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Enterprise Resource Planning (ERP) software which is a knowledge-based design on the interconnective communication of business units and information share, ensures that business processes such as finance, production, purchasing, sales, logistics and human resources, are integrated and gathered under one roof. This integrated system allows the company to make fast and accurate decisions and increases its competitiveness. Therefore, for an enterprise, choosing the suitable ERP software is extremely important. The aim of this study is to present new research on the ERP software selection process by clarifying the uncertainties and find suitable software in a computational way.

ERP selection problem design includes uncertainties on the expert opinions and the criteria values using intuitionistic fuzzy set theory and interval grey-numbers to MACBETH multi criteria decision making method. In this paper, a new interval grey MACBETH method approach is proposed, and the degree of greyness approach is used for clarifying the uncertainties. Using this new approach in which grey numbers are used, it is aimed to observe the changes in the importance of the alternatives. Moreover, the intuitionistic fuzzy set method is applied by considering the importance of expert opinions separately.

The proposed method is based on quantitative decision making derived from qualitative judgments. The results given under uncertain conditions are compared with the results obtained under crisp conditions of the same methods. With the qualitative levels of experts reflected in the decision process, it is clearly seen that ERP software selection problem area has more effective alternative decision solutions to the uncertain environment, and decision makers should not undervalue the unsteadiness of criteria during ERP software selection process.

This study contributes to the relevant literature by (1) utilizing the MACBETH method in the selection of the ERP software by optimization, and (2) validating the importance of expert opinions with uncertainties on a proper ERP software selection procedure. So, the findings of this study can help the decision-makers to evaluate the ERP selection in uncertain conditions.

Reliable operation of natural gas pipeline (NGP) is a critical factor in Iran’s economic development. NGP projects go through different ecosystems and considerably affect the environment. Environmental analysis is an essential step toward sustainable development. Tackling the challenges, this paper aims to develop a framework to systematically assess the environmental impact of NGPs.

This study proposes a comprehensive framework for environmental impact analysis of NGPs using Measuring Attractiveness by a Categorical-Based Evaluation Technique (MACBETH). MACBETH protocol is used to calculate the overall environmental scores of projects.

The results indicate that the impact of implementing NGPs on protected areas is of the highest priority, while the impact on vegetation covers is of least priority for assessing the environmental impact of NGP.

The practicality and validity of the model in the case of three candidate routes for the Polkale-Neizar project in Iran are examined. According to the results, the third alternative is selected based on its non-interference in protected areas and less environmental impacts. The proposed model can be modified and applied to perform environment appraisal of other linear projects such as energy, road and railway networks.

This model addresses a range of environmental impacts of implementing NGPs at two levels, with the second level being non-additive. The novelty of this study translates into considering the qualitative and quantitative features of each evaluation criterion applied to linear projects simultaneously using a multi-criteria value measurement.

Considered the largest investment for most households, buying a house requires careful and transparent analysis by all parties involved in the transaction. The aim of this paper is to propose a methodological framework allowing for the readjustment of trade-offs among risk evaluation criteria, considered of extreme importance in the lending decision process of mortgage loans.

Multiple criteria decision analysis (MCDA) has proved over the years to be effective and versatile in handling compensations among criteria. Measuring attractiveness is applied by a categorical based evaluation technique (MACBETH) to a pre-established structure of credit-scoring criteria for mortgage lending risk evaluation. This pre-established structure is currently used by one of the largest banks in Portugal.

The framework allowed the authors to provide the credit experts who participated in the study with a more informed, transparent and accurate mortgage-lending risk-evaluation system. The sensitivity and robustness analyses carried out also helped in promoting discussion and supporting the readjustments made.

The study shows the usefulness of using the MACBETH approach to assist credit analysts in making better informed decisions, and opens avenues for further research. However, due to the dependence on the participants involved, extrapolations without proper caution are discouraged.

The credit analysts who participated in this study considered the framework more discerning in terms of Basel directives.

The integration of MACBETH and credit-scoring mechanisms holds great potential for risk assessment and decision support. No prior work reporting the application of MACBETH in terms of mortgage-lending risk-evaluation is known.

