Decision Maker's Preferences Research Articles

Benchmarking nursing homes using the Order Rated Effectiveness model

Benchmarking, a critical process to compare relative performance of nursing homes, was implemented in an earlier study applying multicriteria measures of operational and quality of care efficiencies. In that study those measures were aggregated and optimized using Data Envelopment Analysis (Shimshak et al., 2009) [1]. The authors concluded that while providing useful analysis, the DEA results did not discriminate well among the nursing homes. In this paper we apply the Order Rated Effectiveness (ORE) model (Klimberg and Ratick, 2018; Klimberg and Ratick, 2020a; Klimberg and Ratick, 2020b) [2,3,4], to the Shimshak et al. data set to address that issue. The ORE model utilizes Order Weighted Averaging (OWA) to aggregate operational and quality performance measures, providing a range of relative performance measures for each nursing home. These aggregates are then used within a Data Envelopment Analysis (DEA) optimization framework. The use of OWA helps capture the implied preferences of multiple decision makers within the different nursing homes. We compare and evaluate the ORE results to those obtained in the original Shimshak et al. study. The ORE process provided aggregate comprehensive measures of relative performance that addressed both the multi-objective and multi-decision-maker character of this decision problem essential to making effective and actionable comparisons of nursing home performance.

A circular waste bioeconomy development model in the Ecuadorian fishery industry: the impact of government strategy on supply chain integration and smart operations.

This study develops a set of measures to address the interrelationship among circular waste-based bioeconomy (CWBE) attributes, including those of government strategy, digital collaboration, supply chain integration, smart operations, and a green supply chain, to build a circular bioeconomy that feeds fish waste back into the economy. CWBE development is a potential solution to the problem of waste reuse in the fish supply chain; however, this potential remains untapped, and prior studies have failed to provide the criteria to guide its practices. Such an analytical framework requires qualitative assessment, which is subject to uncertainty due to the linguistic preferences of decision makers. Hence, this study adopts the fuzzy Delphi method to obtain a valid set of attributes. A fuzzy decision-making trial and evaluation was applied to address the attribute relationships and determine the driving criteria of CWBE development. The results showed that government strategies play a causal role in CWBE development and drive digital collaboration, smart operations, and supply chain integration. The findings also indicated that smart manufacturing technology, organizational policies, market enhancement, supply chain analytics, and operational innovation are drivers of waste integration from fisheries into the circular economy through waste-based bioeconomy processes.

Simulating the CCUS technology diffusion in thermal power plants: An agent-based evolutionary game model in complex networks

The utilization of carbon capture, utilization, and storage (CCUS) technology is critical for achieving carbon neutrality and establishing a circular carbon economy. Thermal power plants represent a significant contributor to carbon emissions, and facilitating the spread of CCUS technology throughout the power industry is a crucial means of advancing this technology. The diffusion of CCUS technology would be influenced by policy incentives, market environment, enterprises' individual characteristics as well as complex social network relationships. To study the impacts of these factors on the diffusion of CCUS technology, this study develops an evolutionary game model of CCUS technology diffusion in thermal power plants based on a small-world network. This model includes agents as the network nodes with different production capacities and decision preferences. Through numerical simulations, the study examined the impact of market prices, carbon taxes, and subsidies as incentive measures under different diffusion environments. The results demonstrate that those with higher production capabilities show a higher level of sensitivity to incentives for technology diffusion. To reduce fiscal expenditure, the government can adopt differentiated incentive measures for enterprises with varying production capacities. In addition, the synergistic combination of various incentive measures can effectively decrease the government's expenses in promoting CCUS technology. The incentive mechanisms for promoting CCUS diffusion should be implemented preferably during the early stage of low-carbon transition in the power sector. As the operating hours of thermal power plants decrease, the cost of promoting technology diffusion increases.

