Socio-Economic Planning Sciences Creating technical criteria for the hierarchization of public works: Case study in Paraná state, Brazil

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Socio-Economic Planning Sciences 90 (2023) 101748

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Creating technical criteria for the hierarchization of public works: Case ´ state, Brazil study in Parana Alexandre Arns Steiner a, b, David Gabriel de Barros Franco c, *, Elpídio Oscar Benitez Nara a, Maria Teresinha Arns Steiner a a b c

Graduate Program in Industrial Engineering and Systems (PPGEPS), Pontifical Catholic University of Paran´ a (PUCPR), Curitiba, PR, Brazil Paran´ a State Court of Justice (TJPR), Curitiba, PR, Brazil Graduate Program in Digital Agroenergy (PPGADIGITAL), Federal University of Tocantins (UFT), Palmas, TO, Brazil

A R T I C L E I N F O

A B S T R A C T

Keywords: Public administration Multiple-criteria decision analysis Fuzzy-delphi method Panel of experts Sustainable hiring

Public works in general play an important role because of their expressive value and considerable social rele­ vance. In this respect, it is necessary to establish criteria/indicators for defining the hierarchy of works that must be conducted by a public entity, mainly for works considered ordinary, that is, those that do not stand out from a set of alternatives by degree of emergency or importance. Specifically, the hierarchization of engineering works to be carried out by the Public Administration in Brazil usually adopts the political approach to decision making without the application of rational technical criteria. Therefore, the aim of this article is to present a method­ ology to define the hierarchy of engineering works with the judiciary branch of power through the creation of technical criteria/indicators, followed by the application of the Fuzzy-Delphi technique to define the indices/ weights that comprise the indicators. The technical criteria were created based on Resolution 114 of the country’s National Council of Justice (Conselho Nacional de Justiça; CNJ), whose weights were obtained through the aforementioned method, which was applied to a panel of experts, in two stages, with the adoption of triangular fuzzy numbers. The results, which were clear and objective, provide the General Hierarchization Index (GHI), with the ordering/ranking of the works included in the process. The methodology was validated in a case study applied to 162 alternatives (districts), containing 192 buildings of the Court of Justice of Paran´ a State (Tribunal de Justiça do Paran´ a; TJPR), proving to be an important tool to support decision making. The opti­ mization of resources through the determination of priorities converges to the sustainable hiring applied to public contracts. Institutions of the other Powers of the Republic could and should also be encouraged by public authorities to conduct technical studies similar to the proposal presented here, always clarifying the need for a clear and objective definition of the criteria and weights to be applied in the development of solutions for multicriteria decision making.

1. Introduction According to the Constitution of the Federative Republic of Brazil, the actions of direct and indirect Public Administration must comply with the principles of legality, impersonality, morality, publicity, and efficiency. Thus, public actions must be conducted along technical lines, which can define the policies to be conducted and the goals to be ach­ ieved by the administration. It is a primary function of public adminis­ tration to use public resources efficiently to ensure the provision of services to the population [1], considering administrative efficiency as

the direct relationship between the maximization of public services and the use of available resources [2]. Public policies in Brazil are sometimes conducted without the use of technical criteria, based on data and the application of scientific methods, following a rational decision-making approach. Rather, they are conducted through political approaches, determined by the under­ standing of public managers regarding which actions they wish to take in their management. The use of institutional public governance, strat­ egy and control allows the representatives of a public organization and its interested parties to assess its situation and demands, direct its

* Corresponding author. E-mail addresses: [email protected] (A.A. Steiner), [email protected] (D.G.B. Franco), [email protected] (E.O.B. Nara), [email protected] (M.T.A. Steiner). https://doi.org/10.1016/j.seps.2023.101748 Received 30 July 2023; Received in revised form 19 October 2023; Accepted 29 October 2023 Available online 31 October 2023 0038-0121/© 2023 Elsevier Ltd. All rights reserved.

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actions, and monitor its functioning [3]. The realization of public works is of great importance in this context. First, because they tend to have significant values and, secondly, because public works delivered to the population are more socially relevant than their mere physical presence [4], by directing activities, financial resources and the commitment and efforts of the institution’s servers. In this respect, it is of great importance to establish criter­ ia/indexes/indicators for determining the hierarchy of works that must be conducted by a public entity, mainly works considered ordinary, that is, those that do not stand out from a set of alternatives by degree of emergency or importance. Thus, the aim of this work is to focus on improving the exercise of public administration, making a relevant contribution to society through the better application of public resources. This is done through the presentation of a methodology that can be applied in the hierarchy of public works so that, in technical and objective terms, guidance can be provided for public administration managers regarding decision mak­ ing. Consequently, hiring will be sustainable, as decisions will begin to be made based on a previously known and established need, optimizing human and financial resources. In addition, the tasks of public agents will be optimized, making contributions in social terms by directing activities and funds and strengthening the commitment of the in­ stitution’s servers when performing their tasks. The main contributions of this work are related to two aspects: 1) the creation of the methodology, step-by-step, which will be able to bridge existing gaps in public agencies due to the lack of an adequate technical procedure; and 2) the creation of technical indices aimed at applying the classic Fuzzy-Delphi decision-making technique. ´ To illustrate the methodology, a case study is presented of the Parana ´; TJPR), in which the State Court of Justice (Tribunal de Justiça do Parana Fuzzy-Delphi technique was applied to a group of experts from the institution in two stages, with the adoption of triangular fuzzy numbers, aiming to understand, validate and refute the goals set by in public policy [5]. The technical indices created for this case study, explained in Section 4.1 of this article, were: area index; dispersion index; leasing index; index based on the HDI (human development index); growth index; physical index and accessibility index that, together, will generate the general hierarchization index (GHI). The article is organized as follows. In Section 2, a literature review is presented regarding the technique employed and some correlated works. Section 3 contains a description of the case study in question, with all its details. The methodology used, including the creation of technical indices and the Fuzzy-Delphi technique, is presented in Section 4. Sections 5 contains information on the results of the case study, and the conclusions of the study are discussed in Section 6.

Table 1 Articles related to decision making that used multi-criteria techniques, in chronological order. Author(s) (year)

Objective

Technique (s) used

Place applied

Stefano, Casarotto Filho & Duarte [6] McMillan; King; Tully [7]

Evaluation of the management of scientific journals How to use the nominal group in the pharmaceutical field Exploration and analysis of various opinions associated with public policy for sustainable purchases Measurement of dynamic capabilities of service companies Making and evaluation of accounting choices based on an intelligent system Development of a payment program for environmental services Analysis of critical factors for the successful deployment of drones in the logistics sector Classification and identification of scientific publications Evaluation of different authentication methods for online banking services Evaluation and classification of different alternatives for supplying water systems in a farming system Analysis and evaluation of the performance of principal public railroad organizations Predictions to minimize the spread of COVID-19 during the pandemic Analysis of tourism trends through building scenarios A study of research on school counseling

FuzzyDelphi

Brazil

NGT and Delphi

Australia

Delphi

Brazil

Delphi

Brazil

ANN and MCDM Delphi

International oil and gas company Brazil

GreyDEMATEL

United States of America

FuzzyDelphi

Indonesia

DEMATEL

Iran

TOPSIS

Azerbaijan

AHP, DEA, VIKOR and MPI

India

Fuzzy-AHP

Saudi Arabia

Delphi

Portugal

Delphi

Malaysia

Management of risks and uncertainties during the management phases of public-private partnerships Development of a virtual learning module based on problems for an Islamic studies course Classification of various attributes responsible for the implementation of an electronic governance system Classification of the importance of pillars within an ESG model

Fuzzy-AHP; FuzzyTOPSIS

Iran

FuzzyDelphi

Malaysia

TOPSIS; WSM; WPM

India

AHP; Delphi

South Africa

Measurement of the performance of learning institutions based on interviews with a panel of experts

FuzzyDelphi; BWM

Iran

Couto & Ribeiro [8]

Franco et al. [9] Duan; Yeh [10] Mariottoni; Canada [11] Raj; Sah [12]

Ciptono et al. [13] Sepehri-Rad; Sadjadi; SadiNezhad [14] Ardestani et al. [15]

Kumar; Singh; Vaidya [16] Baz; Alhakami; Alshareef [17] Moreira; Santos [18] Hizam; Sivalingam; Zandi [19] Jokar; Aminnejad; Lork [20]

2. Theoretical background This section discusses some related works that make use of multi­ criteria decision-making techniques to determine the weights of estab­ lished technical criteria for the hierarchization process. The theoretical basis of the Delphi, Fuzzy and Fuzzy-Delphi methods, used to achieve the goals of this work, are then presented.

