Information For Decision-making Research Articles

8.B. Scientific session: Strengthening health information systems in the European Region

Abstract Strong health information systems (HIS) are essential for robust, evidence-informed policymaking and decision making in all levels of healthcare. The COVID-19 pandemic underscored the vital importance of HIS, but also highlighted flaws and weaknesses across HIS in Europe. Common HIS challenges include limited resources and capacity; insufficient coordination and collaboration between HIS stakeholders, leading to fragmentation and problems with interoperability; lack of central governance; and limited use of health information for decision-making. Both at the level of the WHO Regional Office for Europe (WHO/Europe) and the European Commission, policies and strategies are being implemented to support Member States in strengthening their HIS, thereby improving the availability of high quality, timely data for evidence-informed decision making, both at the country and international level. Supporting the further digitalization of HIS is an important element in this. In 2023, WHO/Europe and the European Commission joined forces in the field of HIS strengthening. This workshop will inform participants about current and future capacity building tools and activities that will be implemented under the umbrella of the EU-funded action ‘Supporting Member States in the WHO European Region in strengthening HIS and boosting health data governance and interoperability’. It will explain the policy as well as situation-on-the-ground contexts in which the action will be implemented. The workshop will start with a (1) presentation by WHO/Europe on the current HIS situation in the Region and what are the main priority areas in WHO’s work for the coming years. After that, (2) the European Commission will give more information on the above-mentioned EU-funded action and the related EU policy landscape, most notably the European Health Data Space (EHDS). Next, (3) WHO/Europe will present their catalogue of capacity building tools and activities, and share experiences with implementing these. Finally, (4) HIS modernization cases with enabling factors and challenges will be presented based on different countries’ real life experiences, illustrating the impact of HIS strengthening activities at the country level. Workshop participants will get a comprehensive overview of available HIS strengthening tools and activities in the European Region. This will help them in selecting and applying tools for strengthening their own national or regional HIS, and ensuring their HIS is prepared for aligning with the EHDS and other important policies and strategies. This will contribute to sustainable and future-proof HIS across Europe. During the workshop, there will be ample time for questions and discussion. In the discussion, participants will be asked whether they have any HIS strengthening needs that are not yet covered in the current package of tools and activities. This will help WHO and the European Commission to further harmonise their efforts with what is needed on the ground. Key messages • Despite investments in HIS following the COVID-19 pandemic, many challenges remain, which are often similar across European countries. • WHO/Europe and the European Commission have joined forces to strengthen HIS and boost health data governance and interoperability, while leveraging EHDS developments.

Analysis of Enterprise Internet of Things Maturity Models: A Review

Maturity models are valuable tools when assessing the readiness and progress of technology incorporation in organizations, providing information for decision-making, resource allocation, and competitive advantage. The Internet of Things is a technology paradigm of global importance, especially for organizations, as it supports productivity improvements, real-time analysis, and customer satisfaction. Therefore, adopting and implementing this technology in enterprises brings several challenges, such as technological, organizational, security, and maturity issues. However, secondary studies that systematically compile the existing literature on these specific mechanisms for the enterprise domain are still being determined. This article aims to address this knowledge gap by conducting a review to deepen and synthesize the existing knowledge. This research followed established methodologies and protocols to synthesize and analyze the state of the art in the area; 489 documents were retrieved from seven bibliographic databases, and, applying inclusion and exclusion criteria, 36 primary studies were selected. The results indicate that the typical structures of maturity models incorporate technological, organizational, human, performance, and security dimensions through graded levels that denote the sophistication of the Internet of Things. Measurement techniques and metrics vary from model to model. There are few empirical validations or standardized improvement frameworks. The main conclusion is that there is a diversity of models, dimensions, indicators, and methods and a need for more comprehensive, adaptable, and user-friendly tools to help companies assess their Internet of Things maturity and inform future development strategies.

Sensitive personal health information, public trust, and biases in algorithmic decision-making: public health concerns in digital wellness.

Sensitive personal health information, public trust, and biases in algorithmic decision-making: public health concerns in digital wellness.

Investing in green, sustaining the planet: The role of fintech in promoting corporate green investment in the Chinese energy industry

In recent years, fintech has rapidly developed on a global scale, bringing about significant transformations across various industries. Particularly in the energy sector, the potential of fintech to promote corporate green investment has increasingly become a focus. As the energy industry accounts for a significant proportion of global greenhouse gas emissions, guiding companies in implementing green investment has become an important issue for environmental protection and sustainable development. However, previous studies have rarely systematically investigated the influence of fintech on corporate green investment in the energy industry and the mechanisms involved. Hence, this study aims to bridge this research gap within the context of China. By utilizing valid survey data from 466 corporations in the Chinese energy industry and the method of structural equation modeling, the results indicate that: (1) Fintech can promote corporate green investment in the energy industry. (2) Fintech can promote corporate data-driven decision-making capability, information transparency, and sustainable development strategy. (3) Data-driven decision-making capability, information transparency, and sustainable development strategy can also promote corporate green investment in the energy industry. (4) Mediation analysis reveals that data-driven decision-making capability, information transparency, and sustainable development strategy each play a mediating role in the impact of fintech on corporate green investment. (5) Comparative analysis of the mediation effects indicates that there is a certain degree of difference among these three variables’ mediating effects, but it did not reach a statistically significant level. This study provides rich insights for business practices, encouraging companies to strengthen their focus on green investment in the fintech era and offer guidance and recommendations to relevant stakeholders, thereby providing practical guidance for corporate green transformation and sustainable development. Finally, this research also contributes to policy development and optimization.

