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The purpose of this paper is to report a research on application of ORESTE (Organization, Rangement Et Synthese De Donnees Relationnelles, when translated into English means organization, storage and summarizing data relational) for agile concept selection.

The concept selection problem has been formulated as a multi-criteria decision-making (MCDM) problem to select the best concept design of the rotary switch component. ORESTE has been used as solution methodology. The selected concept design alternatives were subjected to implementation.

As ORESTE is a preferential outranking method, it uses ordinal data, enabling decision makers in situations where practically sufficient data are not available. This paper uses ORESTE for agile concept selection where gathering sufficient data is difficult. Also, the results generated by ORESTE have been compared with technique for order performance by similarity to an ideal solution.

In the present study, ORESTE has been applied for concept selection of rotary switch component. In future, more number of studies need to be conducted to select more concept design alternatives where getting prior information is difficult or consumes more time to ensure practical effectiveness of ORESTE.

The application of ORESTE for concept design selection enabled the practitioners to select the best concept with ordinal data and also enabled scope for indifferentiability and incomparableness of any two alternatives in the final outranking.

Formulation of MCDM problem for agile concept selection and solution generation using ORESTE is the original contribution of the authors.

The purpose of this paper is to analyse the long-term nature of the interrelationship between interest rate and exchange rate.

By employing Mexican data, the authors estimate a non-linear autoregressive distributed lags (NARDL) model to investigate the nature of the changes and the interaction between interest rate and exchange rate in response to monetary authorities’ actions.

The results show that, contrary to simplistic predictions, the real exchange rate causes the real interest rate in an asymmetric way. The bounds testing approach of the NARDL models suggests the presence of co-integration among the variables and the exchange rate variations appear to have significant long-run effects on the interest rate. Most importantly, these effects are asymmetric and positive variations in the exchange rate have a lower impact on the interest rate. It is also interesting to report that the reverse is not true: the interest rate in the long-run exerts no statistical significant impact on the exchange rate.

The asymmetric long-term relationship between real exchange rate and real interest rate is evidence of why monetary authorities are reluctant to free float exchange rate. In Mexico, as in most developing countries, monetary policy strongly responds to exchange rate movements because these have relevant effects on commercial trade. Moreover, in dollarized economies these effects are stronger because of pass-through impacts to inflation, income distribution and balance-sheet equilibrium (the well-known “original sin”).

Under inflation targeting and flexible exchange rate regime, despite central banks pursue the control of short-term interest rate, in the long-run one could observe that it is the exchange rate that influences the interest rate, and that this reverse causality is stronger in emerging economies. This paper contributes by analysing the asymmetric relationship between the variables.

The idea of this study is to provide a solid Financial Condition Index (FCI) that allows the monetary transmission policy to be monitored in a country which in recent decades has suffered from major financial and monetary crises.

The authors construct three FCIs for Mexico to analyse the role of financial asset prices in formulating monetary policy under an inflation-targeting regime. Using monthly data from 1995 to 2017, the authors estimate FCIs with two different methodologies and build the index by taking into account the mechanism of transmission of monetary policy and incorporating the most relevant financial variables.

This study’s results show that, likewise for developing countries as Mexico, an FCI could be a useful tool for managing monetary policy in reducing macroeconomic fluctuations.

Apart from building a predictor of possible financial stress, the authors construct an FCI for a central bank that pursues inflation targeting and to analyse the role of financial asset prices in formulating monetary policy.

1. We construct three FCIs for Mexico to analyse the role of financial asset prices in formulating monetary policy under an inflation-targeting regime.

2. The FCIs are based on (1) a vector autoregression model (VAR); (2) an autoregressive distributed lag model (ARDL) and (3) a factor-augmented vector autoregression model (FAVAR).

3. FCI could become a new target for monetary policy within a hybrid inflation-targeting framework.

4. FCI could be a good tool for managing monetary policy in developing countries with a low-inflation environment.

We construct three FCIs for Mexico to analyse the role of financial asset prices in formulating monetary policy under an inflation-targeting regime.

The FCIs are based on (1) a vector autoregression model (VAR); (2) an autoregressive distributed lag model (ARDL) and (3) a factor-augmented vector autoregression model (FAVAR).

