Relevant Decision Criteria Research Articles

Covergalls Incorporated

Social implications The case study will help improve systemic gender-related challenges for women in STEM, male-dominated nontraditional workplaces, such as mining, and contribute to CASE FOR WOMEN database of women-centered business teaching cases. Learning outcomes The learning objectives are as follows: discuss gender issues in nontraditional science, technology, engineering, mathematics (STEM)–related male-dominated industries; conduct a strategic competitive strengths and weaknesses, the opportunities and threats analysis and political, economic, social, technological, legal and environmental analysis; evaluate relevant information and decision criteria to assess the options; provide recommendations for strengthening vision mission and strategy; and analyze the business model using the Business Model Canvas. Case overview/Synopsis Alicia Woods (she/her), founder of Covergalls Inc., was facing an unexpected challenge during the COVID-19 worldwide pandemic restrictions and lockdowns which had created an unprecedented disruption to her business. Should Covergalls continue on its current path, or was it time to branch out? Complexity academic level This case is suitable for diversity, equality and inclusion, strategic management, entrepreneurship, marketing or leadership courses at the undergraduate BBA and graduate MBA level on campus or online. Supplementary materials Teaching notes are available for educators only. Subject code CCS 3: Entrepreneurship.

Significance of intermodal freight modal choice criteria: MCDM-based decision support models and SP-based modal shift policies

This paper reviews modal choice decisions associated with intermodal freight transportation through decision support models based on the Multi-Criteria Decision-making (MCDM) techniques and modal shift policy assessments based on the Stated Preferences (SP) experiments. The objectives were to determine the relevant decision criteria and their relative significance, to define methods in use, and to identify respective policies that boost intermodality. Google Scholar database and manual search using identified keywords were conducted and references of the relevant articles were double-checked. Consequently, a total of 27 articles consisting of respective 18 and 9 MCDM-based and SP-based articles were reviewed in this study. The results showed that the most commonly used decision criteria were cost, CO2 emissions, delivery time, safety, reliability, flexibility, and frequency. The cost factor was assigned the highest weight in 22 articles (or 81.4%). Analytical Hierarchy Process (AHP) technique was implemented in 12 out of 18 MCDM articles (or 66.6%)). Successful application of MCDM methods (both single and integrated) showed the suitability of these methods for intermodal freight modal choice decision-making. The results of SP experiments revealed that cost reduction policies are more effective than policies addressing other factors to increase the demand for intermodal transportation.

Outcome of a survey on antibiotic prescribing in veterinary medicine

As part of the national strategy on antibiotic resistance (StAR), a therapy guide for the prudent prescription of antimicrobial agents in animals was developed. To facilitate its implementation in the veterinary practice, the therapy recommendations contained therein have been translated to the user-friendly decision support AntibioticScout.ch. In this context, we conducted a non-representative survey to assess the level of awareness as well as usage of this guide and the AntibioticScout.ch decision support. Based on case studies with typical diseases in dogs, cats and cattle, it was shown that the veterinarians participating in the survey strive to handle antibiotics responsibly and to prescribe them with restraint. Nevertheless, the survey points to possible improvements in the antibiotic therapy. In particular, the StAR guidelines or AntibioticScout.ch can be useful to the practicing veterinarians for taking into account all relevant decision criteria in the optimal selection of a suitable antimicrobial agent.

How will I know about local energy projects? A conjoint-analysis of communication preferences in Germany

In an interconnected world like ours, boundaries between nations and between political, economic, and ecological challenges fade away. Within renewable energy and infrastructure projects, fields of tension evolve between global goals and local worries, and often protest arises. Communication strategies can be a way to involve citizens in project development and to build a dialogue instead of hardened fronts. However, it is unclear whether communication requirements and willingness to protest are connected and to which extent communication strategies help to create and shape a dialogue between potential protesters and other stakeholders. A conjoint approach was chosen to determine relationships between communication and protest motivation in the energy context. We compare this with mobility infrastructure and local political projects as examples, to find out whether results are unique or generalizable.Overall, we found generalizable aspects, that are the same for the energy and the example contexts. Point in time, informing person and participation were relevant decision criteria, whereas information channel was the least important independent communication criterion for all contexts. Two essential decision patterns were identified focusing either on source or on time of information. These patterns were influenced by diverse individual factors, e.g. age and protest experience.