Yusoff et al. [21]

Sahoo; Behera; Pattmaik [22]

2.1. Related work Decision-making techniques have been extensively used in a wide range of fields of knowledge, with studies conducted using a wide va­ riety of tools. Some of these studies are briefly presented below and summarized in Table 1 to highlight their similarities and contrasts. The multicriteria decision process was used to obtain preference weights for coastal space suitability criteria. Stefano, Casarotto Filho and Duarte [6] presented a study proposing an instrument to evaluate the management of scientific journals using the intellectual capital approach through Fuzzy-Delphi modeling. A questionnaire was prepared and distributed to seven expert editors of scientific journals, with rounds for surveying

Matemane; Moloi; Adelowotan [23] Petrudi; Ghomi; Mazaheriasad [24]

(continued on next page)

2

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literature analyses on the use of the technique. The results allowed adequate interaction in the field of learning, enabling the selection of specialization courses in professional schools, according to the skills required by industry. Sepehri-Rad, Sadjadi and Sadi-Nezhad [14] used the Dematel technique with experts from the banking sector to evaluate the different authentication methods for online banking services. The study evaluated 12 criteria that were divided into two groups of cause and effect, determining eight factors that effectively influence online banking. Ardestani et al. [15] used the multicriteria decision method known as TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to evaluate and classify different alternatives for supplying water systems for farming in the Poldasht Basin in West Azerbaijan. They used four sets of criteria, including social, economic, technical, and bioenvironmental definitions. Kumar, Singh and Vaidya [16] analyzed public railroad organizations in India by integrating four techniques to evaluate the performance of transport systems into 23 criteria for two consecutive years. Baz, Alhakami and Alshareef [17] developed a model based on the Fuzzy-AHP technique to aid experts working on strategies to minimize the spread of the coronavirus and predict the most vulnerable regions of Saudi Arabia. Moreira and Santos [18] used Delphi to construct scenarios on trends in tourism with a view to providing a better outlook for planning and managing tourist destinations. Hizam, Sivalingam and Zandi [19] presented a conceptual work with the application of the Delphi technique for school counseling, with the technique used to predict future scenarios. Jokar, Aminnejad and Lork [20] used the Fuzzy-AHP and Fuzzy-TOPSIS methods to manage risks and uncertainties in the management phases of public-private partner­ ships. Yusoff et al. [21] used the Fuzzy-Delphi technique to develop a problem-based virtual learning module for an Islamic studies course. Sahoo, Behera and Pattmaik [22] presented a comparative study of techniques such as TOPSIS, WSM (Weighted Sum Model) and WPM (Weighted Product Model), to find the classification of several attributes responsible for better decision making to implement the e-governance system in India. Matemane, Moloi and Adelowotan [23] aimed to clas­ sify the importance of the pillars within an ESG (Environmental, Social and Governance) model and five indicators below each pillar for determining executive compensation plans through the AHP. The Fuzzy-Delphi and BWM (Best Worst Method) techniques were used by Petrudi, Ghomi and Mazaheriasad [24] in a performance anal­ ysis of educational institutions. Peng and Zhou [25] used fuzzy multi­ criteria decision-making criteria and ANN technology to conduct decision-making research on the relevant factors of the allocation of public sports resources in international tourist cities. The AHP and TOPSIS methods were used by Odoi-Yorke, Owusu and Atepor [26] to rank the performance of 10 hybrid renewable energy systems for sus­ tainable port operations in Ghana. The criteria were technical, eco­ nomic, environmental, socio-cultural, and political. Rana et al. [28] applied Fuzzy-Delphi for evaluating biopsychosocial factors for systematic prioritization of patients in public healthcare systems. The chosen objectives and its application are based on hospital conditions, and in consultation with the surgeons in hospital in Pakistan. Danaci and Yildirim [29] applied the Fuzzy-Delphi method for prioritize the factors responsible for lifeboat accidents and to provide compre­ hensive recommendations for managers and policymaker. Jahanvand et al. [30] used the Fuzzy-Delphi method to determine essential criteria for selection of risk assessment techniques in occupa­ tional health and safety. A ranked list of 25 weighting criteria was presented in the form of nine dimensions, without considering a specific organization or industry. Tuni et al. [31] applied the Fuzzy-Delphi method to assess the risk factors to the industrial case of composite materials, identifying 24 major risk factors for innovative circular business models that were classified into six categories. Rongen et al. [32] applied the Fuzzy-Delphi method to identify promising stakeholder interactions at peripheral mobility hubs through the concept of multi-sided platforms in the Netherlands. Oteng, Zuo and

Table 1 (continued ) Author(s) (year)

Objective

Technique (s) used

Place applied

Peng; Zhou [25]

Allocation and optimization of public sports installation resources in international tourist cities Classification of the performance of 10 hybrid renewable energy systems for sustainable harbor operations: Takoradi Harbor as a case study Evaluation on end-of-life solar photovoltaic management Evaluation of biopsychosocial factors for patient’s prioritization Prioritization of factors responsible for lifeboat accidents Determining essential criteria for selection of risk assessment techniques in occupational health and safety Risk assessment for circular business models

Fuzzy and ANN

International tourist resorts

AHP; TOPSIS

Ghana

FuzzyDelphi

Australia

FuzzyDelphi

Pakistan

FuzzyDelphi

Turkey

FuzzyDelphi

Iran

FuzzyDelphi

Identification of promising stakeholder interactions

FuzzyDelphi

Composite materials industries Netherlands

Odoi-Yorke; Owusu; Atepor [26]

Oteng; Zuo; Sharifi [27] Rana et al. [28] Danaci; Yildirim [29] Jahanvand et al. [30]

Tuni et al. [31] Rongen et al. [32]

Key (in alphabetical order): AHP (Analytical Hierarchical Process); ANN (Artificial Neural Network); BWM (Best Worst Method); DEA (Data Envelopment Analysis); DEMATEL (Decision-making Trial and Evaluation Laboratory); ESG (Environmental, Social and Governance); GAIA (Geometrical Analysis for Interactive Assistance); MCDM (Multi-Criteria Decision Making); MPI (Malm­ quist Productivity Index); NGT (Nominal Group Technique); PROMETHEE (Preference ranking organization method for enrichment evaluations); TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution); Vikor (VlseKriterijuska Optimizacija I Komoromisno Resenje); WSM (Weighted Sum Model); WPM (Weighted Product Model). Source: Prepared by the authors (2023).

the points. McMillan, King and Tully [7] presented a general view of the Nominal Group Technique and Delphi techniques, with an application in the pharmaceutical field. Couto and Ribeiro [8] also used the Delphi method to explore and analyze various opinions associated with public sustainable purchase policies in the federal sphere. Thirty-five experts were chosen through selective sampling and from different segments of society. Meanwhile, Franco et al. [9] adopted Delphi to measure dy­ namic capabilities in service companies through the opinion of experts. The study included three rounds, and the result was 12 responses. Duan and Yeh [10] presented an intelligent system to make and evaluate ac­ counting choices through the preparation of an ANN (Artificial Neural Network) model created to examine the interactions between opera­ tional data and accounting results. The ANN were adopted together with multicriteria decision-making techniques associated with strategic business objectives. Mariottoni and Canada [11] used Delphi for a payment program for environmental services for the protection of springs in collaboration ˜o Paulo State. Raj and Sah [12] developed a with the Government of Sa work related to the use of drones by companies in the logistics sector, evaluating the factors that can play a significant role in the use of this tool, employing the Grey-Dematel multicriteria technique. Cypton et al. (2019) presented a study on projects that adopted the Fuzzy-Delphi method to classify and identify scientific publications and perform 3

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Sharifi [27] evaluated end-of-life solar photovoltaic waste management using the Fuzzy-Delphi method.

