconomic and market matters, suggests that there is an opportunity to expand the use of transplantation techniques even more widely as an alternative to sowing directly in the field to achieve advantages of a technical, environmental, and commercial nature (Power et al., 1991; Timpanaro et al., 2015). Modern nurseries have therefore become complex and articulated structures, marked by intensive cultivation systems with considerable utilization of fixed and circulating capital and ways of managing production processes. These systems have allowed an elevated degree of integration and coordination, along with market relationships, for the supply of raw materials and the placement of finished products that are no longer circumscribed at the territorial level but are directed toward interregional or national dimensions. This organizational complexity is linked to the multiplicity of production cycles realized (in all of the cases, the sowing is done directly in multiholed containers inside greenhouses to control the entire process and guarantee the result from qualitative– quantitative and phytosanitary points of view) and to the simultaneous presence of many sectors within the nursery structure that are able to assure a determined phase of the ‘‘seedling multiplication’’ productive process (collections of mother plants, seed beds, greenhouse cultivation, etc.) with the parceling of the enterprise’s surface area, which renders the management of this business activity and the reaching of adequate levels of profitability somewhat difficult (Kubota et al., 2017; Rivard et al., 2010). This also occurs because, technically, the nurseries are multiproduct enterprises (many species and varieties and many cultivation cycles on the same unit of surface area within the same greenhouse in the same year), characterized by returns to scale that oscillate between constants, increasing and decreasing, in different production systems. Thus, only a limited number of enterprises manage to realize productive volumes capable of generating economies of scale and, therefore, of increasing net profits. The contribution of this work lies, essentially, in exploring these aspects of nursery management and assessing to what extent the economic results of these activities could be attributable to differences in the efficiency of the nursery. The results are provided through the DEA method, a nonparametric method of analysis that is particularly versatile for the study of the efficiency of productive units and that is widely used for analyzing multiple input/output processes and for determining a score of relative efficiency between different enterprises/productive processes. The objective, therefore, is to evaluate the relative efficiency of each nursery in terms of radial distance from the efficient frontier, defined by best practices, and to identify the variations in the factors necessary so that an inefficient nursery emulates the benchmark (the group of nurseries of reference on the frontier). Finally, on the basis of a multivariate Tobit-type analysis, an estimation of the influence of a series of key variables preselected from among the technical-economic, structural, and managerial factors that are most relevant on the efficiency indicator is made. Conceptual Framework The DEA technique was originally defined by Charnes et al. (1978) with the intention of developing Farrell’s measure of efficiency and making it operative in the field of linear programming. Starting from the research of Farrell (1957), a conceptual framework was developed for the analysis of an enterprise’s performance in terms of economic, technical, and allocative efficiency. The largest advantage of this type of analysis lies in the fact that it allows a global approach to the enterprise, simultaneously considering all the inputs and outputs (Coelli, 1995) rather than considering them in terms of yield, e.g., per unit of input entered. From its original inception, DEA has rapidly spread to a multitude of fields of application and business sectors, from the public to the private, and has fueled a broad Received for publication 15 Aug. 2017. Accepted for publication 15 Dec. 2017. This study was carried out with the financial support of the Assessorato Risorse Agricole e Alimentari, Regione Sicilia ‘‘Progetto Sementiero Regionale—Analisi economiche’’ (Giuseppe Timpanaro, scientific coordinator) and FIR 2014 on ‘‘L’innesto erbaceo del pomodoro: qualit a e sostenibilit a delle produzioni’’ (Francesco Giuffrida, scientific coordinator). The study is the result of full collaboration and therefore all authors accept full responsibility for it. The actual writing of sections ‘‘Introduction,’’ ‘‘Analysis of the cause factors of inefficiency in the nurseries,’’ and ‘‘Concluding considerations’’ is attributable to Giuseppe Timpanaro; the section ‘‘Conceptual framework’’ and ‘‘Economic results and production costs’’ is attributable to Arturo Urso; and the section ‘‘Materials and Methods,’’ ‘‘Characteristics of the nurseries investigated,’’ and ‘‘Results of the analysis of efficiency with the DEA method’’ is attributable to Vera Teresa Foti. Corresponding author. E-mail: giuseppe.timpanaro@ unict.it. 208 HORTSCIENCE VOL. 53(2) FEBRUARY 2018 debate on goodness and limits of application. Liu et al. (2013) published an article in which they use the Web of Science database 1978– 2010 and present the results of research on the applications made possible by DEA thus far. With reference to the agri-food sector, it is possible to find vast literature on the use of DEA to determine the competitiveness, productivity, and efficiency of the sector and on the use of alternative tools. Certain useful comparative contributions are based on the parametric analysis of the stochastic and nonparametric (DEA) frontier in an attempt to combine the virtues of both approaches into a unitary framework that is applicable to retail and wholesale distribution (Kuosmanen, 2006). Among other contributions, we highlight that of Bonfiglio (2006), who measured the results of Italian agro-food cooperatives [also using a Tobit regression analysis for identifying differences in technical efficiency (TE)], and that of Aramyan et al. (2006), who analyzed various performance indicators of the agri-food supply chain. In regard to the role of cooperation, the work of Fanfani and Maccarini (2009) demonstrated the imbalance between the size of a cooperative and the levels of production achieved through DEA. Latruffe (2010), moreover, suggested a revision of the literature to redefine the concepts of productivity and performance and to illustrate the methods of measurement and the possible obtainable results. Dadura and Lee (2011) used DEA to determine the key factors of innovation in Taiwan’s food industry and to define appropriate strategies for improving innovative capacity, taking into account the size of the enterprise. Mutonyi and Gyau (2014) proposed a conceptual model of measurement of marketing performance based on five constructs: efficacy, efficiency, adaptability, the quality of food products, and customer satisfaction, in light of the increased opportunities of the market created by globalization and the growing demand for traceability, food safety, and standards of quality. Pagotto and Halog (2016), moreover, proposed the principles of the circular economy for increasing the performance of environmental sustainability in the agri-food industry with economic and environmental measures. Finally, Folinas et al. (2015) shifted their attention to the logistical processes of the agri-food sector, proposing DEA as a means to determine the criticalities for the customer, the costs, and the contribution of logistics to the added value of services and products. Furthermore, there are numerous applications of DEA to specific productive sectors. Among many such studies, we re