Productivity and Efficiency of Small and Large Farms in Moldova

The paper presents a comparative analysis of the productivity of small and large farms in Moldova based primarily on cross-section data from three farm surveys conducted by the World Bank and USAID in 2000 and 2003. The survey data are supplemented where feasible with time series from official national-level statistics. We calculate partial land and labor productivity, total factor productivity, and technical efficiency scores (using Stochastic Frontier and Data Envelopment Analysis algorithms) for the two categories of small individual farms and large corporate farms. Our results demonstrate with considerable confidence that small individual farms in Moldova are more productive and more efficient than large corporate farms. This finding is not restricted to Moldova, as a similar result has been obtained by other authors in Russia (2005) and in the U.S. (2002), where a recent study has found that an increase of farm size reduces, rather than increases, agricultural productivity. Policies encouraging a shift from large corporate farms to smaller individual farms, rather than the reverse, can be expected to produce beneficial results for Moldovan agriculture and the economy in general. The government of Moldova should abandon its inherited preference for large-scale corporate farms and concentrate on policies to improve the operating conditions for small individual farms. At the very least, the government should ensure a level playing field for farms of all sizes and organizational forms, and desist from biasing its policies in favor of large farms.Land Economics/Use,

PRODUCTIVITY AND EFFICIENCY OF SMALL AND LARGE FARMS IN MOLDOVA

The paper presents a comparative analysis of the productivity of small and large farms in Moldova based primarily on cross-section data from three farm surveys conducted by the World Bank and USAID in 2000 and 2003. The survey data are supplemented where feasible with time series from official national-level statistics. We calculate partial land and labor productivity, total factor productivity, and technical efficiency scores (using Stochastic Frontier and Data Envelopment Analysis algorithms) for the two categories of small individual farms and large corporate farms. Our results demonstrate with considerable confidence that small individual farms in Moldova are more productive and more efficient than large corporate farms. This finding is not restricted to Moldova, as a similar result has been obtained by other authors in Russia (2005) and in the U.S. (2002), where a recent study has found that an increase of farm size reduces, rather than increases, agricultural productivity. Policies encouraging a shift from large corporate farms to smaller individual farms, rather than the reverse, can be expected to produce beneficial results for Moldovan agriculture and the economy in general. The government of Moldova should abandon its inherited preference for large-scale corporate farms and concentrate on policies to improve the operating conditions for small individual farms. At the very least, the government should ensure a level playing field for farms of all sizes and organizational forms, and desist from biasing its policies in favor of large farms.family farms, corporate farms, comparative performance, technical efficiency, total factor productivity, agrarian reforms, transition countries, Farm Management, D24, J24, P27, P31, P32, Q12, Q15, R14,

Testing the hospital value proposition: An empirical analysis of efficiency and quality

Purposes: To assess the relationship between hospitals’ X-inefficiency levels and overall care quality based on the National Quality Forum’s 30 safe practices score and to improve the analytic strategy for assessing X-inefficiency. Methodology: The 2005 versions of the American Hospital Association and Leapfrog Group’s annual surveys were the basis of the study. Additional case mix indices and market variables were drawn from the Centers for Medicare and Medicaid Services data sources and the Area Resource File. Data envelopment analysis was used to determine hospitals’ X-inefficiency scores relative to their market-level competitors. Regression was used to assess the relationship between X-inefficiency and quality, controlling for organizational and market characteristics. Expenses (total and labor expenditures), case-mix-adjusted admissions, length of stay, and licensed beds defined the X-inefficiency function. The overall National Quality Forum’s safe practice score, health maintenance organization penetration, market share, and teaching status served as independent control variables in the regression. Findings: The National Quality Forum’s safe practice scores are significantly and positively correlated to hospital X-inefficiency levels (ß = .105, p = .05). The analysis of the value proposition had very good explanatory power (adjusted R2 = .414; p = .001; df = 7,265). Contrary to earlier findings, health maintenance organization penetration and being a teaching hospital were positively related to X-inefficiency. Similar with others’ findings, greater market share and for-profit ownership were negatively associated with X-inefficiency. Practice Implications: Measurement of overall hospital quality is improving but can still be made better. Nevertheless, the National Quality Forum’s measure is significantly related to efficiency and could be used to create differential pay-for-performance programs. A market-segmented analytic strategy for studying hospital’s efficiency yields results with a high degree of explanatory power

Relative efficiency measurement of the educational schools from the perspective of data envelopment analysis (DEA) -case study: Educational schools in Saida of Wilaya-Ageria

The aim of this search paper is to shed light on the relative efficiency measurement of the educational schools presented in the sample composed by 33 schools from the perspective of data envelopment analysis (DEA) (Model CRS is oriented input) for the period 2010-2013, where the number of efficient institutions 16 , and 17 inefficient institutions