Research can be performed in accordance with the self-explanatory steps presented in the flow chart in Fig. 1. It must be objective and contain only the data and information required for analysis by the ex­ perts participating in the research. The application of the Delphi method is a relevant factor regarding obtaining more consistent data, repre­ senting a valuable communication tool with a group of experts (MARI­ OTTONI & CANADA, 2017). It is also characterized as a facilitating instrument for the drafting of public policies and in aiding decision making [38].

2.2. Delphi Method The Delphi Method, developed by Ref. [33], allows the weights of technical criteria to be determined based on research conducted with a panel of experts. Experts are consulted to take advantage of the knowledge and experience of the institution’s professionals to determine what is most relevant for decision making. When the method is applied, comparisons or direct communication between panel members should be avoided, so that the understanding of one expert does not interfere with the understanding of one or more other members of the panel. Thus, the anonymity of the participants is essential and must be pre­ served throughout the research period. An expert represents a very specific perspective on a subject to be integrated with other views, but does not imply a final or definitive word on the topic in question [34]. Taylor et al. [35] highlighted the impor­ tance of linking the investigative strategy of the panel of experts to the research purposes. The process of assembling groups of experts without concern for geography is one of the characteristics of the technique [36], and the consulted experts can respond electronically to the questions that are asked. In studies using the Delphi technique, researchers should analyze whether agreements were reached during the rounds that were conducted [37].

2.3. Fuzzy theory People often find it difficult to judge their opinions with certainty on a given scale. The differentiation between alternatives tends to be dis­ torted in the opinion of the judges [41], without the necessary precision to differentiate between black and white colors, for example. In this respect, Zadeh [42] presented a theory to “work around” these un­ certainties presented by linguistic or scale variables. In fuzzy theory, fuzzy numbers are employed to represent linguistic variables, providing a strict mathematical framework in which vague, subjective, and imprecise theories can be studied scientifically [43]. Traditionally, according to classical set theory, the true value of a response can be represented by a binary membership function, as pre­ sented in (1).

Fig. 1. Usual stages of research using the Delphi Method. Source: Adapted from Godet [39] and Landeta [40]. 4

A.A. Steiner et al.

{

μA (x) =

1, if x ∈ A 0, if x ∈ ∕A

Socio-Economic Planning Sciences 90 (2023) 101748

triangular fuzzy number form. The ranking process occurred by select­ ing the defuzzification value based on the expert consensus that the highest value is determined by the most prominent ranking [59]. The Fuzzy-Delphi method was used with the aim of identifying and selecting the main factors for evaluating innovation capacity, based on the intellectual capital of industrial sectors in Indonesia, in a study prepared by Lianto [60]. The author used a questionnaire to collect opinions from industry professionals and academic experts defined based on the domain of the research topic and professional experience. The development of research involving the preparation of ques­ tionnaires assigned to specialists with the application of defuzzification of results is an object present in the routine of organizing work with the Fuzzy-Delphi method [61,62]. The use of this method with the engagement of experts with broad knowledge of the subject can favors obtaining a result that is closer to the reality of the object under study.

(1)

Meanwhile, for fuzzy theory, fuzzy numbers can be referred to as a set of real numbers based on the concept of confidence intervals [24]. As an example of the use of this theory, triangular fuzzy numbers are often used because of the convenience of calculation and simplicity, being better understood by the manager. The triangular fuzzy number may be ̃ = (l, m, u), defined by (2) and, in represented with three points: A

addition, by Fig. 2. ⎧ (x − l) ⎪ ⎪ , if l ≤ x ≤ m ⎪ ⎪ ⎪ (m − l) ⎪ ⎨ μA˜ (x) = (u − x) ⎪ , if m ≤ x ≤ u ⎪ ⎪ ⎪ (u − m) ⎪ ⎪ ⎩ 0, otherwise

(2)

3. Description of the problem

Associated with multicriteria decision-making methods, the Fuzzy technique has been widely used in the literature because it involves uncertainties in the judgments made by experts [44–48].

´ State, The TJPR is an arm of the Judiciary Branch of Power of Parana Brazil, based in the city of Curitiba, the state capital. It has jurisdiction in all state territory. Its main activity is the provision of jurisdictional services statewide. The TJPR is classified as a Large Court, being one of the five courts across the country that are classified in this group [63]. According to data from Justice in Numbers for 2022, the Judiciary in ´ comprised, in 2020, a total of 929 judges and 18,592 civil ser­ Parana vants. In the jurisdictional sphere, it had a volume of 1,281,624 new cases and had accumulated 3,754,090 pending cases. The Judiciary of Paran´ a State, in 2022, comprised 162 Districts and 192 buildings, encompassing the 399 municipalities in the state, thus with an average of 2.45 municipalities per district. According to the National Justice Council (Conselho Nacional de Justiça; [64]), a district corresponds to the territory in which a first-grade judge exercises his jurisdiction and may cover one or more municipalities, depending on the number of residents and voters, how busy the forum is, the territorial extension of the state’s municipalities, and other aspects. Therefore, ´ each district may have several judges or only one. The map of Parana State shown in Fig. 3 shows the distribution of the state’s districts. The TJPR currently uses a hierarchization/ranking process of dis­ tricts that require works to be conducted based on technical data from each district in the state, such as areas of land, constructed area and the age of the buildings. According to the examined record by authors, there is no data related to the state of conservation and accessibility of each building, and there is no evaluation of the population served and the HDI of the districts. The different colors on the Map shown in Fig. 3 represent the size of the Districts. The blue color shows the advanced districts in metropol­ itan areas that have a population greater than 400,000 inhabitants, while the advanced districts indicated in red color have an estimated population between 80,000 and 400,000 inhabitants. The green color indicates the intermediate districts with a population between 30,000 and 80,000 inhabitants and, finally, the initial districts, below 30,000 inhabitants, are represented in yellow.

2.4. Fuzzy-Delphi Method The Fuzzy-Delphi method began to be used to overcome the possible deficiencies of judgments made by experts [49], being a combination of the Delphi method and the analysis of information using the definitions of fuzzy set theory [50–52]. Cheng and Lin [53] satisfactorily used fuzzy numbers attributed to the Delphi technique to achieve expert consensus. Fuzzy theory was also successfully employed to address the uncertainty and imprecision of judgments in a study conducted by Ocampo et al. [54]. Compared with the traditional method, the main advantage of the combined application of the Fuzzy-Delphi method is the comprehensive consideration of the uncertainty and ambiguity of the experts’ judg­ ment, which is generally subjective, so that their opinions can be fully reflected in the decision and results [55]. Using the Fuzzy-Delphi method provides at least four advantages: (a) overcoming the inevi­ table uncertainty; (b) reduce the number of searches; (c) the semantic structure of the prediction items can be explained; and (d) the individual attributes of the expert can be described [56]. Noorderhaven [57] indicated that applying the Fuzzy-Delphi Method to group decision can solve the fuzziness of common understanding of expert opinions. Zakaria, Hamzah, and Abduul Razak [58] conducted a survey to obtain expert opinions on the factors that influence Muslim students’ moral appreciation. An expert questionnaire was assigned to a group of 15 experts in two rounds, with the data examined and converted into a