Fried Chicken Consumer’s Preference and Purchase Decision Analysis During Covid 19 Pandemic Era

This study aims to observe the decision-making process on fried chicken purchases, and identify the most considered attribute, and combination of attributes based on consumer preference in the Covid-19 pandemic era. The pandemic has altered consumer behavior and consumption patterns, leading to changes in the food industry. Understanding how consumer preferences have shifted can help businesses adapt their strategies to better serve their customers. The data were collected using the questionnaire method through the Google Form platform with respondent criteria being fried chicken consumers who had purchased fried chicken at least twice in the last six months with the number of respondents being 135. The questionnaire consisted of two parts, the first part is about the consumer's purchase decision-making process and the second one is about the consumer's preference for fried chicken. Price, serving, purchase state, and packaging are the attributes chosen to identify consumer preferences using the conjoint analysis method. This study shows consumer habits in the decision-making process of buying fried chicken and consumers’ preferences toward the price, serving, purchase state, and packaging of fried chicken. Product attributes were the most considered based on importance level Price (40.73%), Purchase state (33.57%), Serving (16.99%), and Packaging (8.70%). The combination of fried chicken product attributes that are preferred by consumers according to the utility value of each level attribute is less than 15.000 IDR of price, served with rice/fried chicken and vegetables, purchased in ready-to-eat (takeaway/delivery) form and using paper box packaging.

Exercise as the sum of our choices between behavioral alternatives: The Decisional Preferences in Exercising (DPEX) test

Exercising can be theorized as the result of choosing one behavior over alternative behaviors. The Decisional Preferences in Exercising (DPEX) test is a computerized, easy-to-use, publicly available (open source Python code: https://osf.io/ahbjr/) and highly adaptive research tool based on this rationale. In the DPEX, participants are asked to choose between two images by pressing a key on the computer keyboard, one showing a physical exercise and the other showing a non-exercise behavioral alternative in a series of trials. Combinations are randomly assembled from two definable pools of stimuli trial-per-trial. The test can be scored either based on a crossed random effects model (facilitating the use of different stimulus material in different studies without compromising the comparability of test scores) or with a simple proportion score. Data from diverse study samples (N = 451) showed strong correlations of DPEX scores with past and future exercise behavior (r = 0.42 and 0.47 respectively) as well as with affective experiences with exercise (e.g., ‘pleasure-displeasure’: r = 0.47). DPEX test scores discriminated between exercisers and non-exercisers according to receiver operating curve (ROC) analysis. The DPEX may be used to examine research questions derived from dual process theories, the effects of psychological states on behavioral choices can be tested, or the effects of behavior change interventions can be evaluated. The DPEX helps to avoid common method bias in the assessment of exercise behavior, for example, when psychological variables are measured with questionnaires.

An indirect multicriteria group decision-making method with heterogeneous preference relations and reliabilities of decision-makers

This study proposes a new indirect method to solve multicriteria group decision-making (MCGDM) problems with heterogeneous preference relations and decision-makers’ reliabilities. To unify the heterogeneous preference relations, the transformation of multiplicative preference relations (MPRs), fuzzy preference relations (FPRs), intuitionistic fuzzy preference relations (IFPRs), and linguistic preference relations (LPRs) into distributed preference relations (DPRs) is analyzed. As consistency among DPRs is constructed under the assumption that decision-makers are bounded rationality, the abstract transformation of MPR, FPR, IFPR, and LPR into DPR is defined, and its reality depends on the preferences of decision-makers. Two important properties of abstract transformation, namely, internal consistency and restricted max-max transitivity, were theoretically verified. The reliabilities of decision-makers are involved in MCGDM by estimating the reliability of each criterion to improve solution quality. Based on the four types of abstract transformations, a process for analyzing MCGDM problems with heterogeneous preference relations and decision-makers’ reliabilities is developed. The proposed method is used to analyze a new business selection problem for an enterprise located in Changzhou, Jiangsu, China to demonstrate its applicability and validity.

DEA-BWM cross efficiency target setting with preferences

Due to the existence of different evaluation perspectives, target setting has always been the key in cross efficiency development and practice. However, ignoring the preference of decision makers in the process of target setting may affect the rationality of target setting, and even may make this method unable to meet the needs of actual production. This paper innovatively combines the best-worst method (BWM) with the benevolence cross efficiency (BCE) model, and proposes four new target setting approaches for individual decision-making unit (DMU) with BWM, global optimization with BWM, BWM for individual DMU and BWM for global optimization. In order to find the optimal target DMUs in the range of production possibility set, the fifth new target setting method is proposed for global optimization of target setting and controlling. On this basis, the improvement direction of target DMUs with different methods is studied, and the influence of different cross efficiency approaches on target setting are compared. Finally, the effectiveness and practicability of those approaches are illustrated by case analysis and method comparison.