First-line treatment of metastatic clear cell renal cell carcinoma: a decision-making analysis among experts

BackgroundThe treatment landscape of metastatic clear cell renal cell carcinoma (mccRCC) has been transformed by targeted therapies with tyrosine kinase inhibitors (TKI) and more recently by the incorporation of immune checkpoint inhibitors (ICI). Today, a spectrum of single agent TKI to TKI/ICI and ICI/ICI combinations can be considered and the choice of the best regimen is complex.Materials and methodsWe performed an updated decision-making analysis among 11 international kidney cancer experts. Each expert provided their treatment strategy and relevant decision criteria in the first line treatment of mccRCC. After the collection of all input a list of unified decision criteria was determined and compatible decision trees were created. We used a methodology based on diagnostic nodes, which allows for an automated cross-comparison of decision trees, to determine the most common treatment recommendations as well as deviations.ResultsDiverse parameters were considered relevant for treatment selection, various drugs and drug combinations were recommended by the experts. The parameters, chosen by the experts, were performance status, International Metastatic renal cell carcinoma Database Consortium (IMDC) risk group, PD-L1 status, zugzwang and contraindication to immunotherapy. The systemic therapies selected for first line treatment were sunitinib, pazopanib, tivozanib, cabozantinib, ipilimumab/nivolumab or pembrolizumab/axitinib.ConclusionA wide spectrum of treatment recommendations based on multiple decision criteria was demonstrated. Significant inter-expert variations were observed. This demonstrates how data from randomized trials are implemented differently when transferred into daily practice.

Enabling manufacturer selection and an equitable order allocation amongst textiles and apparel manufacturers

Small and medium-sized textile enterprises (SMTEs) contribute to the UK economy. Anecdotal evidence indicates that many SMTEs fail to secure enough orders from British retailers. So, this paper reports on the methodological decision analysis model and the qualitative linear weighted point method (LWPM) to develop the pertinent critical success decision criteria and virtually distribute the bulk orders equitably. The relevant decision criteria are stated for the SMTEs. The criteria are crucial as they were consolidated from the textiles and apparel manufacturers only, contrary to other several studies that established generic decision criteria. The criteria consist of corporate social responsibility, economic and environmental factors. The results indicate the opportunity to execute order quantities equitably after having ranked the collaborating SMTEs. LWPM assisted to rank SMTEs in selecting the right manufacturers. Since the criteria are from the SMTEs only; the generalisability of the results to other industries may need further research.

Integrating Sustainability Into the Machinery Selection Decisions in the Agriculture Sector

Mechanization in the agriculture sector requires well-informed technology selection decisions and a balance of financial and nonfinancial considerations. This article integrates sustainability and technical considerations into farm machinery selection decisions. Using an industry case study-where technology selection for the mechanization process is imperative-a multimethod decision-making framework is developed to select the best rice harvest machinery. For this purpose, the Delphi method is used to systematically identify the most relevant decision criteria; the analytic hierarchy process determines the criteria's importance, and the fuzzy technique for order of preference by similarity to ideal solution is applied to rank the alternatives. Given the wide variety of available harvesting technologies in the competitive market, it is shown that the sustainability criteria are receiving recent recognition among agriculture practitioners. The findings provide insights for the producers to help improve production, and exportation of the local brands in accordance with the international market needs.

Bayesian adaptive designs for multi-arm trials: an orthopaedic case study

BackgroundBayesian adaptive designs can be more efficient than traditional methods for multi-arm randomised controlled trials. The aim of this work was to demonstrate how Bayesian adaptive designs can be constructed for multi-arm phase III clinical trials and assess potential benefits that these designs offer.MethodsWe constructed several alternative Bayesian adaptive designs for the Collaborative Ankle Support Trial (CAST), which was a randomised controlled trial that compared four treatments for severe ankle sprain. These designs incorporated response adaptive randomisation (RAR), arm dropping, and early stopping for efficacy or futility. We studied the operating characteristics of the Bayesian designs via simulation. We then virtually re-executed the trial by implementing the Bayesian adaptive designs using patient data sampled from the CAST study to demonstrate the practical applicability of the designs.ResultsWe constructed five Bayesian adaptive designs, each of which had high power and recruited fewer patients on average than the original designs target sample size. The virtual executions showed that most of the Bayesian designs would have led to trials that declared superiority of one of the interventions over the control. Bayesian adaptive designs with RAR or arm dropping were more likely to allocate patients to better performing arms at each interim analysis. Similar estimates and conclusions were obtained from the Bayesian adaptive designs as from the original trial.ConclusionsUsing CAST as an example, this case study shows how Bayesian adaptive designs can be constructed for phase III multi-arm trials using clinically relevant decision criteria. These designs demonstrated that they can potentially generate earlier results and allocate more patients to better performing arms. We recommend the wider use of Bayesian adaptive approaches in phase III clinical trials.Trial registrationCAST study registration ISRCTN, ISRCTN37807450. Retrospectively registered on 25 April 2003.

