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Describes non‐parametric methods applied to comparisons of three or more sample groups.Illustrates non‐parametric ANOVA applied to a randomized block design for a consumer sensory experiment.

Libraries constitute a highly developing area as they always enrich their offered services in order to satisfy users' expectations. One of the most important factors in customization strategies and improvement of individual services must be user preferences. However, customization requires an in‐depth analysis of user preferences and an evaluation of future behavior. The main objective of this paper is to present a framework for analyzing changes of user preferences in a library.

The paper presents detailed results of two independent user satisfaction surveys conducted in an interval of five years in the Library of the Technical University of Crete and analyzes them using a proposed framework. However, the framework can be applied in every modern library. The analyses are based on non‐parametric statistical techniques and a multicriteria satisfaction analysis method, which is a multicriteria preference disaggregation approach.

Overall, user judgments for both surveys show that 50‐70 percent of users are “very satisfied” or “satisfied”. The percentage of “satisfied” users increased from 2005 to 2010 (almost 18 percent) and “very satisfied” remained almost the same.

Results are mainly focused on the evaluation of potential trends of user preferences. Furthermore, results of a benchmarking analysis are also presented, based on the evolution of satisfaction levels for the quality characteristics of the offered services.

The goal of the presented study and proposed framework and methodology is to help library decision makers track changes to user preferences and improve the provided services according to those preferences.

The purpose of this work is twofold: on the one hand, recent methodologies will be used to estimate efficiency and productivity in Spain's non‐specialized retail sector for the period of 1997‐2007. In particular, the order‐m approach proposed by Cazals et al., which is based on the concept of expected minimum input function. On the other hand, the results obtained applying the methods mentioned in the Spanish retail sector can contribute to opening up a new field of analysis since the results may be compared by means of the methodologies proposed as well as those which already exist in the literature.

The paper used data envelopment analysis stochastic (order‐m) and bootstrapping Malmquist index to measure productivity and efficiency in 12 sectors in Spanish retail trade 1997‐2007.

In order to illustrate the methodology proposed in this paper different phases involved; first, we have estimated the efficiency in 12 sectors of the retail sector four digits NACE, we found high levels of inefficiency in most of the sectors analyzed over the period of analysis. Next, we will deepen and simplify the analysis by concentrating on food‐predominant sectors in non‐specialised shops (5211). The evolution of the efficiency of firms belonging to this sector decreases over the period of analysis. Analyzing the relationship between firms and size, the results obtained in this work shows that the firm's size have a positive influence on efficiency that suggest that the management may have incentives to grow in order to improve their efficiency levels. Our second contribution has to do with the use of bootstrapping Malmquist productivity indices. Productivity decreased at an average rate of −4.1 percent over the entire period of 1997‐2007. On average, this deterioration was due to efficiency change −6.1 percent. Technical progress is increased at an average rate of 2.1 percent. All rates at global level are statistically significant at 95 percent.

The main contribution of this paper is to provide an efficiency analysis using a non‐parametric approach with a robust estimator that has been suggested recently by Cazals et al. This methodology is that the first time that is applied in the analysis of retail sector. In addition, we analyze productivity growth using bootstrapping Malmquist indices. This methodology allows for a more careful analysis of what happens at firm level. Differences in conclusions between the original estimates and the bootstrap results are more evident when we scrutinize the sample firms and individual levels.

Internet service providers (ISPs) constitute a highly competitive market, while the unstable market conditions directly affect customer preferences and make ISPs to develop a “mass customization” strategy, individualizing services and approaching every customer in an individual way. However, customization requires an in‐depth analysis of current customer preferences and an evaluation of future behavior. The main objective of the paper is to present a framework for analyzing changes of customer preferences.

The paper presents detailed results of independent customer satisfaction surveys conducted in different time periods in the Greek ISP market. The analyses are based on non‐parametric statistical techniques and the multicriteria satisfaction analysis method, which is a multicriteria preference disaggregation approach.

Results are mainly focused on the evaluation of potential trends of e‐customer preferences. Furthermore, results of a benchmarking analysis are also presented, based on the evolution of satisfaction levels for the quality characteristics of the provided services.

Future research in the context of the presented study may be focused on satisfaction benchmarking analysis, given the rapid changes of the market conditions. An extended satisfaction survey will give the ability to analyze customer preferences in comparison with the main ISP competitors.

The presented study may help organizations in highly competitive markets dominated by rapid technological progresses to track short‐term changes of customer preferences.

The analyses presented are based on the combination of multicriteria analysis and non‐parametric statistics. The main advantage of these methods is that they respect the qualitative (ordinal) form of collected survey data.

Though many studies in the past dealt with the survival and growth of enterprises both in the local- and export-markets, less attention was given to the analysis of the duration of enterprises entry into the export-markets. The aim of this paper is, therefore, to analyze the duration of Ethiopian enterprises entry into the export-markets.

This paper used data collected from 848 enterprises through a cross-sectional survey method conducted by the World Bank in 2015. In order to estimate the average duration – the time that enterprises need to wait before entering into the export-markets and the associated factors – the authors used the mixture of non-parametric (Kaplan-Meier) and parametric (Weibull) models.