FCI could become a new target for monetary policy within a hybrid inflation-targeting framework.

FCI could be a good tool for managing monetary policy in developing countries with a low-inflation environment.

The purpose of this paper is to investigate the relationship between the leadership style of a chief audit executive (CAE) and the perceived effectiveness of the internal auditing (IA) function that he/she leads. Perceived IA effectiveness is based on identified attributes in the literature influencing IA effectiveness. The aim of this paper is thus to expand the IA effectiveness debate by adding individual differences in CAEs’ leadership styles as a research focus.

A quantitative approach is followed. A survey was conducted on a sample of 58 IA students enrolled in a master’s degree programme at a South African university; all students hold senior positions in IA.

The study confirms that the CAE leadership style significantly influences the identified attributes of perceived IA effectiveness. It further shows that the traditional conceptualisation of leadership (as transformational, transactional and/or laissez-faire) might not be appropriate for or compatible with leaders of professional teams in a regulated environment.

Practically, the study identifies and explores attributes influencing IA effectiveness that are within the purview of the CAE’s leadership style and within his/her ability to influence. This information could (re)direct leadership development training programmes presented in industry and by the Institute of Internal Auditors (IIA), and at organisational level, it could inform appointment and retention and succession practices for heads of and senior management in IA.

CAEs are cautioned about the limitations imposed by laissez-faire leadership on IA effectiveness. They should strive to become both transformative and transactional leaders as it has a significant influence on the effectiveness of their IA functions, and by being more effective, they can demonstrate the value proposition of IA. Organisations need to create the environment in which CAEs can act as transformational and transactional leaders. The IIA, as the pre-eminent professional body, could become involved in developing leadership skills of its members. The IIA could provide guidance on leadership styles for CAEs and could also offer formal training initiatives to internal auditors on skills needed to lead IA teams.

This paper may open a new research area in IA effectiveness by focussing on the role and leadership qualities of the CAE.

To develop a multi‐attribute decision making model for evaluating and selecting among logistic information technologies.

First a multi‐attribute decision making model for logistic information technology evaluation and selection consisting of 4 main and 11 sub criteria is constructed, then a hierarchical fuzzy TOPSIS method is developed to solve the complex selection problem with vague and linguistic data. Sensitivity analysis is presented.

Reviews the literature and provides a structured hierarchical model for logistic information technology evaluation and selection based on the premise that the logistic information technology evaluation and selection problem can be viewed as a product of tangible benefits, intangible benefits, policy issues and resources. Defines tangible benefits as cost savings, increased revenue, and return on investment; intangible benefits as customer satisfaction, quality of information, multiple uses of information, and setting tone for future business; policy issues as risk and necessity level; resources as costs and completion time. Presents a methodology that is developed for the complex, uncertain and vague characteristics of the problem.

Comparisons with other multi‐attribute decision making techniques such as AHP, ELECTRE, PROMETHEE and ORESTE under fuzzy conditions can be done for further research.

This article is a very useful source of information both for logistic managers and stakeholders in making decisions about logistic information technology investments.

This paper addresses the logistic information technology evaluation and selection criteria for practitioners and proposes a new multi‐attribute decision making methodology, hierarchical fuzzy TOPSIS, for the problem.

The Hispanic American Scholastics look at the price doctrine from a triple point of view: as an economic philosophy, as an instrument for regulating the market, and as an analytic basis[l].

The relationships between tourist resorts and transnational crime are rarely analyzed systematically. This paper begins to fill this gap by examining how organized crime groups and individuals linked to them can take advantage of tourist resorts to commit crimes.

To propose novel predictor‐corrector time‐integration algorithms for pseudo‐dynamic testing.