3.1. The National Justice Council and resolution 114 The National Justice Council (CNJ) centralizes control of the administrative and financial activities of the Judiciary. It is also in charge of defining strategy and planning actions, such as the annual compilation of statistics in Justice in Numbers, the setting of manage­ ment goals for the courts, thematic joint efforts, and the nationalization of the electronic judicial process. According to Krüger and Freitas [65], the CNJ plays a fundamental role in regulating the activities of the Brazilian Judiciary, causing a breach in the principle of judicial impartiality. In the context of public works conducted by the Judiciary, on April 20, 2010, the CNJ published Resolution 114 [66], which provides,

Fig. 2. Triangular fuzzy number and its membership function. Source: Adapted from Petrudi et al. [24]. 5

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Fig. 3. Map of Paran´ a State with its 399 municipalities (thin lines) and the distribution of the 162 districts (thick lines). Source: Planning Department of the TJPR (2022).

among other matters, for the planning, execution and monitoring of works for the Judiciary. It also provides for reference areas to be used when drafting new projects for the renovation or construction of prop­ erties for the Judiciary. The establishment of criteria for drafting work plans, based on the institution’s needs program and strategic planning are presented in Article 2 of Resolution 114, in which, according to Paragraph 1, each work must have a priority indicator, obtained from the implementation of a technical evaluation system that includes the scoring and weighting criteria grouped as follows: I - Set 1 - Physical structure of the occupied property. The following criteria are used for evaluation, by scoring: a) coverage and fin­ ishings (floors, walls, ceilings, façade, and window frames, among others); b) electrical, voice, data and similar installations; c) hydraulic installations; d) security (grids, railing, alarms, prevention and firefighting, etc.); e) condi­ tions of efficiency, hygiene and healthiness; f) the building’s potential for pathologies (depending on its age and/or condition); g) functionality (sec­ torization and articulation of spaces); h) accessibility, location and inter­ connection with public modes of transport; and i) other objective criteria deemed relevant. II - Set 2 - Adequacy of the property for the jurisdiction. These criteria are intended to evaluate, by weighting, the fulfillment of the needs of jurisdictional activities, in view of: a) the strategic policy of the court for replacing the use of leased or assigned properties, with emphasis on ad­ equacy for the provision of legal services; b) the strategic policy of the court for the concentration or dispersion of its physical structure; c) the availability of current space in the areas recommended by the National Justice Council; d) number of cases handled over the years and a projection for the coming years; e) the demands of the population served and the economic and social development of the region; f) possible changes in the administrative structure of the court, such as the creation of new branches or an increase in the number of civil servants and judges; g) the adoption of new technologies (IT,

energy efficiency, sustainability guidelines, among others). Thus, the parameters of the criteria to be adopted for the preparation of a multicriteria decision-making process for judicial works have already been legally presented in Resolution 114. It falls to the institu­ tion to determine the indices or technical criteria and the form of calculation to establish the comparison parameters between the alter­ natives under analysis. It also falls to the institution to determine and set weights for the various criteria to be adopted in decision-making processes. Thus, this article was prepared with the perspective of complying with CNJ Resolution 114 for the hierarchization of engineering works for decision making regarding the works to be conducted by the entities of the Judiciary. The perspective of assistance for conducting engi­ neering works by the Judiciary must fully comply with the legislation presented in the Resolution 114, both regarding the descriptions of the reference areas presented for each space within public buildings for use by the Judiciary, as well as the criteria established for the development of a process of prioritizing these works. 4. Proposed methodology The proposed methodology to define the hierarchization of new engineering works for the Judiciary will be addressed according to the flowchart in Fig. 4, with the stages for defining the hierarchization process of the districts to be served by the construction of new forums. The proposed methodology has four main stages: analysis, collection and modeling of data and result (General Hierarchization Index, GHI). The analysis phase is the result of the institution’s policy of technical standardization for the creation and establishment of a database and technical data that enable effective compliance with CNJ Resolution 6

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Fig. 4. Stages of the proposed methodology. Source: Prepared by the authors (2023).

4.1.1. Area index (AI) The AI represents the ratio between the area suitable for providing the public service in relation to the reference area identified by the needs program as adequate for the provision of the judicial service. If the institution has more than one building in its own domain in a given region that provides the same public service to the same popula­ tion group, the areas of the buildings must be added for comparison purposes in relation to the reference area necessary to provide the public service to this population group. The calculation of the area index is determined by Formula (3). ∑ AOwNn If AIN = n 100 < 100⇒ new forum, (3) ArefN

114. The data collection phase involves obtaining technical information on the buildings in the districts and the process of selecting the districts that should be served by the building of a new court. The modeling phase uses the technical data of the problem through the creation of technical indices that will compose the GHI. In this stage, surveys are conducted with expert panels to obtain weights for the physical indices and accessibility indices of the building. The result phase is the final phase, in which the GHI of each district is obtained by applying the modeling to a panel of experts, obtaining all the data for the calculation of the GHI. The use of a hierarchization process of the districts in the decisionmaking process stems from the limitation of public resources at two levels: financial, within the principle that the institution should limit itself to spending the resources available in its annual budget; and human, considering that the number of professionals in the institution’s administrative and technical staff may limit the works carried out by the institution to a certain number. In this scenario, in which not everything that needs to be done can effectively be done, a rational approach is adopted, providing the public manager with knowledge of the hierar­ chical scenario of the necessary public works as a technical element of support for his decision making. It should be noted that, within the scope of the Judiciary, CNJ Res­ olution 114 determines that every work should have a priority indicator, obtained from the implementation of a technical evaluation system that in­ cludes the clustered scoring and weighting criteria ([66], Paragraph 1 of Article 2). The hierarchization demanded by the CNJ from the courts should serve as a basis for the drafting of the work plan, based on the program of needs, its strategic planning, and its guidelines.

where N represents each district, i.e., N = 1, 2, …, 162 and n is the number of buildings in District N (number that is variable according to District N). Thus: AIN = area index of District N; AOwNn = Own area of building n, belonging to District N; ArefN = Reference area needed to provide public services in District N. Therefore, if the number obtained for AIN in (3) is less than “100”, District N must participate in the hierarchization for the building of a new forum. The adoption of the AI as a defining requirement in the hierarchi­ zation process of the Districts is in direct compliance with Item “c” of set 2 of Resolution 114 ([66], Article 2, Paragraph 1), which constitutes as a criterion for evaluation by weighting the availability of space in relation to the reference areas recommended by the National Justice Council.

4.1. Technical criteria

4.1.2. Dispersion index (DI) The DI considers the existence of more than one property for the provision of certain legal services in the same district. To the districts with more than one property being used as a forum, a value of “1” will be assigned to the Dispersion Index. For districts with two properties used for forums, an index of “0.90” is applied. Those with three properties are assigned an index of “0.8”. Meanwhile, those with four are assigned an index of “0.70”, and a value of “0.60” is assigned to those with five or more being used as forums.

The seven technical criteria, selected among others, developed and presented here were obtained based on the assessment of CNJ Resolu­ tion 114 which, in turn, is based on the institution’s needs program and strategic planning. This information is presented in Article 2 of the Resolution 114, which states in its first paragraph that every work must have a priority indicator, obtained from the implementation of a technical evaluation system that includes clustered scoring and weighting criteria. These theoretical criteria were created as shown below.

If DIN < 1⇒ new forum

7

(4)

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between the rise in new cases per district (NC), and judicial growth should be inversely proportional. In other words, the greater the rise in the number of new cases, the lower the index to be applied ought to be (with a view to reducing the DGI, which will provide the result of the hierarchization). This work considered that the Judicial Growth Index of a district should be obtained using Formula (8).

where N = 1, 2, …, 162; DIN = dispersion index of District N. If the value obtained for DIN in (4) is less than “1”, District N must participate in the hierarchization process for the building of a new forum. The adoption of the DI as a defining issue in the hierarchization process of the districts is in direct compliance with item “b” of Set 2 of Resolution 114 ([66], Article 2, Paragraph 1), in which it constitutes a criterion for evaluation, by weighting the strategic policy of the court on the concentration or dispersion of its physical structure.

