Performance analysis in the presence of bounded, discrete and flexible measures_

In conventional data envelopment analysis (DEA) models, the relative efficiency of decision making units (DMUs) is evaluated while all measures with certain input and/or output status are considered as continuous data without upper and/or lower bounds. However, there are occasions in real-world applications that the efficiency of firms must be assessed while bounded elements, discrete values, and flexible measures are present. For this purpose, the current study proposes DEA-based approaches to estimate the relative efficiency of DMUs where bounded factors, integer values, and flexible measures exist. To illustrate it, radial models based on two aspects, individual and aggregate, are introduced to measure the performance of entities and to handle the status of the flexible measure such that there are bounded components and discrete data. Applications of approaches proposed in the areas of quality management, highway maintenance patrols, and university performance measurement are given to clarify the issue and to show their practicability. It was found that the introduced procedure can determine practical projection points for bounded measures and integer values (from the individual DMU viewpoint) and can classify flexible measures along with evaluation of DMUs relative efficiency.

Prediction of pork meat prices by selected methods as an element supporting the decision-making process

Forecasts of economic processes can be determined using various methods, and each of them has its own characteristics and is based on specific assumptions. In case of agriculture, forecasting is an essential element of efficient management of the entire farming process. The pork sector is one of the main agricultural sectors in the world. Pork consumption and supply are the highest among all types of meat, and Poland belongs to the group of large producers. The article analyses the price formation of class E pork, expressed in Euro per 100 kg of carcass, recorded from May 2004 to December 2019. The data comes from the Agri-food data portal. A creeping trend model with segments of linear trends of various lengths and the methodology of building ARIMA models are used to forecast these prices. The accuracy of forecasts is verified by forecasting ex post and ex ante errors, graphical analysis, and backcasting analysis. The study shows that both methods can be used in the prediction of pork prices.

Pattanaik’s axioms and existence of preferred with probability at least half winners

In this paper we show that three conditions due to Pattanaik, when satisfied by a given profile of state-dependent preferences (linear orders) on a given and fixed set of alternatives and a probability distribution with which the various states of nature occur, are individually sufficient, for the non-emptiness of the set of alternative(s) which are individually preferred to all alternatives other than itself with probability at least half. Prior to this, we show that since each axiom individually implies Sen-Coherence, then, as a consequence of a result obtained earlier, each axiom along with asymmetry of the ‘preferred with at probability at least half” relation implies the transitivity of the relation. All the sufficient conditions discussed here are required to be applicable at least to all those otherwise relevant events that have positive probability. This observation also applies to a sufficient condition for the non-emptiness of the set of alternative(s) which are individually preferred to all alternatives other than itself with probability at least half, called Generalised Sen Coherence introduced and discussed in earlier research.

Forecasting the Confidence Interval of Efficiency in Fuzzy DEA

Data Envelopment Analysis (DEA) is a well-known method that based on inputs and outputs calculates the efficiency of decision-making units (DMUs). Comparing the efficiency and ranking of DMUs in different time periods lets the decision makers to prevent any loss in the productivity of units and improve the production planning. Despite the merits of DEA models, they are not able to forecast the efficiency of future time periods with known input/output records of the DMUs. With this end in view, this study aims at proposing a forecasting algorithm with a 95% confidence interval to generate fuzzy data sets for future time periods. Moreover, managers’ opinions are inserted in the proposed forecasting model. Equipped with the forecasted data sets and with respect to the data sets from previous periods, this model can rightly forecast the efficiency of the future time periods. The proposed procedure also employs the simple geometric mean to discriminate between efficient units. Examples from a real case including 20 automobile firms show the applicability of the proposed algorithm.

Computing power indices for weighted voting games via dynamic programming

We study the efficient computation of power indices for weighted voting games using the paradigm of dynamic programming. We survey the state-of-the-art algorithms for computing the Banzhaf and Shapley-Shubik indices and point out how these approaches carry over to related power indices. Within a unified framework, we present new efficient algorithms for the Public Good index and a recently proposed power index based on minimal winning coalitions of smallest size, as well as a very first method for computing Johnston indices for weighted voting games efficiently. We introduce a software package providing fast C++ implementations of all the power indices mentioned in this article, discuss computing times, as well as storage requirements.