The non-parametric results show that enterprises are required to wait for an average of about eight years before entering into the export-markets after their establishment. In addition, foreign-owned enterprises were found to be faster in entering into the export-markets than their domestically owned counterparts. The parametric results revealed that enterprises’ product innovation, enterprises’ size and age, and custom and trade regulations are factors that curtail the durations of enterprises entry into the export-markets. On the other hand, enterprises’ operational costs, the size of enterprises’ locality, and enterprises’ location are factors that slow the durations of enterprises’ entry into the export-markets.

This study is the first to offer pioneering evidences on the duration (time in years) that Ethiopian enterprises need to wait before entering into the export-markets and the factors that affect the length of their waiting time.

It is well known that public infrastructure, particularly the transportation infrastructure sector, is notorious for low efficiency, spending waste and corruption. Achieving the efficiency of public infrastructure investment is a crucial element to improve the current deteriorating condition of American transportation infrastructure system. The paper aims to discuss these issues.

This research utilizes an input-oriented, variable return to scale non-parametric data envelopment analysis to estimate the relative cost efficiency of highway infrastructure investment among the 48 American continental states from 1995 to 2009.

The empirical results reveal that there is a large efficiency variation among state highway infrastructure systems.

In addition, state governments on average reach 95.8 percent of the efficiency of their best practice peers in terms of providing quality highway infrastructure outcomes.

Foreclosure risk is a key concern to lenders of real estate mortgages. Using auction data, this study provides the first analysis of mortgage foreclosure in Singapore by examining how macro‐economic variables affect the probability of foreclosure. The foreclosure rate for properties is found to be increasing in the first five years of purchase and decreases as the holding period lengthens. The likelihood of foreclosure increases with unemployment rate, mortgage rate and expenditure and decreases with equity, dividend yield and lending volume at fourth and twentieth quarters lag. Further analysis shows considerable differences between residential and non‐residential properties. However, when the analysis on non‐residential properties is further separated into office, retail and industrial sub‐sectors, the results are relatively similar among the three sub‐sectors. This implies that banks and financial institutions should apply different underwriting standards for residential properties, mainly for owner‐occupation and non‐residential properties for the purpose of businesses and rental income.

The purpose of this paper is to study the production and efficiency of rice growers in drought prone areas with special attention given to economic and financial factors.

The authors use a parametric stochastic frontier approach and a non-parametric data envelopment analysis.

The study found that financial and liquidity constraints negatively influence production efficiency while off-farm work positively influences efficiency in drought prone areas.

Many biotic and abiotic factors affect the production efficiency of rice growers. Among abiotic stress, drought is the strongest constraint affecting nearly one third of the total rice area in Asia and causing significant economic losses. Farmers’ economic conditions and financial constraints further exacerbate the situation. However, very few studies have analyzed the efficiency in drought prone areas and the influence of economic and financial factors. This study contributes to in this regard by augmenting economic and financial factors in the efficiency estimation of drought prone areas using parametric and non-parametric approach.

The comparative method of valuation is based on valuers interpreting prices agreed in the open market to arrive at an opinion of value. This requires the consideration of a diverse range of variables and an assessment of their relative impact. Behavioural analysis using an independent sample of buyers and valuers operative in the Belfast residential market indicates that there are statistically significant differences between the two sample groups in the scoring and ranking of variables. In particular valuers are shown to place a greater emphasis on environmental or neighbourhood effects. Discusses the outcome of this empirically‐based research and analyses whether differences in the treatment of variables between the valuer and buyer samples are reflected in different price and value distributions. The results indicate that valuation accuracy to within 5 per cent of transaction price is not upheld; rather it is argued that a 10 per cent threshold has greater credibility.

This paper aims to investigate the efficiency level of Gulf Cooperation Council (GCC) banks on technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE). Both PTE and SE represent the potential factors that influence the efficiency of the GCC banks. In total, 43 GCC banks were observed in this study over the period from 2007 until 2011.

The Data Envelopment Analysis, a non-parametric method using variable returns to scale under Banker, Charnes and Cooper model, was used with assets and deposit (as input) and loan and income (as output).

On average, the results show that many GCC banks are operating within an optimal scale of efficiency. Nevertheless, the results also show managerial inefficiency in the use of resources. Furthermore, the results indicate that, while the larger banks (the 22 largest) tend to operate at constant returns to scale (CRS) or decreasing returns to scale, the smaller banks (the 21 smallest) are susceptible to operate at either CRS or increasing returns to scale.

Because of the chosen research method, the results may lack generalisation. Therefore, researchers are encouraged to test the propositions further. An additional implication of the results is that it was able to identify some banks that may become potential targets for outside acquisition.

The findings should be useful to banks in the GCC in increasing their efficiencies and recognizing those with a potential for outside acquisition.

The findings are valuable because they will facilitate the maintenance of efficient banks in the GCC. This is necessary to enable the countries to maintain a healthy and sustainable economy.