The Efficiency Score of Small Accommodation Businesses in Non-Coastal Rural Areas in Greece

Small accommodation businesses dominate the rural hospitality industry, producing simple or complex tourist products and services in order to be sustainable and competitive. In this paper, a two-stage data envelopment analysis (DEA) model was applied in a representative sample of 151 small accommodation businesses in non-coastal areas in the region of Central Macedonia in Greece. In the first stage, DEA-bootstrapping is applied to estimate point and interval efficiency ratios of accommodation businesses and identify the benchmark accommodations. The double bootstrapping truncated procedure of Simar and Wilson is implemented in the second stage to investigate the role of five business factors in terms of efficiency. The findings suggest that small accommodation businesses, although they are based in areas where tourist resources abound, are inefficient. Moreover, the results of the truncated regression method showed that the business’s size, the operating days, and the variety of activities (simple/complex) affect business’s inefficiency. On the contrary, the business’s age and their engagement in agriculture or not do not affect business’s efficiency. The results are important for rural entrepreneurs and policy makers, and they will also be useful for the adaptation of businesses to increase their efficiency.

Performance measurement of decision making units through interval efficiency with slacks-based measure: an application to tourist hotels in Taipei

Data envelopment analysis (DEA) is widely used to evaluate the performance of a group of homogeneous decision making units (DMUs). Considering the uncertainty, interval DEA has been introduced to fit into more situations. In this paper, an interval efficiency method based on slacks-based measure is proposed to solve the uncertain problems in DEA. Firstly, the maximum and minimum efficiency values of the evaluated DMU are calculated by the furthest and closest distance from the evaluated DMU to the projection points on the Pareto-efficient frontier, respectively. Then, the AHP method is used for the full ranking of DMUs. The paper uses the pairwise comparison relationship between each pair of DMUs to construct the interval multiplicative preference relations (IMPRs) matrix. If the matrix does not meet the consistency condition, a method to obtain consistency IMPRs is introduced. According to the consistency judgment matrix, the full ranking of DMUs can be obtained. Finally, we apply our method to the performance evaluation of 12 tourist hotels in Taipei in 2019.

An Interval Efficiency Measurement in DEA When considering Undesirable Outputs

Data envelopment analysis (DEA) is a popular mathematical tool for analyzing the relative efficiency of homogenous decision-making units (DMUs). However, the existing DEA models cannot tackle the newly confronted applications with imprecise and negative data as well as undesirable outputs simultaneously. Thus, we introduce undesirable outputs into modified slack-based measure (MSBM) model and propose an interval-modified slack-based measure (IMSBM) model, which extends the application of interval DEA (IDEA) in fields that concern with less undesirable outputs. The novelties of the model are that it considers the undesirable outputs while dealing with imprecise and negative data, and it is slack-based. Furthermore, the model with undesirable outputs is proven translation-invariant and unit-invariant. Moreover, a numerical example is provided to illustrate the changes of the lower and upper bounds of the efficiency score after considering the undesirable outputs. The empirical results show that, without considering undesirable outputs, most of the lower bounds of the efficiency scores will be overestimated when the DMUs are weakly efficient and inefficient. The upper bound will also change after considering undesirable outputs when the DMU is inefficient. Finally, an improved degree of preference approach is introduced to rank the DMUs.

An Interval Efficiency Measurement without Sign Restrictions in Data

Mostly, all conventional DEA models assume that input-output data are precise and nonnegative, but in real-life application, this condition is mostly not applicable. Through progressive development in the methodology of DEA, some models separately deal with imprecise and negative data. In this study, the IMSBM model is proposed to evaluate the performance of a set of homogenous DMUs with imprecise and negative input-output data. The IMSBM model is far superior to models with similar capability because it considers the inefficiency caused by both radial and nonradial slacks. The lower and upper bounds of interval efficiency calculated by the IMSBM model reflect the performance of observed DMU in most unfavourable and most favourable situations. Further, it is proved that the IMSBM model is units invariant, monotone, and translation invariant. Moreover, we elaborate both bounds of the interval efficiency are in the range of [0,1]. The degree of preference approach is introduced to rank the DMUs. In addition, we compare the interval efficiency scores calculated by the IMSBM model and the interval SORM model and explain the reason for the difference between the scores. By adjusting the weights of inputs and outputs, it is found that only inefficiency scores fluctuate with slack weights.

THE ISSUES OF TRAIN SCHEDULE FULFILLMENT STABILITY IMPROVEMENT

Objective: At present the majority of railway lines experiences serious difficulties in handling of the increased flow of freight trains with considerable amount of passenger traffic. In view of this there is a necessity to improve the level of train schedule stability by creating certain time slacks in it, which make it possible to eliminate errors. Methods: The methods of simulation, computational theory and construction of a train schedule graph were applied. Results: The method of train routing was developed on the basis of simulation of schedule configuration. The characteristics of schedule configuration and conditions of its creation were presented. The influence of trainhandling capacity efficiency coefficient on the choice of a configured train routing diagram was studied, as well as one of the vital factors, causing degradation of train schedule fulfillment stability – disagreement in train traffic. It was shown that in case of selecting a configuration it was necessary to increase the headway between consecutive trains after a bunch of trains, and if train overtaking is inevitable – to use the time of extra removal. In order to eliminate the consequences of disagreement in train traffic, it was proposed to increase intervals not between all trains, but to compensate the disagreement after passage of a number of trains, the latter should be specified on an individual basis. The assessment of compensating interval efficiency was fulfilled by means of removal coefficient calculation for different conditions on three options. It was concluded that the compensating interval not only reduces disagreement impact, but also improves train-handling capacity. The example of train schedule stability improvement was considered on the basis of applying configurations at “Malaya Vishera – Bologoye” section on down trains within the period of time from 11.30 pm to 7.30 am. Practical importance: Application of configurations makes it possible to achieve higher implementable levels of speed and train-handling capacity, leads to the detection of time slacks and time buffers, which considerably increase train schedule stability and, consequently, the stability of its fulfillment.