The purpose of this research is to test the effectiveness of integrating Grasshopper 3D and measuring attractiveness by a categorical based evaluation technique (M-MACBETH) for building energy simulation analysis within a virtual environment. Set of energy retrofitting solutions is evaluated against performance-based criteria (energy consumption, weight and carbon footprint), and considering the preservation of the cultural value of the building, its architectural and spatial configuration.

This research addresses the building energy performance analysis before and after the design of retrofitting solutions in extreme climate environments (2030–2100). The proposed model integrates data obtained from an advanced parametric tool (Grasshopper) and a multi-criteria decision analysis (M-MACBETH) to score different energy retrofitting solutions against energy consumption, weight, carbon footprint and impact on architectural configuration. The proposed model is tested for predicting the performance of a traditional timber-framed dwelling in a historic parish in Lisbon. The performance of distinct solutions is compared in digitally simulated climate conditions (design scenarios) considering different criteria weights.

This study shows the importance of conducting building energy simulation linking physical and digital environments and then, identifying a set of evaluation criteria in the analysed context. Architects, environmental engineers and urban planners should use computational environment in the development design phase to identify design solutions and compare their expected impact on the building configuration and performance-based behaviour.

The unavailability of local weather data (EnergyPlus Weather File (EPW) file), the high time-resource effort, and the number/type of the energy retrofit measures tested in this research limit the scope of this study. In energy simulation procedures, the baseline generally covers a period of thirty, ten or five years. In this research, due to the fact that weather data is unavailable in the format required in the simulation process (.EPW file), the input data in the baseline is the average climatic data from EnergyPlus (2022). Additionally, this workflow is time-consuming due to the low interoperability of the software. Grasshopper requires a high-skilled analyst to obtain accurate results. To calculate the values for the energy consumption, i.e. the values of energy per day of simulation, all the values given per hour are manually summed. The values of weight are obtained by calculating the amount of material required (whose dimensions are provided by Grasshopper), while the amount of carbon footprint is calculated per kg of material. Then this set of data is introduced into M-MACBETH. Another relevant limitation is related to the techniques proposed for retrofitting this case study, all based on wood-fibre boards.

The proposed method for energy simulation and climate change adaptation can be applied to other historic buildings considering different evaluation criteria and context-based priorities.

Context-based adaptation measures of the built environment are necessary for the coming years due to the projected extreme temperature changes following the 2015 Paris Agreement and the 2030 Agenda. Built environments include historical sites that represent irreplaceable cultural legacies and factors of the community's identity to be preserved over time.

This study shows the importance of conducting building energy simulation using physical and digital environments. Computational environment should be used during the development design phase by architects, engineers and urban planners to rank design solutions against a set of performance criteria and compare the expected impact on the building configuration and performance-based behaviour. This study integrates Grasshopper 3D and M-MACBETH.

Industrial companies are continuously looking to improve their business turn-over and choose improvement actions to achieve this objective. Legitimating this choice by only a strategic financial point of view currently has some limits, because additional ones such as quality, delay, resources needs have also to be taken into account. The multicriteria decision aid (MCDA) approaches have been developed to deal with problems such as ranking, sorting or quantification. The purpose of this paper is to describe the operational aspects in MCDA deployment through a case study submitted by the SME Fournier Company.

This paper concerns analytical overall performance models to allow the decision-makers (DMs) to select potential actions to launch regarding given decision criteria. The principles of the main MCDA approaches, outranking and aggregation, are presented. Then representative MCDA methods, ELECTREIII and MACBETH, are successively deployed to a tactical decision problem of business turn-over increase. From the building of their respective preference modelling, decision aid is provided in the form of preference relation or performance function.

A formal framework supplying information to the industrial DMs in order to legitimate the action selection is described. In addition, the DMs feedback highlights the required expertise for the preference modelling.

The article gives a guideline for industrial practitioners to carry out ELECTREIII and MACBETH for their improvement action selection.

SMEs can find an adapted framework for their improvement actions choice dealing with financial and non-financial criteria. It is also enriched by practical considerations concerning the methods deployment for tactical decision problems.

The purpose of this paper is to investigate whether factor sensitivities of margins of bank-issued warrants depend on issuers’ credit risk during the period of economic turmoil between January 2008 and June 2010.