The novel predictor‐corrector time‐integration algorithms are based on both the implicit and the explicit version of the generalized‐α method. In the non‐linear unforced case second‐order accuracy, stability in energy, energy decay in the high‐frequency range as well as asymptotic annihilation are distinctive properties of the generalized‐α scheme; while in the non‐linear forced case they are the limited error near the resonance in terms of frequency location and intensity of the resonant peak. The implicit generalized‐α algorithm has been implemented in a predictor‐one corrector form giving rise to the implicit IPC‐ρ_∞ method, able to avoid iterative corrections which are expensive from an experimental standpoint and load oscillations of numerical origin. Moreover, the scheme embodies a secant stiffness formula able to approximate closely the actual stiffness of a structure. Also an explicit algorithm has been implemented, the EPC‐ρ_b method, endowed with user‐controlled dissipation properties. The resulting schemes have been tested experimentally both on a two‐ and on a six‐degrees‐of‐freedom system, exploiting substructuring techniques.

The analytical findings and the tests have indicated that the proposed numerical strategies enhance the performance of the pseudo‐dynamic test (PDT) method even in an environment characterized by considerable experimental errors. Moreover, the schemes have been tested numerically on strongly non‐linear multiple‐degrees‐of‐freedom systems reproduced with the Bouc‐Wen hysteretic model, showing that the proposed algorithms reap the benefits of the parent generalized‐α methods.

Further developments envisaged for this study are the application of the IPC‐ρ_∞ method and of EPC‐ρ_b scheme to partitioned procedures for high‐speed pseudo‐dynamic testing with substructuring.

The implicit IPC‐ρ_∞ and the explicit EPC‐ρ_b methods allow a user to have defined dissipation which reduces the effects of experimental error in the PDT without needing onerous iterations.

The paper proposes novel time‐integration algorithms for pseudo‐dynamic testing. Thanks to a predictor‐corrector form of the generalized‐α method, the proposed schemes maintain a high computational efficiency and accuracy.

The purpose of this paper is to propose a practical method of performing maintenance in the offshore industry where engineers have to manage problems such as the high cost of operations, assuring an high availability of the plant, safety on board and environmental protection. Indeed an efficient maintenance method it is necessary in order to offer methods and criteria to select the rights maintenance strategies keeping in to account the environmental, safety and production constrains.

The paper provides an overview of reliability centered maintenance (RCM) and reliability, availability, maintainability methodologies and an integration of the two methodologies in a particular case study in the oil and gas sector.

This paper suggests an improvement of the well-established RCM methodology applicable to industries with high priority level. It is proposed an integration between a reliability analysis and an availability analysis and an application on the offshore oil and gas industry.

The methodology provides an excellent tool that can be utilized in industries, where safety, regulations and the availability of the plant play a fundamental role.

The proposed methodology provides a practical method for selecting the best maintenance strategy considering the equipment redundancy and sparing, the asset’s performance over long time scales, and the system uptime, downtime and slowdowns.

The objective of this paper is to present the employment of the new hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach to evaluate the most suitable business process outsourcing (BPO) decision.

The paper explains the importance of selection criteria for evaluation of BPO. It then describes briefly the fuzzy hierarchical TOPSIS methodology. There then follows a discussion of the application of the fuzzy hierarchical TOPSIS with some sensitivity analysis to the BPO evaluation problem. Finally, some concluding remarks and perspectives are offered.

Use of the hierarchical fuzzy TOPSIS methodology offers a number of benefits. It is a more systematic method than the other fuzzy multi‐criteria decision‐making (FMCDM) methods and it is more capable of capturing a human's appraisal of ambiguity when complex multi‐criteria decision‐making problems are considered. The hierarchical fuzzy TOPSIS is superior to the other FMCDM methods, such as fuzzy analytic hierarchy process (FAHP) and classical fuzzy TOPSIS methods, since the hierarchical structure without making pairwise comparisons among criteria, sub‐criteria, and alternatives is considered. Hierarchical fuzzy TOPSIS is an excellent tool to handle qualitative assessments about BPO evaluation problems, and its calculations are faster than FAHP. Also, hierarchical fuzzy TOPSIS makes it possible to take into account the hierarchical structure in the evaluation model. However, there are drawbacks. The classical fuzzy TOPSIS is a highly complex methodology and requires more numerical calculations in assessing the ranking order of the alternatives than the hierarchical fuzzy TOPSIS methodology and hence it increases the effort, thus limiting its applicability to real world problems.

The proposed model will be very useful to managers in the manufacturing sector, as this method makes decision making easier, systematic, efficient and effective.