Inspecting debt servicing mechanism in Nigeria using ARMAX model of the Koyck-kind

The burden of external debt affects the wellbeing of an economy (or a country) by making the economy vulnerable to external shocks and crowding out investment. When dealing with debt management in indebted poor countries like Nigeria, the rational approach is to allocate a portion of export earnings for debt service payments. Along this line, there is a need to identify the link between debt servicing and export earnings. Hence, the current and long-run effects of export earnings on debt service payments is modelled as a single-input-single-output discrete-time dynamical system within the framework of Autoregressive Moving Average Explanatory Input model of the Koyck-kind (KARMAX). The KARMAX model is identified for Nigeria, using data from the World Bank database from 1970 to 2018 based on the maximum likelihood (ML) method, and the obtained results are compared to the prediction error and the instrumental variable methods. From a theoretical perspective, the KARMAX specification identified by the ML method is more ideal and inspiring. By doing so, this article contributes to the literature on the econometrics of public debt management.

Human factor aspects in information security management in the traditional IT and cloud computing models

This paper attempts to classify the main areas of threats occurring in enterprises in the information management processes. Particular attention was attracted to the effect of the human factor which is present in virtually every area of information security management. The author specifies the threats due to the IT techniques and technologies used and the models of information systems present in business entities. The empirical part of the paper presents and describes the research conducted by the author on information security in business organisations using the traditional IT model and the cloud computing model. The results obtained for both IT models are compared.

Measurement of Control Power in Corporate Networks

This paper discusses some game-theoretical methods for measuring indirect control in complex corporate shareholding networks. The methods use power indices in order to estimate the direct and indirect control in shareholding structures. Some of these methods only estimate the control power of investors (firms without shareholdings), and only a few measure the control power of all firms involved in shareholding networks (which means investors and stock companies). None of them take measuring the importance of mutual connections (edges in the networks) into consideration; thus we focus in particular on an extension of these methods in this paper in order to measure both the control-power of the firms involved in complex shareholding structures (represented by nodes in networks), and the importance (power) of linkages between the firms as elements of a whole corporate shareholding network. More precisely, we apply our approaches to a theoretical example of a corporate network. Moreover, we continue the considerations started in Mercik and Stach (Transactions on Computational Collective Intelligence XXXI, LNCS 11290: 64–79, 2018) about reasonable properties for indirect control measurement. Some ideas of new properties are proposed. The paper also provides a brief review of the literature concerning the topic.

Internet of Things in the accounting field. Benefits and challenges

The main objective of this paper is to identify the benefits and challenges of the Internet of Things (IoT) application in the accounting field of organisations. The study adopts a questionnaire and an interview technique in a company from the road transport sector. The questionnaire research sample includes 151 accounting practitioners and students. Data are collected through the use of an online survey. A principal axis factor analysis with the promax rotation is conducted to assess the underlying structure for the items of the questionnaire. The research outcomes indicate that, in the opinion of accountants and students, the IoT adoption enables the organisation to perform enhanced reporting analysis based on large amount of data gained through sensors (mean=3.98), access to data thorough cloud computing (3.97), and accounting process automation (3.95). From the point of view of managers, the most important benefit is the increase in employee productivity and asset management. The respondents indicate the following aspects as challenges: creation of infrastructure for the adoption a new technology, which accounted for 40.22% of the variance, and cyber security, loss of privacy (7.23% of the explained variance). The findings reveal benefits and challenges for the IoT adoption and could support managers in deploying a new technology in their organisations. The research limitation concerns the fact that this study focuses on respondents from Poland.

Modelling customers’ impatience with discouraged arrival and retention of reneging

This paper presents stochastic modelling of a single server, finite buffer Markovian queuing system with discouraged arrivals, balking, reneging, and retention of reneged customers. Markov process is used to derive the steady-state solution of the model. Closed form expressions using probability generating functions (PGFs) are derived and presented for both classical and novel performance measures. In addition, a sensitivity analysis is carried out to study the effect of the system parameters on performance measures. A numerical problem is also presented to demonstrate the derived results and some design aspects.