JGIN =

4.1.3. Leasing index (LI) The LI considers the existence of more than a certain percentage M of leased area in relation to the owned area being used for a forum in the same district, as in (5). If LIN > MAleaNn ⇒ new forum

(5)

PopT TJC PSIN = PopT N

where N = 1, 2, …, 162; PSIN = index of the population served by District N; PopT = total population of all districts analyzed; TJC = total judicial courts of the analyzed districts; PopTN = population of District N; TJCN = total judicial courts in District N. The adoption of the Population Served Index as a defining require­ ment in the district hierarchization process is in direct compliance with item “e” of Set 2 of Resolution 114 ([66], Article 2, Paragraph 1), in which it is a criterion for evaluating, through weighting, the demand of the population served by the system and the social and economic development of the region.

(6)

where N = 1, 2, …, 162; HDIN = HDI of District N; HDIhcN = HDI of the host city for the provision of public services in District N. The adoption of the HDII as a defining issue for the hierarchization process of the districts is in direct compliance with item “e” of Set 2 of Resolution 114 ([66], Article 2, Paragraph 1), in which it constitutes a criterion to evaluate, by weighting, the demand of the population served and the economic and social development of the region.

4.1.6. Physical index (PhI) The purpose of the PhI is to establish the state of maintenance and use of the properties occupied by the District’s institution. This study proposes eight groups of infrastructure for analysis, clustered as follows: • Hydraulic installations (PhHNn): evaluation of the conditions of the hydraulic and sanitary installations, in addition to the sanitary ware and metals of each building n in District N. • Coverage and collection of rainwater (PhCNn): assessment of the condition of the tiles, roof structure and waterproofed slabs, in addition to the drainage conditions of the gutters and conductors of every building n in District N. • Electrical installations (PhElNn): assessment of the conditions of the electrical wiring, switchboards, outlets, internal and external light­ ing, and the lightning protection system (LPS) of every building n in District N. • Fire protection and prevention system (PhFiNn): assessment of the conditions of fire extinguishers, hydrants and other elements that make up the system, in addition to emergency lighting blocks and signaling for escape in case of fire in every building n in District N. • Structure (PhSNn): assessment of the conditions of the concrete structure of buildings regarding signs of corrosion and deterioration of the steel and concrete elements of every building n in District N. • Coating (PhCoNn): assessment of the conditions of the building’s coating elements for floors, ceilings, doors, and the internal and external painting of every building n in District N.

4.1.5. District growth index (DGI) The DGI is determined through objective information that enables an assessment of whether the location is growing, such as population growth and a rising number of new cases in the district court. For the reality of the Judiciary, there is the possibility of obtaining information on the growth of a given location through the Judicial Growth Index of the District (JGI) and the Population Served Index (PSI) of the District. Considering that these two indices equally reflect the growth of a dis­ trict, the DGI can be obtained by averaging the two indices, using For­ mula (7). JGIN + PSIN 2

(9)

TJCN

4.1.4. Index related to the human development index (HDII) The HDII is applied considering the principle of the need for the state to make priority investments in less favored regions to aid economic and social development. To analyze and apply the HDI index, the HDI Index of the district can be determined by adopting the official index of the host city of the district, according to the list presented by the Brazilian Institute of Ge­ ography and Statistics [67], as in (6).

DGIN =

(8)

where N = 1, 2, …, 162; JGIN = judicial growth index of District N; NCN = rise in the number of new cases in District N. Meanwhile, the Population Served Index (PSI) demonstrates the population growth in the region, represented in this article by the ´ population of the municipalities that make up each District in Parana State. The proportion of the population served by each Judicial Court in each District is a simple calculation, as it is the direct ratio between the total population of the District (PopTN) and the number of Judicial Courts of the district (TJCN). This ratio was adopted for each of the districts in the state, with the understanding that the greater the pro­ portional population served by each judicial court in a district, the greater the need to prioritize work on a new forum. This reasoning is generalized in (9).

where N = 1, 2, …, 162; LIN = leasing index of District N; AleaNn = Area located in District N; M = percentage that must be evaluated and determined by the institution, in accordance with its understanding of the possibility of having properties that are not its own for the provision of judicial services provided in the district. The adoption of the LI as a defining requirement in the hierarchi­ zation process for the districts directly complies with item “a” of Set 2 of Resolution 114 ([66], Article 2, Paragraph 1), in which it is declared a criterion to evaluate, by weighting, the strategic policy of the court to replace the use of leased or assigned real estate, with emphasis on how adequate it is for the provision of jurisdictional services.

HDIN = HDIhcN

1 NCN

(7)

where N = 1, 2, …, 162; DGIN = the growth index of District N; JGIN = judicial growth index of District N; PSIN = population served index of District N. The aim of the measurement (or Index) of Judicial Growth of a District is to conduct a statistical assessment of the rise in the number of new legal cases compared with the previous period. The relationship 8

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• External services (PhExNn): assessment of the conditions of the external paving of the sidewalk and parking areas, in addition to the conditions of the railings and boundary walls of every building n in District N. • Frames and glazing (PhFrNn): assessment of the conditions of the window frames and glazing of each building n in District N.

Considering that the physical score of the district will be on a scale of 1–10, the calculation of the PhI of the district must be transformed into a decimal scale proportional to the PhS assigned to the district. As this PhS is inversely proportional to the PhI of the district, the higher the PhS, the lower the PhI must be. Formula (12) is used to calculate the PhI of the district.

To obtain the PhI of District N, in the case that the Judicial District has a single property (only one building used as a forum), the PhI of building n will be the physical score to be assigned to Judicial District N. For Districts with two or more forums, the PhI of the district must be obtained through the weighted average of the scores of buildings n ac­ cording to their areas, in accordance with (10) and (11).

PhINn =

PhIN = 1 −

1 SPhN

(12)

where N = 1, 2, …, 162; PhIN = physical index of District N; SPhN = physical score of District N, obtained through (11). Furthermore, it should be observed that, through Formula (12), the values of the PhI scores will always be between 0 and 10.

(weightHNn PhHNn ) + (weightCNn PhCNn ) + (weightElNn PhElNn ) + ... + (weightFrNn PhFrNn ) (weightHNn + weightCNn + weightElNn + ... + weightFrNn )

(10)

The adoption of the physical index of the population served as a defining requirement of the hierarchy process of the Districts directly complies with items “a”, “b”, “c”, “d”, “e” and “f” of Set 1 - Physical Structure of the occupied property - of Resolution 114 ([66], Article 2, Paragraph 1), which constitutes a criterion aimed at evaluating, by scoring: a) coverings and finishing (floor, wall, ceiling, façade, window frames, etc.); b) electrical, voice, data and similar installations; c) hydraulic installations; d) security (grids, railing, alarm, prevention, firefighting, etc.); e) the conditions of efficiency, hygiene and healthiness; and f) the building’s potential for pathologies (depending on its age and/or condition).

where N = 1, …, 162 Districts; n = varies according to the number of buildings in District N; PhNn = physical score for building n in District N; PhHNn = score for the hydraulic installations of building n in District N; PhCNn = score for coverage and collection of rainwater of building n in District N; PhElNn = score for electrical installations of building n in District N; PhFiNn = score for fire prevention and protection of building n in District N; PhSNn = score for the structure of building n in District N; PhCoNn = score for the coating of building n in District N; PhExNn = score for external services of building n of District N; PhFrNn = score for window frames and glazing of building n in District N. These scores have the corresponding weights: weightHNn; weightCNn; weightElNn; weightFiNn; weightSNn; weightCoNn; weightExNn; weightFrNn. The weights indicated here must be determined by the competent technical sector of the institution in order to represent, in variables from 1 (not relevant) to 5 (extremely relevant), the reality of which groups of installations in the building are most relevant, in relation to the others, for their physical maintenance. For the work reported in this paper, these weights were determined by applying the Fuzzy-Delphi method along to specialist engineers from the TJPR’s Engineering and Archi­ tecture Department, in a similar way to the application of the technique described in section 4.2. ∑ PhINn ANn SPhN = n ∑ (11) ANn