Multi-Criteria Decision Analysis (MCDA) Models in Health Technology Assessment of Orphan Drugs-a Systematic Literature Review. Next Steps in Methodology Development?

Background: Multi-criteria decision analysis (MCDA) is a decision-making tool that can take into account multidimensional factors and enables comparison of (medical) technologies by combining individual criteria into one overall appraisal. The MCDA approach has slowly gained traction within Health Technology Assessment (HTA) and its elements are gradually being incorporated into HTA across Europe. Several groups of scientists have proposed MCDA approaches targeted toward orphan drugs and rare diseases by including criteria specific to rare diseases. The goal of this article is to provide an overview of the current state of knowledge and latest developments in the field of MCDA in HTA for orphan drugs, to review existing models, their design characteristics, as well as to identify opportunities for further model improvement.Methods: A systematic literature search was conducted in January 2018 using four databases: MEDLINE (Pubmed), EBSCO HOST, EMBASE, and Web of science to find publications related to use of MCDA in the rare disease field (keywords: MCDA/orphan drug/rare disease and synonyms). Identified MCDA models were analyzed, e.g., structure, criteria, scoring, and weighting methodology.Results: Two hundred and eleven publications were identified, of which 29 were included after removal of duplicates. 9 authors developed own MCDA models, 7 of which based on literature reviews intended to identify the most important and relevant decision criteria in the model. In 13 publications (8 models) weights were assigned to criteria based on stakeholder input. The most commonly chosen criteria for creation of the MCDA models were: comparative effectiveness/efficacy, the need for intervention, and disease severity. Some models have overlapping criteria, especially in the treatment cost and effectiveness areas.Conclusions: A range of MCDA models for HTA have been developed, each with a slightly different approach, focus, and complexity, including several that specifically target rare diseases and orphan drug appraisal. Models have slowly progressed over the years based on pilots, stakeholder input, sharing experiences and scientific publications. However, full consensus on model structure, criteria selection and weighting is still lacking. A simplification of the MCDA model approach may increase its acceptance. A multi-stakeholder discussion on fundamental design and implementation strategies for MCDA models would be beneficial to this end.

Cloud computing technology selection based on interval-valued intuitionistic fuzzy MCDM methods

Cloud computing technology (CCT) can bring considerable advantages to businesses and people by taking over many time-wasting technicalities, such as establishing communications infrastructure, thus adding value. CCT is revolutionizing every industry by allowing all types of organizations to buy a service instead of owning with flexible rates. An objective of this study is to identify a set of relevant decision criteria and their subcriteria needed in the evaluation of the CCT provider selection (PS) problem. Another objective is to provide a powerful integrated framework that can be used for the evaluation and selection of the most appropriate CCT provider and then to apply this proposed approach in a real case study. CCT PS is a complex multi-criteria decision problem that involves a number of qualitative and quantitative parameters that might be conflicting, or even ambiguous. Interval-valued intuitionistic fuzzy (IVIF) set is an effective concept that is used to cope with uncertainty by taking both the degree of membership and non-membership functions in an interval. Therefore, this paper proposes a state-of-the-art novel methodology consisting of IVIF analytic hierarchy process, IVIF complex proportional assessment, IVIF multi-objective optimization by ratio analysis plus the full multiplicative form, IVIF technique for order of preference by similarity to ideal solution and IVIF visekriterijumsko kompromisno rangiranje methods. This combination aims to rank available CCT PS alternatives in the presence of imprecise and vague information.

Value-based medicine in oncology: the importance of perspective in the emerging value frameworks

Recently, professional and healthcare-related entities have launched frameworks designed to assess the value of cancer innovations in multistakeholder decision processes. Among the most visible entities that propose and implement value frameworks in oncology are the European Society of Medical Oncology (ESMO), the American Society of Clinical Oncology (ASCO), the Memorial Sloan Kettering Cancer Center (MSKCC) and the National Comprehensive Cancer Network (NCCN). However, these value frameworks have been criticized for conceptual inconsistencies, inability to include a greater variety of value criteria, and inadequate explanation of the uncertainty approach used in the modeling process. On the other hand, Multi-Criteria Decision Analysis (MCDA) is a set of methods and processes that allow the multiple criteria involved in a decision to be explicitly addressed. This approach allows the identification of relevant decision criteria, gathering of evidence based on scientific literature, attribution of weights to the criteria and scores to the evidence raised, and aggregation of the weighted scores to constitute a global metric of value. The purpose of this article is to review the main features of these value frameworks in oncology and the importance of perspective for framework readiness to support healthcare decision-making based on MCDA methodology.

