Analysis of efficiency and profitability of franchise services

The present study analyses the relative efficiency of franchise services and characterises the best companies, confirming the relationship between efficiency and profit. These companies are from the trade and other services sector , the main group of service-providing companies in the Spanish economy. The methodology calls for first comparing the relative efficiency of franchisers and ownership enterprises. Second, the focus turns to the most efficient franchise services, using a super-efficiency model to rank them. The paper then goes on to cover the analysis of the main characteristics of the best franchise enterprises, the number of own establishments in a franchise business and the profitability of the company. This paper presents arguments as to why companies from the trade and other services sector are included. The main conclusion is that, whilst the number of establishments is irrelevant in achieving greater efficiency, many of the most efficient enterprises have high returns.García Martin, CJ.; Medal Bartual, A.; Peris-Ortiz, M. (2014). Analysis of efficiency and profitability of franchise services. Service Industries Journal. 34(9):796-810. doi:10.1080/02642069.2014.905921S79681034

CONTEXT-DEPENDENT ASSESSMENT OF THE EFFICIENCY OF LITHUANIAN FAMILY FARMS

Kontekstinė duomenų apgaubties analizė leidžia stratifikuoti stebėjimus atsižvelgiant į jų gamybinę aplinką ir efektyvumą. Toks klasifikavimas yra naudingas nustatant realesnius produktyvumo ir efektyvumo didinimo tikslus bei rekomendacijas. Tyrimo tikslas – nustatyti ir kiekybiškai įvertinti efektyvumo lygio skirtumus Lietuvos ūkininkų ūkiuose. Efektyvumo skirtumai vertinti patrauklumo ir progreso rodiklių atžvilgiu. Augalininkystės ūkiai buvo sugrupuoti į devynias stratas (efektyvumo lygmenis), gyvulininkystės ūkiai – į penkias, o mišrūs ūkiai – į šešias. Taigi augalininkystės ūkiai buvo labiausiai heterogeniški efektyvumo atžvilgiu. Mišriuose ūkiuose buvo pastebėta strata, pasižyminti aukšta progreso rodiklio reikšme. Šiai ūkių grupei būtų ypač sudėtinga pasiekti aukštesnį produktyvumo ir efektyvumo lygmenį. Tyrimo rezultatai rodo, kad numatant žemės ūkio paramos priemones, tikslinga atsižvelgti į atskirų ūkininkavimo tipų ir jiems priklausančių ūkių grupių potencialias efektyvumo didinimo galimybes.The context-dependent data envelopment analysis ensures that the observations are stratified with respect to their levels of efficiency. The latter instance of stratification enables one to draw more reasonable recommendations regarding performance improvements. The research aims to identify and quantify the discrepancies in efficiency levels among Lithuanian family farms. The crop farms were grouped into the nine strata associated with different levels of efficiency, the livestock farms were grouped into the five strata, and the mixed farms were grouped into the six strata. Therefore, the crop farms appeared to be the most heterogeneous in terms of efficiency and productivity. The results showed that the mixed and livestock farms were specific with certain strata featuring inflated values of the progress scores. Accordingly, support measures for the mixed and crop farms should take into account the underlying differences in the farm performance

Measuring Residential Energy Efficiency Improvements with DEA

This paper measures energy efficiency improvements of US single-family homes between 1997 and 2001 using a two-stage procedure. In the first stage, an indicator of energy efficiency is derived by means of Data Envelopment Analysis (DEA), and the analogy between the DEA estimator and traditional measures of energy efficiency is demonstrated. The second stage employs a bootstrapped truncated regression technique to decompose the variation in the obtained efficiency estimates into a climatic component and factors attributed to efficiency improvements. Results indicate a small but significant improvement of energy efficiency over the studied time interval, mainly accounted for by fuel oil and natural gas users

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

<p>Abstract</p> <p>Background</p> <p>Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved.</p> <p>Method</p> <p>This paper introduces a new hybrid methodology <it>Expert-based Cooperative Analysis </it>(EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by <it>EbCA-Data Envelopment Analysis (EbCA-DEA)</it>, and 2) Case-mix of schizophrenia based on functional dependency using <it>Clustering Based on Rules (ClBR)</it>. In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases.</p> <p>Results</p> <p>EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here <it>Implicit Knowledg </it>-IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases.</p> <p>Discussion</p> <p>This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.</p

Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds

Development and application of the data envelopment analysis (DEA) method, have been the subject of numerous reviews. In this paper, we consider the papers that apply DEA methods specifically to financial services, or which use financial services data to experiment with a newly introduced DEA model. We examine 620 papers published in journals indexed in the Web of Science database, from 1985 to April 2016. We analyse the sample applying citations network analysis. This paper investigates the DEA method and its applications in financial services. We analyse the diffusion of DEA in three sub-samples: (1) banking groups, (2) money market funds, and (3) insurance groups by identifying the main paths, that is, the main flows of the ideas underlying each area of research. This allows us to highlight the main approaches, models and efficiency types used in each research areas. No unique methodological preference emerges within these areas. Innovations in the DEA methodologies (network models, slacks based models, directional distance models and Nash bargaining game) clearly dominate recent research. For each subsample, we describe the geographical distribution of these studies, and provide some basic statistics related to the most active journals and scholars

Eco-efficiency measurement and material balance principle:an application in power plants Malmquist Luenberger Index

Incorporating Material Balance Principle (MBP) in industrial and agricultural performance measurement systems with pollutant factors has been on the rise in recent years. Many conventional methods of performance measurement have proven incompatible with the material flow conditions. This study will address the issue of eco-efficiency measurement adjusted for pollution, taking into account materials flow conditions and the MBP requirements, in order to provide ‘real’ measures of performance that can serve as guides when making policies. We develop a new approach by integrating slacks-based measure to enhance the Malmquist Luenberger Index by a material balance condition that reflects the conservation of matter. This model is compared with a similar model, which incorporates MBP using the trade-off approach to measure productivity and eco-efficiency trends of power plants. Results reveal similar findings for both models substantiating robustness and applicability of the proposed model in this paper

A classification of DEA models when the internal structure of the Decision Making Units is considered

We classify the contributions of DEA literature assessing Decision Making Units (DMUs) whose internal structure is known. Starting from an elementary framework, we define the main research areas as shared flow, multilevel and network models, depending on the assumptions they are subject to. For each model category, the principal mathematical formulations are introduced along with their main variants, extensions and applications. We also discuss the results of aggregating efficiency measures and of considering DMUs as submitted to a central authority that imposes constraints or targets on them. A common feature among the several models is that the efficiency evaluation of the DMU depends on the efficiency values of its subunits thereby increasing the discrimination power of DEA methodology with respect to the black box approach

Environmentalism in the EU-28 context: the impact of governance quality on environmental energy efficiency

Environmental policies are a significant cornerstone of a developed economy, but the question that arises is whether such policies lead to a sustainable growth path. It is clear that the energy sector plays a pivotal role in environmental policies, and although the current literature has focused on examining the link between energy consumption and economic growth through an abundance of studies, it does not explicitly consider the role of institutional or governance quality variables in the process. Both globalization and democracy are important drivers of sustainability, while environmentalism is essential for the objective of gaining a “better world.” Governance quality is expected to be the key, not only for economic purposes but also for the efficiency of environmental policies. To that end, the analysis in this paper explores the link between governance quality and energy efficiency for the EU-28 countries, spanning the period 1995 to 2014. The findings document that there is a nexus between energy efficiency and income they move together: the most efficient countries are in the group with higher GDP per capita. Furthermore, the results show that governance quality is an important driver of energy efficiency and, hence, of environmental policies.University of Granad

Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions

YesAlthough many modelling and prediction frameworks for corporate bankruptcy and distress have been proposed, the relative performance evaluation of prediction models is criticised due to the assessment exercise using a single measure of one criterion at a time, which leads to reporting conflicting results. Mousavi et al. (Int Rev Financ Anal 42:64–75, 2015) proposed an orientation-free super-efficiency DEA-based framework to overcome this methodological issue. However, within a super-efficiency DEA framework, the reference benchmark changes from one prediction model evaluation to another, which in some contexts might be viewed as “unfair” benchmarking. In this paper, we overcome this issue by proposing a slacks-based context-dependent DEA (SBM-CDEA) framework to evaluate competing distress prediction models. In addition, we propose a hybrid crossbenchmarking- cross-efficiency framework as an alternative methodology for ranking DMUs that are heterogeneous. Furthermore, using data on UK firms listed on London Stock Exchange, we perform a comprehensive comparative analysis of the most popular corporate distress prediction models; namely, statistical models, under both mono criterion and multiple criteria frameworks considering several performance measures. Also, we propose new statistical models using macroeconomic indicators as drivers of distress