Therefore, first, Fama–MacBeth estimations were applied and it was demonstrate that the sensitivities of margins in terms of time to maturity and moneyness vary substantially over time; the average outcomes are similar to the results of classical pooled estimations.

Then, time-series tests were used and it was found that the steepness of the issuers’ credit default swap (CDS) spread curves correlates negatively with the time-to-maturity sensitivities as well as with the explanatory power of Fama–MacBeth estimations.

These findings indicate that the life-cycle hypothesis is weakened when the issuers’ CDS spread curves become steeper.

Thus, this study offers a new approach to gain insights into the role of issuers’ credit risk on price setting behavior.

Small- and medium-sized enterprises (SMEs) have become increasingly important in national and international markets because they contribute to the development of local and national economies. SMEs often face serious challenges when competing with multinational companies. The purpose of this paper is to develop a method for assessing SMEs’ competitiveness.

Based on a constructivist epistemology, this study makes an integrated use of cognitive mapping and the measuring attractiveness by a categorical-based evaluation technique (MACBETH). To this end, face-to-face sessions were conducted with a panel of entrepreneurs and senior managers who deal with the challenges of maintaining SME competitiveness every day. The proposed assessment system was tested and validated by the panel members.

The methodological processes adopted in this study provide promising results for decision makers seeking to identify the most competitive SMEs. Specifically, the results emphasize, among other points, the importance of innovation and the human dimension to gaining competitive advantages.

The evaluation system developed in this study is extremely versatile and confirms the usefulness of integrating cognitive mapping and MACBETH to facilitate evaluations of SME competitiveness. However, due to its idiosyncratic and process-oriented nature, generalizations need to be done with caution.

The proposed method can be valuable to researchers seeking to develop mechanisms for evaluating SMEs’ entrepreneurial performance and include specialized know-how and sensemaking in organizational decision-making processes.

The integrated use of cognitive maps and MACBETH contributes to a better understanding of how to assess SMEs’ competitiveness. No prior work reporting the use of this dual methodology in this study context has been found.

We examine the incremental cross-sectional role of several common risk factors related to size, book-to-market, and momentum in size-and-momentum-sorted portfolios. Unlike the existing literature, which focuses on the conditional mean specification only, we evaluate the common risk factors’ incremental explanatory power in the cross-sectional characterization of both average return and conditional volatility. We also investigate the role of ex-ante market risk in the cross-section. The empirical results demonstrate that the size-and-momentum-based risk factors explain a significant portion of the cross-sectional average returns and cross-sectional conditional volatility of the benchmark equity portfolios. We find that the Fama–French (1993) factors and the ex-ante market risk are priced in the cross-sectional conditional volatility. We conclude that the size-and-momentum-based factors provide a source of risk that is independent of the Fama–French factors as well as ex-post and ex-ante market risk. Our results bolster the risk-based explanation of the size and momentum effects.

The prosthodontics sector is facing major challenges because of scientific and technological advances that imply a clearer definition of lines of action and decision making processes. Measuring quality of service in this sector is a complex decision problem since the perceptions of three main players need to be considered: patients, dentists and dental technicians. This study sought to develop an artificial-intelligence-based (AI-based) method for assessing service quality in the dental prosthesis sector.

Using strategic options development and analysis (SODA), which is grounded on cognitive mapping, and the measuring attractiveness by a categorical based evaluation technique (MACBETH), a constructivist decision support system was designed to facilitate the assessment of service quality in the dental prosthesis sector. The system was tested, and the results were validated both by the members of an expert panel and by the vice-president of the Portuguese association of dental prosthesis technicians.

The methodological process developed in this study is extremely versatile and its practical application facilitated the development of an empirically robust evaluation model in this study context. Specifically, the profile analyses carried out in actual clinics allowed the cases in which improvements are needed to be identified.

Although already applied in the fields of AI and decision making, no prior work reporting the use of SODA and MACBETH for assessing service quality in the prosthodontics sector has been found.

Precise colour matching, a regular requirement for architects, major retailers, designers and clothes buyers, is now much more convenient with Macbeth's portable viewing booth. Easy to carry and quick to erect, the Judge II can be used for matching colours, evaluating colour quality and appraising colour uniformity in almost any environment. The unit's extremely rugged construction also allows it to double as a fixed booth.