Expanding knowledge on environmental impacts of transport processes for more sustainable supply chain decisions: A case study using life cycle assessment

With this study, we highlight the necessity to improve the environmental performance in supply chains and freight transportation systems to respond to the unbroken trend of increasing environmental impacts of transport. Based on a literature review, we first identify 19 environmentally relevant decision criteria which determine transport processes, such as delivery times, delivery frequency, or mode choice. We group these criteria depending on the time horizon and their influenceability by a company decision-maker and further apply them to empirically enquire in a life cycle assessment case study about the relationship between freight transport processes and the related environmental impacts. The case example of a resource intense and heavy-weight product represents a typical product system with long transport distances and economic as well as environmental relevance. By means of some robustness tests we further show how some criteria which are controllable and influenceable in the short and medium term trigger the indicator results. Finally, we develop a decision tree approach to prioritize actions and derive environmental transport strategies depending on the time horizon and the influenceability of the decision criteria. While the decision tree is from a manufacturing company’s perspective, it has relevance also for other actors along the supply chain and in politics. With this literature review, case study, and decision-tree approach we contribute to transportation research and practice and thereby aim to incentivize decision-makers to systematically explore the sources of environmental impacts and continuously improve the environmental performance of freight activity.

PGI22 - PATIENTS’ PREFERENCES IN FUNCTIONAL DYSPEPSIA AND MOTILITY DISORDER: A DISCRETE-CHOICE EXPERIMENT

Functional gastrointestinal disorder is common worldwide and a healthcare burden for many individuals. Functional dyspepsia and motility disorder can be extremely disabling. The aim of this study was to identify and weight the patient’s relevant decision criteria with regard to drug treatment of functional dyspepsia and motility disorders. Treatment characteristics such as the type of drug, onset of action, reduction of symptoms and side effects were to be examined in order to evaluate the patient preferences. The literature review and nine qualitative interviews revealed eight patient-relevant treatment attributes. A discrete choice experiment (DCE) was used to rank the identified treatment characteristics. The DCE was conducted using a fractional-factorial-design (Ngene) and the statistical data analysis used random effect logit and latent class models for subgroup identification. In total N=1096 patients with functional dyspepsia or motility disorder participated in the computer-assisted personal interviews. The estimation revealed a clear dominance for a reduction of “stomach cramps” (coef.:3,01) and “epigastric pain” (coef.:2.98), followed by the reduction of “acid reflux/indigestion” (coef.:2.06), “time to onset of action” (coef.:1.57) and reduction of “feeling of fullness” (coef.:1.46). The side effects “diarrhea” (coef.:1.20) and “headache” (coef.:1.05) as well as the “type of drug” was less important for participants (coef.:0.17). The reduction of symptoms like cramps and pain were identified as key patient-relevant characteristics. The sole consideration of these criteria is not sufficient from the patients’ perspective as multiple criteria are important. Subgroup analysis revealed that there are two population groups showing different preferences for the evaluated treatment characteristics. For one sub-sample the onset of action and side effects of a treatment are more important than a reduction of symptoms. The results inform decision makers on how much a decision criteria affects the potential treatment decision from a patient’s perspective.

The Expert Perspective in Treatment of Functional Gastrointestinal Conditions: A Multi‐Criteria Decision Analysis Using AHP and BWS