Data Warehouse (DWH) Efficiency Evaluation Using Fuzzy Data Envelopment Analysis (FDEA)

This paper proposes the macro model and micro model for the efficiency evaluation of data warehouses (DWH), and introduces Fuzzy Data Envelopment Analysis (FDEA) and Data Envelopment Analysis (DEA) to comprehensively assess DWH efficiency. FDEA can determine the efficiencies of data warehouses with multiple input / output variables, and also resolve the problem that standard DEA cannot handle with imprecise input / output data. FDEA results present efficiency from different viewpoints: Best-Worst Scenario and Worst-Best Scenario. The final ranking results between FDEA and DEA are similar on the highest efficiency and the lowest efficiency of data warehouses. Compared with DEA, FDEA can distinguish the efficiency difference for some data warehouses

Social services, human capital, and technical efficiency of smallholders in Burkina Faso:

This study applies regression analysis as well as a non-parametric method to survey data from Burkina Faso to analyze the role of human capital in explaining technical efficiency in smallholder agricultural production. Exploiting the panel nature of the data and explicitly treating human capital inputs as endogenous, a two-stage estimation method is used for the analysis of determinants of data envelopment analysis (DEA) technical efficiency scores in a double-bootstrap procedure. Findings suggest that the impact of human capital on technical efficiency differs strongly by gender. Strong positive returns exist for education of females, whereas male education is associated with higher inefficiency. Body mass index of adult females also positively relates to technical efficiency. At the community level, presence of a clinic, connection to the electrical grid, presence of a secondary school, and year-round accessibility of the community are found to be vital for human capital formation.Human capital, non-parametrics, public services, Smallholders,

Supplier's total cost of ownership evaluation: a data envelopment analysis approach

Supplier Total Cost of Ownership (TCO) is a widely-known approach for determining the overall cost generated by a supplier relationship, but its adoption is still limited. The complex calculations involved - and in particular the activity-based costing procedure for computing the cost of managing the relationship - pose a major obstacle to widespread TCO implementation. The purpose of this work is to formulate a Data Envelopment Analysis application (denoted 'TCO-based DEA') that can act as a proxy for TCO, and to test its ability to approximate the results of TCO with less effort. The study is based on the analysis of two categories of suppliers (74 in total) of a medium-sized Italian mechanical engineering company. The results show that TCO-based DEA is able to significantly approximate the outcomes of TCO, for both the efficiency indexes and rankings of suppliers, whilst requiring substantially less effort to perform the analysis. To our knowledge, this is the first study to develop a DEA-based tool for approximating TCO and to test it in a real-world setting. The research shows significant potential within the supply chain management field. In particular, TCO-based DEA can be used for analysing suppliers' performance, rationalising and reducing the supplier base, assisting the negotiation process

Improving customer equity through value creation and value appropriation

Customer equity is increasingly being considered as a market-based asset that can improve financial performance and market valuation of firms. There has been a trend therefore within organizations to design internal processes which can facilitate maximal achievement of customer equity. From a managerial perspective, it is important to know how such processes come together to influence equity perceptions of the firm\u27s customers. Value theory categorizes processes into two components: value creating and value appropriating. In this dissertation, I evaluate how marketing-related VC and VA processes interact in shaping customer equity of a firm. I develop a framework that identifies several VC and VA organizational processes based on the work of Srivastava and his colleagues (1999) and other relevant extant research. I also propose outcomes to measure effectiveness of VC and VA processes. Using data collected from B2B firms in India, I estimate the efficiency of firms in converting VC and VA inputs into VC and VA outcomes. I call these efficiencies as value creation efficiency (VCE) and value appropriation efficiency (VAE). I then test how VCE and VAE work together to affect CE outcomes. The floodlight analysis of interaction effects between VCE and VAE show that the effect of VC processes on value and relationship equity assessment by customers depends on VA processes being moderately efficient. On the other hand, the effect of VC processes on brand equity assessment by customers depends on the presence of high level of VA efficiency. The overall message is that unless a firm is efficient in transforming VA processes into VA outcomes, it may not gain equity benefits from VC processes

Analysis of the role of innovation and efficiency in coastal destinations affected by tourism seasonality

This research analyses the relationship between efficiency, innovation and seasonality of the Spanish coasts for a five-year period (2015−2019). First of all, the nexus between the level of efficiency and changes in productivity, driven by improvements in innovation and/or efficiency, is determined using Data Envelopment Analysis and the Malmquist Index. Second, this paper proposes a synthetic index to measure seasonality and assess its connection with efficiency and innovation, using a cross efficiency approach to do so. Results show how the intensity of seasonality influences efficiency. In addition, it is observed that innovation can offset possible decreases in efficiency; as such, policies that promote both aspects are needed in the more seasonal destinations