Early Surgical Reconstruction Versus Rehabilitation for Patients With Anterior Cruciate Ligament Rupture: A Systematic Review and Meta-Analysis.

Anterior cruciate ligament (ACL) rupture is a common and debilitating knee injury that can significantly impair knee function and stability. The optimal management of ACL injuries remains a topic of ongoing debate, with two primary treatment approaches being surgical reconstruction and adequate rehabilitation. The aim of this study is to compare the knee function and stability outcomes between these two treatment modalities, shedding light on their respective effectiveness. We utilized Scopus, PubMed, Cochrane Database, MEDLINE, and Web of Science from inception until April 20, 2022. We utilized the Cochrane risk of bias tool for quality assessment. The following outcomes were assessed: Knee Injury and Osteoarthritis Outcome Score (KOOS), International Knee Documentation Committee (IKDC) Subjective Knee score, Lysholm score, the occurrence of the knee giving way, Tegner score, KT1000, Lachman test, pivot shift test, SF-36 score to assess the quality of life, and incidence of reinjury and reoperation. We included a total of six trials with a population sample size of 691 patients, which were divided into surgical versus non-surgical groups, accounting for 348 and 343 patients, respectively. The pooled estimate demonstrated that the surgical reconstruction was associated with a significant increase in the IKDC score (MD = 7.49 [2.04, 12.94], (P = 0.007)), and KOOS score was significant in the reconstruction cohort (MD = 5.87 [1.64, 10.09], (P = 0.007)). The incidences of reoperation (RR = 0.43 [0.20, 0.91], (P = 0.03)), reinjury (RR = 0.49 [0.27, 0.88], (P = 0.02)), and occurrence of the knee giving way (RR = 0.19 [0.08, 0.49], (P = 0.005)) were significantly decreased in the surgical cohort. There is no significant difference between both cohorts regarding the Lysholm score (1.27 [-1.39, 3.93], (P = 0.35)). The findings of this comprehensive analysis indicate that early reconstruction does not demonstrate clear superiority over rehabilitation alone in terms of knee function, Lysholm score, and Tegner score among patients with ACL rupture. However, early reconstruction does exhibit a substantial reduction in the incidence of reinjury, reoperation, and knee giving way, suggesting potential benefits in terms of stability outcomes. These results underscore the importance of considering individual patient characteristics and preferences in treatment decision-making.

A multi-objective modeling and optimization approach to municipal solid waste collection for classified treatment in China towards sustainable development

With the popularity of waste classification and increasing requirements for coordinated waste management towards sustainability, it is essential to study how to generate efficient waste collection solutions for classified treatment towards social-economic and environmental goals. We proposed a new methodological framework to identify not only the optimal routes for different collection modes in classification but also the most desirable mode under different decision preferences, by a novel multi-objective optimization model applicable to different collection modes with addressing economic, environmental and social dimensions of sustainability. We incorporated the lifecycle carbon emissions of fuel and the economic and environmental impacts of vehicle idling due to queening to make the model more realistic and comprehensive. To solve the model, we proposed a modified metaheuristic algorithm based on particle swarm optimization and genetic algorithm. Through the case study in a pilot waste classification city of China, we demonstrated the effectiveness of the designed algorithm and the applicability of the proposed methodological framework. The results indicate that there are strong synergies between environmental and economic objectives, but trade-offs between social and environmental/economic objectives. “Classification then combined-collection” should be given priority under economic and environmental preferences, while “Classification then separated-collection” should be adopted under social preference.

Understanding people’s decisions when choosing or declining a kidney transplant: a qualitative evidence synthesis

ObjectivesTo synthesise qualitative research exploring patients’ perspectives, experiences and factors influencing their decision-making preferences when choosing or declining kidney transplantation.DesignA qualitative evidence synthesis.Data sourcesElectronic databases were searched from 2000 to...

Identifying the Needs of Health Care Providers in Advanced First-Line Renal Cell Carcinoma: A Mixed-Methods Research.