4.1.7. Accessibility index (AccessI) The aim of the AccessI is to establish the state of accessibility of the properties occupied by the institution in the district. The present study proposes five clusters of infrastructure for analysis, clustered as follows: • Existence of ramps and/or platforms or elevators to overcome diffi­ culties and facilitate access at the entrance and to other floors of building n in District N (AcRampNn); • Existence of a guardrail and handrail on the stairs and ramps in building n of District N (AcHandNn); • Existence of sanitary spaces adapted for people with special needs in building n of District N (AcSaniNn); • Existence of reserved parking spaces for disabled people in building n of District N (AcParkNn); • Existence of tactile paving from the access points to the information desk/registry office in building n of District N (AcTactNn). The process for obtaining the AccessI for building n in District N is similar to the process for obtaining the PhI, that is, it is assigned by a technical team for each group of facilities. To determine their weights, the research process was also applied to a panel of technical experts.

n

where N = 1, …, 162 Districts; n = varies according to the number of buildings in District N; SPhN = physical score of District N; PhINn = physical score of building n of District N. ANn = area of building n of District N. While the physical scores of the facilities for each building n of each District N are assigned by a technical team, their weights are determined by applying the research process to a panel of technical experts made up of engineering and architecture professionals from the institution.

In the case of districts with two or more forums, the AccessI should be obtained through the weighted average of the scores of the buildings according to their areas. Thus, the AccessI of each building should be multiplied by the area of this building. After being added together, the result must be divided by the sum of the areas of the buildings in the District, as shown in (13) and (14), below.

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( AcessINn =

Socio-Economic Planning Sciences 90 (2023) 101748

) weightRampNn AcRampNn + (weightHandNn AcHandNn ) + ... + (weightTactNn AcTactNn ) ( ) weightRampNn + weightHandNn + ... + weightTactNn

where N = 1, …, 162 Districts; n = varies according to the number of buildings in District N; ARampNn = score for ramps and/or platforms or elevators to overcome difficult accesses at the entrance and other floors of building n in District N; AHandNn = score for the guardrail and handrail on staircases and ramps in building n in District N; ASaniNn = score for the sanitary spaces adopted for people with spe­ cial needs in building n of District N;

GHIN = AIN

interconnection with modes of public transport. 4.1.8. General hierarchization index (GHI) With the construction of the seven indices that were previously presented, it is finally possible to define the GHI to assign a score to the district to classify all those that need the construction of a new forum. The GHI is assigned according to Formula (16) and should be applied to each of the 162 jurisdictions of the TJPR.

(weightDIN DIN + weightLIN LIN + ... + weightPhIN PhIN + weightAcessIN AcessIN ) weightDIN + weightLIN + .... + weightPhIN + weightAcessIN

AParkNn = score for parking spaces reserved for people with special needs in building n of District N; ATactNn = score for tactile paving from access points to the informa­ tion desk/registry office of building n in District N. These scores have their corresponding weights: weightRampNn; weigh­ tHandNn; weightSaniNn; weightParlNn; weightTactNn. In a similar way to the determination of weights described for the physical index, the weights of groups of accessibility facilities must be determined by the technical sector of the institution. For this purpose, the Fuzzy-Delphi method was used along with specialist engineers from the TJPR’s Department of Engineering and Architecture, in a similar way to the application of the technique described in section 4.2. ∑ AcessINn ANn SAcessN = n ∑ (14) ANn

4.2. Application of the Fuzzy-Delphi Method In order to apply the Fuzzy-Delphi method to the case study, we have to obtain the weights presented in Formula (16). For that, a survey was conducted with the panel of management experts for the administrative evaluation of decision making for the building of a new forum. The questionnaire prepared for the experts was based on the premise that the area of a court owned by the TJPR in each judicial district is insufficient to meet all face-to-face legal demands. In addition to iden­ tifying the civil servants participating in the panel of experts, the questions asked to determine the weights of the indices in the applica­ tion of the case study regarding decision making about conducting works by the TJPR were as follows:

where N = 1, 2, …, 162; n = varies according to the number of buildings in District N; SAcessN = accessibility score of District N; AcessINn = accessibility score of building n of District N obtained with (13); ANn = area of building n in District N. Considering that the SAccess of the district will be assigned a value on a scale from 1 to 5, the calculation of the AccessI of the district should transform the SAccess of District N into a decimal scale proportional to the assigned score. The AccessI is calculated using Formula (15). It should be observed that the values of the SAccess of the district will always be from 0 to 5. 1 2SAcessN

(16)

where N = 1, 2, …, 162; GHIN = general hierarchization index of District N; AIN; DIN; LIN; DGIN; HDIIN; PhIN; AccessIN are the seven already defined indices; weightDIN; weightLIN; weightDGI; weightHDIIN; weightPhIN; weightAccessIN are the corresponding weights of the six indices. It should be observed that the AIN is not linked to a weight as it is considered the main tech­ nical index of the hierarchization process. Thus, the other technical indices are applied as qualifiers of the AI of each district.

n

AcessIN = 1 −

(13)

a) What impact does the existence of more than one building for use as a forum (leased, assigned, or owned) in the same judicial district have on the decision-making process for the construction of a new forum (of a larger size that can centralize all the judicial activities of the district)? (weightDI) b) What impact does the existence of a building leased by the TJPR in the district have on the decision-making process to build a new forum? (weightLI) c) What impact does judicial growth (statistical increase in the number of new cases per judicial court) and population growth in the district have on the decision-making process for building a new forum? (weightDGI) d) What impact does the HDI of the district have on the decision-making process for the building of a new forum? (weightHDI) e) What impact does a building in a more precarious state of conser­ vation, leading to the need for significant building works at the district forum, have on the decision-making process to build a new forum? (weightPhI)

(15)

where N = 1, 2, …, 162; AccessIN = accessibility index of District N; SAccessNn = score for the accessibility of building n in District N, obtained with (14). With Formula (15), the values of the AccessI scores will always be between 0 and 10, since the SAccess is multiplied by 2. Thus, the PhI and AccessI can be treated under equal conditions. The adoption of the population served index as a defining require­ ment of the hierarchization process of the district complies directly with item “h” of Set 1 - Physical structure of the occupied property - of Res­ olution 114 ([66], Article 2, Paragraph 1), in which it is a criterion intended to evaluate, by scoring: h) accessibility, location and 10

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5.1. Regarding the research with the panel of experts

Table 2 Responses of the panel of expert managers to the first round of questions to determine the impact or importance of the technical indices. Index

To determine the weights of the indices to be used in Formula (16) of the GHI of the districts, a survey was conducted with a group of TJPR civil servants who occupy or have occupied strategic positions in the organization in recent years, with a direct link to the presidential decision-making advisors, that is, people with no political positions or connections. Limiting the number of experts is justified because the addition of more experts with less experience can weaken the accuracy of the results obtained [70]. The current and already occupied top positions in the administration by the selected servers are as follows (protecting the identity of the participants):

Experts

Dispersion (DI) Leasing (LI) Growth (DGI) HDI (HDII) Physical (PhI) Accessibility (AccessI)

Manager 1

Manager 2

Manager 3

Manager 4

Manager 5

4 4 5 4 4 4

4 2 3 4 5 3

5 5 4 4 4 5

4 4 3 3 5 4

3 3 4 3 5 4

Source: Prepared by the authors (2023).