AbstractObjectivesThe aim of this study was to identify and weight the expert's relevant decision criteria with regard to drug treatment of functional dyspepsia and motility disorders. Attributes such as onset of action, reduction of symptoms and side effects were to be examined in order to test their relevance to healthcare decision makers. Moreover, the objective was to verify the extent to which the analytic hierarchy process (AHP) and best–worst scaling (BWS) are suitable for use in context of an expert panel.MethodIn order to identify patient‐relevant therapy characteristics, a literature search and qualitative interviews were conducted. On this basis, a questionnaire was developed using multi‐criteria decision analysis. By means of the AHP and BWS, the study elicited the experts' priorities as regards the various aspects of treatments and gastrointestinal symptoms. The data collection from experts in gastroenterology was performed in real time within a group discussion using an item‐response system.ResultsAs a result of the interviews, seven characteristics and 10 symptoms were established. A total of N = 20 experts took part in the survey. The following criteria were shown to be the most relevant in the AHP: ‘reduction of abdominal cramps’ (w: 0.302), ‘reduction of epigastric pain’ (w: 0.250) and ‘time to onset of action’ (w: 0.117). In the BWS, it was shown that the gastrointestinal symptoms ‘vomiting’ (sqrt(b/w): 0.118), ‘abdominal cramps’ (sqrt(b/w): 0.157) and ‘epigastric pain’ (sqrt(b/w): 0.356) were the most significant.DiscussionThe methods represent a suitable and scientifically transparent approach for the elicitation of experts' priorities. Using AHP, it was possible to ascertain the most important aspects of drug treatment and to correlate positive and negative characteristics. The BWS showed which gastrointestinal symptoms had the least and most pronounced negative impact on patient well‐being from expert perspective. The item‐response system served as a valuable instrument to collect data based on a group discussion. Copyright © 2016 John Wiley & Sons, Ltd.

A New Decision Support System for Supplier Selection using Boolean Algebra

For organizations operating with number of products/services and number of suppliers, to select the right supplier meeting all their requirements will be a challenging job. Such organizations need a good decision support system to evaluate the suppliers effectively. Several decision support systems have been reported to deal with complex selection process to decide the right supplier. Many mathematical models have also been developed. This paper presents a new method, named as Bit Decision Making (BDM) method, which treats such complex system of decision making as a collection and sequence of reasonable number of meaningful and manageable sub-systems by identifying and processing the relevant decision criteria in each sub-system. Help of Boolean logic and Boolean algebra is taken to assign binary digit values to the selection criteria and generate mathematical equations that correlate the inputs to the output at each stage of decision making. Each sub-system with its own mathematical model has been treated as a standardized decision sub-system for that phase of making decision in evaluating suppliers. The sequence and connectivity of the sub-systems along with their outputs finally lead to selection of the best supplier. A real-world case of evaluation of information technology (IT) tenders has been dealt with for application of the proposed method. The paper discusses in detail the theory, methodology, application and features of the new method.

Interactive Socially Responsible Portfolio Selection: An Application to the Spanish Stock Market

During the late years, given the causes of the 2008 financial crisis, ethical, social, environmental and governance concerns have become relevant investment decision criteria for both individual and institutional investors. However, while a diverse set of models has been developed to support investment decision-making based on financial criteria, models including also socially responsible criteria are rather scarce. The model proposed in this paper is intended to be an individual investment decision making tool for stocks‘ portfolio selection, taking into account the subjective and individual preferences about different financial and socially responsible features of a particular investor. In this sense, the first problem to be solved is the measurement of the social responsibility degree of financial assets. In this work, we propose the construction of synthetic indicators based on the double reference point scheme. Once the social responsibility degree of the assets has been measured, multiple criteria portfolio selection model is formulated, which includes, together with the classical financial criteria, a social responsibility criterion based on the previously obtained synthetic indicators. The resulting model is solved using a mixed reference point – classification scheme. In order to illustrate the suitability of the synthetic indicators built, and the applicability of the proposed investment decision making model, an empirical study on a set of Spanish domiciled stocks is presented.

Making the right decisions about new technologies

Decision makers in hospitals are regularly faced with choices about the adoption of new technologies. Wrong decisions lead to a waste of resources and can have serious effects on the patients' and hospital's well-being. The goal of this research was to contribute to the understanding of decision making in hospitals. This study produced insights regarding relevant decision criteria and explored their specific relevance. An initial empirical survey was used to collect the relevant criteria for technological decision making in hospitals. In total, 220 experts in the field of health technology assessment from 34 countries participated in the survey. As a second step, the abovementioned criteria were used to form the basis of an analytic hierarchy process model. A group of 115 physicians, medical technical assistants, and other staff, all of whom worked in the field of radiooncology, prioritized the criteria. An analysis of variance was performed to explore differences among groups in terms of institutional and personal categorization variables. The first part of the research revealed seven key criteria for technological decision making in hospitals. The analytic hierarchy process model revealed that organizational impact was the most important criterion, followed by budget impact. The analysis of variance indicated that there were differences in the perceptions of the importance of the identified criteria. This exploration of the criteria for technological decision making in hospitals will help decision makers consider all of the relevant aspects, leading to more structured and rational decisions. For the optimal resource allocation, all of the relevant stakeholder perspectives and local issues must be considered appropriately.