Systemic treatments for metastatic or unresectable renal cell carcinoma (mRCC) are rapidly evolving. This study aimed at investigating challenges in the care of mRCC to inform future educational interventions for health care providers (HCPs). The sequential mixed-method design consisted of a qualitative phase (semistructured interviews) followed by a quantitative phase (online surveys). Participants included US-based medical oncologists, nephrologists, physician assistants, nurse practitioners, and registered nurses. Interview transcripts were thematically analyzed. Survey data was descriptively and inferentially analyzed. Forty interviews and 265 surveys were completed. Analysis revealed four challenges in the care of mRCC patients. A challenge in staying current with emerging evidence and treatment recommendations was found with 33% of surveyed HCPs reporting suboptimal skills interpreting published evidence on the efficacy and safety of emerging agents. A challenge weighing patient health and preferences in treatment decisions was found, especially among HCPs with 3 to 10 years of practice (37%) who reported suboptimal skills in assessing patients' tolerance to side effects. Promoting a collaborative care approach to the management of immune-related adverse events was a challenge, specifically related to barriers involving nephrologists (eg, diverging treatment goals). Breakdowns in communication were reported (46% of HCPs), especially in the monitoring of side effects and treatment adherence. This study revealed key challenges faced by HCPs when treating and managing patients with mRCC across multiple providers. Future interventions (eg, community of practice) should aim to address the identified gaps and promote a team-based approach to care that strengthens the complementary competencies of HCPs involved.

Gender-based discrimination and son preference in Punjabi-Canadian families: a community-based participatory qualitative research study

ObjectivesTo conduct a qualitative study, guided by the principles of community-based participatory research, with the following objectives: (1) to provide a conceptual framework describing the drivers of son preference; (2)...

A Three-Way Decision Methodology With Regret Theory via Triangular Fuzzy Numbers in Incomplete Multiscale Decision Information Systems

The three-way decision theory provides a three-way philosophical thinking to solve problems, and the regret theory quantifies the risk preferences of decision makers under different psychological behaviors. On the one hand, the combination of these two theories makes models more practical by considering the psychological behaviors of decision makers. On the other hand, we can effectively combine the advantages of the three-way decision theory with the regret theory to highlight the interpretability of decision making processes. In this paper, we propose a novel approximate estimation method for incomplete utility values via the regret theory and establish a wide sense of three-way decision model on incomplete multi-scale decision information systems. First, the degree of consistency for each scale is measured via using the dependency degree, then the optimal subsystem is selected by evaluating the scale selection cost. Further, the incomplete multi-scale evaluation information is transformed into triangular fuzzy numbers via linguistic term sets. Second, in light of fuzzy evaluation values and trade-off factors, an estimation method for incomplete fuzzy subsystems is constructed, which can be used to calculate the utility difference and regret-rejoicing values for pairwise comparisons. Finally, from the perspective of human cognition, the tri-partition and the corresponding decision rules are built by the tolerance degree, and the ranking of objects is calculated by the relative closeness degree. Additionally, multi-aspect comparative and experimental analyses are performed by extensive experiments, and the feasibility, validity and stability of the constructed model are shown by parametric analyses.

Analisa Perbandingan Metode MAUT dan Metode TOPSIS Dengan Menggunakan Pembobotan ROC Dalam Sistem Pendukung Keputusan Pemilihan Calon Kepala Desa

This study aims to carry out a comparative analysis process between the MAUT method and the TOPSIS method using ROC weighting. The MAUT method functions to deal with problems in decision making that link several interrelated attributes, in which the method combines the decision maker's preferences for the relevant attributes by giving a weight value to each attribute. Meanwhile, the TOPSIS method is used to select the best alternative from the many choices based on their relative distances from the ideal solution. In this study, weighting using the ROC method is used to objectively determine attribute weight values. The results of the research conducted show that the MAUT Method and the TOPSIS Method with ROC weighting can give good results in determining village heads. The results of the ranking using the MAUT method are A4 with a value of 0.950. while the ranking results using the TOPSIS method are A4 with a value of 0.917.