• Manager 1: Judicial Technician and Director of the Judiciary Department. He has already held the positions of Director of the Office of the Presidency, General Secretary and Undersecretary of the TJPR; • Manager 2: Economist for the TJPR. She has held positions as Gen­ eral Secretary of the TJPR, Director of the Justice Fund (FUNJUS) and Director of the Outsourced Services Management Department; • Manager 3: Legal Consultant and Undersecretary of the TJPR. She has already held the positions of General Secretary of the TJPR and Director of the TJPR Planning Department; • Manager 4: Legal Consultant and Director of the Department of Patrimony of the TJPR. She has already held the position of General Secretary of the TJPR. • Manager 5: Legal consultant of the TJPR and its current Director of Planning, having occupied this position for the last six years.

f) What impact does a building with no or limited accessibility, creating the need for significant interventions to enable full accessibility to the district forum, have on the decision-making process to build a new forum? (weightAccessI) The objective questions had five levels of responses, as on a Likert [68] scale, with the option with “1 star” indicating little relevance or impact and the “5 stars” option indicating considerable importance or a great impact. In the combination of Fuzzy theory with the Delphi method, as proposed by Murray et al. [49], the maximum and minimum values of the collected responses are taken as terminal points of the triangular fuzzy numbers, and the geometric mean is considered as a degree of association of these numbers to derive the unbiased statistical effect and avoid the impact of extreme values [69]. In the methodological procedure of the Fuzzy-Delphi method, after obtaining the final responses from the experts through the Delphi method, as shown in Fig. 1, it is necessary to determine the triangular fuzzy numbers for each criterion i, defining:

Adopting the Delphi method, as shown in Fig. 1, the management experts were asked “two rounds” of questions (“a” to “f” of Section 4.2). After the results of the first round were obtained, the responses of each of the experts were presented individually, preserving their anonymity, so that each expert could issue a new response, either confirming or changing their original responses. The results for the first round are presented in Table 2, while Table 3 contains the results for the second round of questions. Once the responses presented by the panel of experts have been evaluated, the Fuzzy technique must be applied to the results, using Formula (17) on the final results obtained for each criterion, in accor­ dance with the data presented in Table 4. Thus, applying Formula (16) with the weights obtained in Table 4 to determine the GHI, results in Formula (18).

• li = min (lik) is the minimum classification value provided by the number of experts k for criterion i; • mi = (Ri1 x Ri2 x … Rik)1/k is the geometric mean of the classification provided by the number of experts k for criterion i; • ui = max (lik) is the maximum value of the classification provided by the number of experts k for criterion i. The next step handles the “defuzzification” of the information, which is performed using Formula (17), where Gi = score/weight for alterna­ tive i.

GHIN = AIN

(3, 9829DIN + 3, 9093LIN + 3, 4553DGIN + 3, 5921HDIN + 4, 5244PhIN + 3, 9829AcessIN ) where N = 1, 2, …, 162 23, 4469

(18)

5.2. Of the hierarchization process of building works (ui − li ) + (mi − li ) Gi = + li 3

(17)

Formula (18), which was obtained for the GHI of the districts, must be applied to District N to define the hierarchization/ranking of the districts to guide decision making regarding the building of a new forum. It should be highlighted that the values of the technical indices were previously determined according to the evaluation of the technical in­ formation of the buildings occupied by the TJPR in its database, eval­ ´ State, in accordance with uating all 162 districts in the interior of Parana Table 5. Table 5 presents, in addition to the technical indices, the GHI, already in hierarchical form, showing in an orderly way in which dis­ tricts should be served in terms of the need to build a new Forum.

The result of G for each criterion i indicates the weight to be assigned to the indices that comprise Formula (16) for the calculation of the GHI. 5. Results and discussions In this section, the results obtained in the research applied to the panel of experts and the results of the application of GHI Formula (16) in the case study of the TJPR are presented.

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technical indices and the GHI, which were presented were based on CNJ Resolution 114 and constitute the main methodology stage, is the main contribution of this article. The presentation of the applied technique indicates how a survey of a group of experts can be conducted to make use of their knowledge and administrative experience to aid good public management. The appli­ cation of the academically renowned Fuzzy-Delphi method to the TJPR case study proved to be simple and effective, enabling the weights of each technical criterion to be determined in a technical and objective way. The technical ordering of works, resulting from the application of weights to technical indices, is characterized as an important manage­ ment support tool, enabling the identification of demands characterized as priorities. The results obtained through the proposed methodology will allow the Public Administration to objectively determine which works should be included in the Annual Procurement Plan, required by Bidding Law 14.133/2021. They will also ensure an adequate technical character­ ization of the need to undertake a building work when drafting the Preliminary Technical Study. This leads to the sustainable management of Public Administration, optimizing resources and enabling an objec­ tive analysis of the best solutions through the application of decisionmaking support techniques. As suggestion for future work, the other needs also mentioned by Resolution 114 can be considered, in addition to the seven explored in this article. Furthermore, it is possible for other public institutions to adopt the methodology of the multicriteria decision-making process presented here, provided that its requirements and technical informa­ tion are observed. Institutions of the other Powers of the Republic could and should also be encouraged by public authorities to conduct technical studies similar to the proposal presented here, always clarifying the need for a clear and objective definition of the criteria and weights to be applied in the development of solutions for multicriteria decision making.

Table 3 Final responses of the panel of expert managers following the second round of questions to determine the impact or importance of the technical indices. Index

Experts

Dispersion (DI) Leasing (LI) Growth (DGI) HDI (HDII) Physical (PhI) Accessibility (AccessI)

Manager 1

Manager 2

Manager 3

Manager 4

Manager 5

4 4 4 4 5 4

4 3 3 4 5 3

5 5 4 4 4 5

3 4 3 4 5 4

4 3 3 3 4 4

Source: Prepared by the authors (2023).

It should be emphasized that through Formulas (3), (4) and (5), 116 candidate districts were selected from the total of 162 to be given a new forum. Of these 116 candidate districts, 15 are shown in Table 5, below, with the knowledge that the lower the value of the final GHI, the greater the need for a new forum. It is important to note that the districts of Amp´ere, Nova Aurora and Centen´ ario do Sul have zero scores for the GHI because they do not have their own building and, naturally, their AI is null, nullifying the value of the GHI. The four Districts were created about 10 years ago, and their own forums are currently under construction. 6. Conclusions The execution of public works must be planned and based on tech­ nical justifications and financial resources that indicate the need and the possibility of carrying them out. In this respect, the aim of this work was to propose a methodology for ranking public works for the Judiciary, making use of the Fuzzy-Delphi multicriteria method, together with criteria/indicators to support decision making. The creation of the seven

Table 4 Application of the Fuzzy-Delphi method to determine the weights of the technical indices. Index

Expert Managers

Dispersion (DI) Leasing (LI) Growth (DGI) HDI (HDII) Physical (PhI) Accessibility (AccessI) Sum

1

2

3

4

5

4 4 4 4 5 4

4 3 3 4 5 3

5 5 4 4 4 5

3 4 3 4 5 4

4 3 3 3 4 4

Geometric Mean (mi)

Max (ui)

Min (li)

Weight (Gi)

3.9487 3.7279 3.3659 3.7764 4.5731 3.9787

5 5 4 4 5 5

3 3 3 3 4 3

3.9829 3.9093 3.4553 3.5921 4.5244 3.9829 23.4469

Source: Prepared by the authors (2023). Table 5 Result of the hierarchization of the districts to be considered for new court forums for the first 15 districts in the state. Order

Name of District

Final GHI

AI

DI

LI

DGI

HDII

PhI

AccessI

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

´ AMPERE ´ CENTENARIO DO SUL NOVA AURORA ´ PONTAL DO PARANA COLOMBO ˆ CANDIDO DE ABREU ´ SENGES

0.00 0.00 0.00 0.00 12.91 21.98 22.23 23.58 23.62 23.67 24.69 25.89 26.17 26.73 27.03