A New Decision Support System for Supplier Selection Using Boolean Algebra

For organizations operating with number of products/services and number of suppliers, to select the right supplier meeting all their requirements will be a challenging job. Such organizations need a good decision support system to evaluate the suppliers effectively. Several decision support systems have been reported to deal with complex selection process to decide the right supplier. Many mathematical models have also been developed. This paper presents a new method, named as Bit Decision Making (BDM) method, which treats such complex system of decision making as a collection and sequence of reasonable number of meaningful and manageable sub-systems by identifying and processing the relevant decision criteria in each sub-system. Help of Boolean logic and Boolean algebra is taken to assign binary digit values to the selection criteria and generate mathematical equations that correlate the inputs to the output at each stage of decision making. Each sub-system with its own mathematical model has been treated as a standardized decision sub-system for that phase of making decision in evaluating suppliers. The sequence and connectivity of the sub-systems along with their outputs finally lead to selection of the best supplier. A real-world case of evaluation of information technology (IT) tenders has been dealt with for application of the proposed method. The paper discusses in detail the theory, methodology, application and features of the new method.

Development of a Tool to Identify Patients' Preference for Vitamin K Antagonist or Direct Oral Anticoagulant Therapy

Direct oral anticoagulants (DOACs) were developed for the treatment of thromboembolic diseases to overcome limitations of vitamin K antagonists (VKA). International guidelines on atrial fibrillation acknowledge patients' for antiembolic therapy with VKA or DOAC as relevant decision criteria. The objective assessment of patients' preference social interactions and psychological factors are hard to measure albeit representing important contributors. After a series of structured interviews and pilot studies assessing the preparedness to use DOAC as an anticoagulant and the motivation of patients to participate in clinical studies with DOAC, seven items were identified from several questionnaires by regression analysis. Those items were seen the best to describe the willingness to change anticoagulation from VKA to DOAC. By their use, we aim to develop a tool for the objective identification of the patients' preferences for VKA or for DOAC to increase adherence to therapy and to reduce anticoagulant undertreatment. German-speaking patients were asked to fill out a questionnaire consisting of biographic data and the seven selected items, and 180 patients completed the questionnaire so far. Of these, 90 patients were on treatment with VKA (group 1), 57 patients changed anticoagulation from VKA to DOAC (group 2), 29 patients were DOAC naive patients (group 3), and 4 patients changed from DOAC to VKA (group 4). Overall, 94 patients received VKA, 29 patients received dabigatran, 50 patients received rivaroxaban, and 7 patients received apixaban as an anticoagulant. Eight patients were younger than 40 years, 35 patients were aged between 40 and 59 years, 53 patients were aged between 60 and 70 years, and 84 patients were aged older than 70 years. Indication for anticoagulation were atrial fibrillation (n = 106), pulmonary embolism (n = 24), deep vein thrombosis (n = 40), artificial heart valve replacement (n = 8), or other diseases (n = 2). Based on the results of the analysis, a score will be suggested to identify the preference of patients for anticoagulation with VKA or DOAC. This tool may be useful for practitioners and health-care professionals to support patient adherence to therapy, and thereby increase treatment effectiveness.

Synthetic indicators of mutual funds’ environmental responsibility: An application of the Reference Point Method

Socially Responsible Investing (SRI) is broadly defined as an investment process that integrates not only financial but also social, environmental, and ethical (SEE) considerations into investment decision making. SRI has grown rapidly around the world in the last decades. In the last years, given the causes of the 2008 financial crisis, ethical, social, environmental and governance concerns have become even more relevant investment decision criteria. However, while a diverse set of models have been developed to support investment decision-making based on financial criteria, models including also social responsibility criteria are rather scarce.The aim of this paper, in which we focus on the environmental dimension, is to assist individual investors in their investment decisions providing them with a synthetic indicator of mutual funds’ environmental responsibility, which is by nature a multicriteria concept and therefore multicriteria techniques are to be used to measure it.The proposed approach is based on the double (reservation–aspiration) Reference Point Method. This scheme is applied to each fund of a randomly selected set of U.S. equity mutual funds, in order to determine, on the basis of a given set of indicators, a pair of synthetic indicators that measure the weak and the strong environmental responsibility degree of each mutual fund, relying on the particular preferences of the investor.