Advance Care Planning in South Africa

South Africa (SA), an upper middle-income country, faces significant challenges, including severe inequality, poverty, high unemployment rates, unequal access to basic services, and a long history of human rights violations. It is a diverse nation with eleven official languages. The country also bears a heavy burden of communicable and non-communicable diseases, with many patients seeking healthcare services too late. Despite the pressing need, palliative care is still an emerging field in South Africa, with limited funding allocated for its integration.Advance Care Planning (ACP) is a recommended practice in SA for patients with serious illnesses while they are still in good health and can function independently. Non-Governmental Organizations (NGOs) in SA have played a significant role in integrating ACP planning within their settings through advocacy and training. ACP has been included in both formal academic training and training programs offered by NGOs. Additionally, research has been initiated to evaluate the acceptability and validity of the Serious Illness Conversation Guide within the cultural diversity and complexities of the SA context.Acceptance of ACP amongst SA healthcare workers and the public faces many challenges. Many South Africans still have a low level of trust and acceptance towards the public healthcare system. In many South African cultures discussing death and dying is considered culturally taboo. Traditional cultures interpret and apply the concept of individual autonomy differently. The philosophy of “Ubuntu”, which translates to “I am because we are”, is widely endorsed in the country, prioritising community needs over individual needs. It is, therefore, essential for healthcare professionals engaging in ACP conversations not to make assumptions about a person's preferences for communication, decision-making and care, based on external attributes. Instead, they should respectfully explore these preferences and be adaptable in their approach to ACP.The implementation of ACP in SA is still in its early stages, requiring further research to inform culturally sensitive approaches to advance care planning.

Shared Decision Making in Health Care Visits for CKD: Patients’ Decisional Role Preferences and Experiences

Research on shared decision making (SDM) in chronic kidney disease (CKD) has focused almost exclusively on the modality of kidney replacement treatment. We explored what other CKD decisions are recognized by patients, what their preferences and experiences are regarding these decisions, and how decisions are made during their interactions with medical care professionals. Cross-sectional study. Patients with CKD receiving (outpatient) care in 1 of 2 Dutch hospitals. Patients' preferred decisional roles fortreatment decisions were measured using theControl Preferences Scale survey administered after a health care visit with medical professionals. Number of decisions for which patients experienced a decisional role that did or did not match their preferred role. Observed levels of SDM and motivational interviewing in audio recordings of health care visits, measured using the 4-step SDM instrument (4SDM) and Motivational Interviewing Treatment Integrity coding tools. The results were characterized using descriptive statistics, including differences in scores between the patients' experienced and preferred decisional roles. According to the survey (n=122) patients with CKD frequently reported decisions regarding planning (112 of 122), medication changes (82 of 122), or lifestyle changes (59 of 122). Of the 357 reported decisions in total, patients preferred that clinicians mostly (125 of 357) or fully (101 of 357) make the decisions. For 116 decisions, they preferred a shared decisional role. For 151 of 357 decisions, the patients' preferences did not match their experiences. Decisions were experienced as "less shared/patient-directed" (76 of 357) or "more shared/patient-directed" (75 of 357) than preferred. Observed SDM in 118 coded decisions was low (median4; range, 0 - 22). Motivational interviewing techniques were rarely used. Potential recall and selection bias, and limited generalizability. We identified multiple discrepancies between preferred, experienced, and observed SDM in health care visits for CKD. Although patients varied in their preferred decisional role, a considerable number of patients expressed a preference for shared decision making for many decisions. However, SDM behavior during the health care visits was observed infrequently. Shared decision making (SDM) may be a valuable approach for common chronic kidney disease (CKD) decisions, but our knowledge is limited. We collected patient surveys after health care visits for CKD. Patients most frequently experienced decisions regarding planning, medication, and lifestyle. Three decisional roles were preferred by comparable numbers of patients: let the clinician alone decide, let the clinician decide for the most part, or "equally share" the decision. Patients' experiences of who made the decision did not always match their preferences. In audio recordings of the health care visits, we observed low levels of SDM behavior. These findings suggest that the preference for "sharing decisions" is often unmet for a large number of patients.

Intertemporal decision-making as a mediator between personality traits and self-management in type 2 diabetes: a cross-sectional study.