0.00 0.00 0.00 0.00 16.41 23.04 25.80 26.86 24.87 27.44 24.66 31.50 30.28 29.29 30.89

1 1 1 1 0.60 1 1 1 1 0.90 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

0.82 1.10 0.71 0.95 0.82 1.69 1.10 1.41 1.51 1.67 0.79 1.14 0.84 0.80 2.06

0.709 0.668 0.733 0.738 0.733 0.629 0.663 0.700 0.671 0.701 0.696 0.637 0.701 0.718 0.640

0.871 0.863 0.828 0.776 0.848 0.895 0.866 0.805 0.745 0.765 0.874 0.877 0.829 0.868 0.855

0.742 0.884 0.900 0.861 0.719 0.865 0.852 0.819 0.872 0.761 0.783 0.727 0.833 0.774 0.865

SANTA MARIANA TEIXEIRA SOARES PRIMEIRO DE MAIO ´ ALTO PARANA ˜ JERONIMO ˆ SAO DA SERRA ˜ DO PINHAL RIBEIRAO MANDAGUAÇÚ BOCAIÚVA DO SUL

Source: Prepared by the authors (2023). 12

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Socio-Economic Planning Sciences 90 (2023) 101748

Declaration of competing interest

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. CRediT authorship contribution statement Alexandre Arns Steiner: Conceptualization, Methodology, Data curation, Writing – original draft, Writing – review & editing, Visuali­ zation. David Gabriel de Barros Franco: Software, Formal analysis, Writing – original draft, Writing – review & editing, Visualization. Elpídio Oscar Benitez Nara: Writing – review & editing, Validation, Supervision. Maria Teresinha Arns Steiner: Project administration, Funding acquisition, Writing – original draft, Writing – review & editing, Validation, Supervision. Data availability Data will be made available on request. Acknowledgments ˜o de Aperfeiçoa­ The study was financed in part by the Coordenaça mento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. References [1] Silva Filho GM, Pereira TRL, Dantas MG da S, Araujo AO. An´ alise da eficiˆencia nos gastos públicos com educaç˜ ao fundamental nos col´ egios militares do ex´ercito: evidˆ encia para os anos de 2009 e 2011. XIV Congresso USP. Controladoria e Contabilidade; 2014. [2] Matei AI, Savulescu C. Enhancing the efficiency of local government in the context of reducing the administrative expenditures. In: Public administrations in modern times: challenges and perspectives conference; 2009. [3] Steiner AA, Canciglieri Junior O, Nara EOB, Steiner MTA. Gest˜ ao híbrida de projetos em contrataç˜ oes públicas: estudo de caso para a implantaç˜ ao de um projeto de manutenç˜ ao predial comum. Rev Sodebr´ as 2023;18(206). https://doi. org/10.29367/issn.1809-3957.18.2023.206.76. [4] Lima EVA, Soares AS. Uma investigaç˜ ao dos crit´ erios de risco relativos ` as obras públicas na gest˜ ao municipal irregular. Rev Controle 2020;18(2):283–314. https:// doi.org/10.32586/rcda.v18i2.621. [5] Secchi L. Políticas públicas: conceitos, esquemas de an´ alise, casos pr´ aticos. Rev Administ Contemporˆ anea 2011;15(6). https://doi.org/10.1590/S141565552011000600017. [6] Stefano NM, Casarotto Filho N, Duarte MCF. Proposta de um instrumento de pesquisa para avaliar a gest˜ ao de peri´ odicos científicos: utilizando o m´etodo Fuzzy Delphi. Iberoam J Project Manag 2014;5(2):39–69. https://doi.org/10.6084/m9. figshare.1276131. [7] McMILLAN SS, King M, Tully MP. How to use the nominal group and Delphi techniques. Int J Clin Pharm 2016;38:655–62. https://doi.org/10.1007/s11096016-0257-x. [8] Couto H, L G, Ribeiro FL. Objetivos e desafios da política de compras públicas sustent´ aveis no Brasil: a opini˜ ao dos especialistas. Rev Adm Pública 2016;50(2). https://doi.org/10.1590/0034-7612146561. [9] Franco CK, Senff CO, Quandt CO, Lanza B. M´etodo Delphi para criaç˜ ao de um instrumento de mensuraç˜ ao de Capacidades Dinˆ amicas em serviços. Investig Qual Ciˆencias Soc 2017;3. [10] Duan Y, Yeh C-H. An intelligent system based approach to accounting choices evaluation and selection. Japan: Twenty-Second Pacific Asia Conference on Information Systems; 2018. p. 286–93 (aisel.aisnet.org/pacis2018/165/. [11] Mariottoni CA, Canada CB dos S. Aplicaç˜ ao do m´etodo Delphi na pr´ atica de serviços ambientais em mananciais. Rev DAE 2018;66(209). https://doi.org/ 10.4322/dae.2017.020. [12] Raj A, Sah B. Analyzing critical success factors for implementation of drones in the logistics sector using grey-DEMATEL based approach. Comput Ind Eng 2019;138: 1–12. https://doi.org/10.1016/j.cie.2019.106118. [13] Ciptono A, Setiyono S, Nurhidayati F, Vikaliana R. Fuzzy Delphi method in education: a mapping. J Phys Conf 2019;1360. https://doi.org/10.1088/17426596/1360/1/012029. [14] Sepehri-Rad A, Sadjadi SJ, Sadi-Nezhad S. An application of DEMATEL for transaction authentication in online banking. Int J Data Network Sci 2019;3:71–6. https://doi.org/10.5267/j.ijdns.2019.1.002. [15] Ardestani ME, Teshnizi ES, Babakhani P, Mahdad M, Golian M. An optimal management approach for agricultural water supply in accordance with sustainable development criteria using MCDM (TOPSIS). J Appl Water Eng Res 2020;8(2):88–107. https://doi.org/10.1080/23249676.2020.1761896.

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Alexandre Arns Steiner: Engineering degree in Civil Engineering from Federal Techno­ logical University of Paran´ a (UTFPR; 2003), Master’s degree in Production and Systems Engineering (PUC-PR). He has experience in Civil Engineering, with emphasis on Civil Construction. David Gabriel de Barros Franco: Engineering degree in Production Engineer from Pontifical Catholic University of Paran´ a (2012), Master’s degree and PhD in Production and Systems Engineering at Graduate Program in Production and Systems Engineering (PPGEPS PUC-PR; 2015; 2019). PPGEPS’ Post-doctoral internship between 2019 and 2020. He works in Production Engineering, with an emphasis on Operational Research, Metaheuristics, Machine Learning and Logistics Systems Modeling. He is currently pro­ fessor at the Federal University of Tocantins (UFT), at the Graduate Program in Digital Agroenergy (PPGADIGITAL) and at the Logistics Undergraduate Program at the Federal University of North Tocantins (UFNT). Elpídio Oscar Benitez Nara: Engineering degree in Mechanical Engineering from Federal University of Santa Maria (1986), Master’s degree in Production Engineering from Federal University of Santa Maria (1997) and PhD in Quality and Productivity Management from Federal University of Santa Catarina (2005). He has experience in Production Engineering, acting on the following subjects: business process management, total quality. Maria Teresinha Arns Steiner: Graduated in Mathematics at Federal University of Paran´ a (1978) and Bachelor’s in Civil Engineering at Federal University of Paran´ a (1981). Doc­ tor’s in Industrial Engineering Program at Federal University of Santa Catarina (1995). She got her Pos-Doc at ITA (2005) e another Pos-Doc at IST of Lisbon (2014). She worked at UFPR in Numerical Methods in Engineering Graduate Program (PPGMNE) and in Indus­ trial Engineering Graduate Program (PPGEP). She has worked in Catholic University of Paran´ a (PUCPR), in the Industrial and Systems Engineering Graduate Program (PPGEPS).

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