The aims to investigate the mediating effect of intertemporal decision-making on the association between personality traits and self-management among individuals with in Type 2 Diabetes (T2DM). Patients with T2DM in the early stages of hospitalization at two tertiary hospitals in Shenyang and Jinzhou, Liaoning Province, May 2022 to January 2023. Questionnaires, including General Demographic, Self-Management, Big Five Personality, and Intertemporal Decision-Making, were administered. Pearson correlation analysis examined relationships between personality traits, intertemporal decision-making, and self-management. Hierarchical regression analysis identified self-management predictors. Mediation analysis used the PROCESS SPSS Macro version 3.3 model 4 to investigate intertemporal decision-making as mediator between personality traits and self-management. Pearson correlation analysis revealed significant associations between self-management scores, personality traits, and intertemporal decision-making. Hierarchical regression revealed that Neuroticism and Conscientiousness accounted for 20.8% of the variance in self-management, while intertemporal decision-making explained 4.5% of the variance. Finally, using the Bootstrap method, the mediation analysis showed that intertemporal decision-making partially mediated the effect of personality traits on self-management. This study emphasizes the importance of intertemporal decision-making in improving self-management behaviors among patients with T2DM. Interventions targeted at modifying intertemporal decision-making preferences could be effective in enhancing self-management behaviors, leading to better health outcomes.

Current status and influencing factors of participating satisfaction during surgical treatment decision-making among breast cancer patients with immediate breast reconstruction

ObjectiveBreast reconstruction (BR) is a positive contribution to aesthetic effect among breast cancer patients. Identification of influenced factors for participating satisfaction may provide insights on the decision-making theory to promote patient's autonomy in surgical choice. The purpose of this study was to examine the level of participating satisfaction with surgical treatment decision-making and its predictors among breast cancer patients with immediate BR. MethodsA cross-sectional study was conducted including 163 breast cancer patients with immediate BR in Mainland China. Data was collected using patients' participation satisfaction in medical decision-making scale (PSMDS), Big five Short-Form (BFI) Scale, Patient Participation Competence Scale(PPCS) and Patients’ Preference (MPP) scale. Descriptive, bivariate, and multivariate regression analyses were used. ResultsScores of PSMD were 86.38 ± 15.74. Multiple regression analyses indicated autonomous decision-making, marital statue, information acquisition competence, agreeableness, and decision-making preferences as indicators, explaining 29.6% of the response variation (P < 0.05). ConclusionsThe level of PSMD in breast cancer patients with immediate BR need to be improved. Patients with greater autonomous decision-making, married, higher information acquisition competence, agreeableness, and collaborative role are more likely to have an preferable PSMD. A comprehensive assessment and effective decision-making support are needed initially for BC patients to promote positive participation when making surgical decision.

Optimizing collaborative decision-making of multi-agent resources for large-scale projects: from a matching perspective

PurposeIn recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.Design/methodology/approachThe main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.FindingsNumerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.Research limitations/implicationsWhile the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.Practical implicationsCompared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.Social implicationsLarge-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.Originality/valueThe current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.

A new interval meta-goal programming for sustainable planning of agricultural water-land use nexus

Meta-Goal Programming (MGP) is a simultaneous cognitive evaluation of the degree of achievements for original decision goals considered in a GP model. However, in most real-world situations, environmental coefficients and related parameters are not easily available. In such a situation, the decision-maker must consider various conflicting targets in a framework of uncertain aspiration levels at the same time. On the other side, Interval Programming (IP) is a method used to increase the range of available decision-maker preference structures in GP. In the perspective of solving the conflicts between agriculture and water use towards sustainability, this paper proposes an Interval Meta-Goal Programming Model (IMGPM) dealing with imprecision in data that covers interval coefficients, target intervals, and interval bounds of meta-goals. This novel methodology has been tested in a study area in Iran to validate its added value in solving conflicting uses of natural resources by economic sectors. This integration together with its application for sustainable optimal cropping patterns (agroecosystem planning) represents a novelty in the field of ecological modeling. The management solutions of our method in terms of land allocation are different from those in Sen and Pal (2013) model. In the case of Iran, many socio-ecological-economic strategies and policies should be necessary for improving the agricultural sector. More specifically, on the basis of rainfall amounts and spatial patterns, this approach can represent a decision-support system able to define strategies for additional water storage useful to support crop production. Furthermore, the availability of water together with the sustainable use of fertilizers can mitigate the risk of land degradation, guaranteeing people employment, food security, and economic profits. Although the present methodology seems to solve the problem of multi-goals decision-making, the inclusion of spatial relationships is able to introduce dependencies between the management of land use in adjacent areas, making the present approach nearer to real-world functioning.