Prior cocaine use diminishes encoding of latent information by orbitofrontal, but not medial, prefrontal ensembles.

Maladaptive decision-making is a hallmark of substance use disorders (SUDs), though how drugs of abuse alter neural representations supporting adaptive behavior remains poorly understood. Past studies show that the orbitofrontal (OFC) and prelimbic (PL) cortices are important for decision-making, tracking both task-relevant and latent information. However, previous studies have focused on how drugs of abuse impact the firing rates of individual units. More work at the ensemble level is necessary to accurately characterize potential drug-induced changes. Using single-unit recordings in rats during a multidimensional decision-making task and then applying population- and ensemble-level analyses, we show that prior use of cocaine altered the strength and structure of task-relevant and latent representations in the OFC, changes relatable to suboptimal decision-making in this and perhaps other settings. These data expand our understanding of the neuropathological underpinnings of maladaptive decision-making in SUDs, potentially enabling enhanced future treatment strategies.

Effect of Management Information System on Growth of Agro-Firms in Anambra State

The study examined the effect of management information systems on the growth of agro-firms in Anambra State. The objectives were to: determine the effect of decision-making information systems on the Return on Investment (ROI) of agro-businesses in Anambra State, Nigeria, and ascertain the extent to which database management systems affect the ROI of agro-businesses in Anambra State, Nigeria. The study adopted a survey research design, with data generated from both primary and secondary sources. The data collection method was a questionnaire, which was randomly administered to staff of selected agro-firms. The population of the study was 6,727, while the sample size was 1,293, out of which 929 questionnaires were retrieved. The hypotheses were tested using the multiple regression analysis method at a 0.05% level of significance. The findings revealed that decision-making information systems had a significant effect on the ROI of agro-businesses in Anambra State, with a t-statistic of 7.743 and a probability value of 0.000. Additionally, database information systems had a significant effect on the ROI of agro-businesses in Anambra State, with a t-statistic of 2.476 and a probability value of 0.013. The study concluded that management information systems have a significant positive effect on agro-firms in Anambra State. It recommended that agricultural firms should invest in advanced decision support tools to aid data-driven decisions that maximize ROI. Furthermore, agro-business managers should focus on optimizing their database information systems to improve data organization and accessibility. Regular maintenance and updates of the database systems are crucial for ensuring accurate and timely information, which can positively impact ROI.

Treatment preferences in spinal muscular atrophy: A swing weighting study for caregivers of patients with SMA types 1 and 2.

Spinal muscular atrophy (SMA) is a genetic neuromuscular disorder characterized by skeletal muscle weakness and atrophy. Patients with SMA types 1 and 2 develop severe disabilities conferring substantial patient and caregiver burden. Caregiver treatment characteristic preferences are useful for informing treatment choices and improving adherence. We aimed to identify drivers of SMA treatment preference from the perspective of caregivers of patients with SMA types 1 or 2 in the United States. We quantified the relative importance of different treatment characteristics and compared preferences for hypothetical treatment scenarios. Treatment attributes and attribute levels elicited were based on a literature search and interviews with caregivers and health care professionals. The most important treatment characteristics from the perspective of health care professionals and caregivers were identified and used in a survey to quantify relative importance for caregivers. Caregivers completed surveys regarding their preferences using swing weighting methodology. These results were used to estimate the relative value of four hypothetical SMA treatment scenarios exploring different modes of treatment administration. The swing weighting survey, completed by 20 caregivers, demonstrated that the attributes driving treatment preference were reduction in permanent ventilation needs and risk of severe adverse events, followed by treatment access (including cost coverage and availability), increased ability to sit without support, and less treatment administration burden. The hypothetical SMA treatment scenarios with the highest relative value offered an easier mode of administration, lowest risk of severe adverse events, less need of permanent ventilation, and highest ability of patients to feed and sit without support. Our findings suggest that caregivers prefer a treatment with reduced clinical burden and risk in which the cost is covered and treatment is available in the short term. These results can provide important contextual information for decision-makers and help promote patient-centered care for patients with SMA.

Guidance for unbiased predictive information for healthcare decision-making and equity (GUIDE): considerations when race may be a prognostic factor.

Clinical prediction models (CPMs) are tools that compute the risk of an outcome given a set of patient characteristics and are routinely used to inform patients, guide treatment decision-making, and resource allocation. Although much hope has been placed on CPMs to mitigate human biases, CPMs may potentially contribute to racial disparities in decision-making and resource allocation. While some policymakers, professional organizations, and scholars have called for eliminating race as a variable from CPMs, others raise concerns that excluding race may exacerbate healthcare disparities and this controversy remains unresolved. The Guidance for Unbiased predictive Information for healthcare Decision-making and Equity (GUIDE) provides expert guidelines for model developers and health system administrators on the transparent use of race in CPMs and mitigation of algorithmic bias across contexts developed through a 5-round, modified Delphi process from a diverse 14-person technical expert panel (TEP). Deliberations affirmed that race is a social construct and that the goals of prediction are distinct from those of causal inference, and emphasized: the importance of decisional context (e.g., shared decision-making versus healthcare rationing); the conflicting nature of different anti-discrimination principles (e.g., anticlassification versus antisubordination principles); and the importance of identifying and balancing trade-offs in achieving equity-related goals with race-aware versus race-unaware CPMs for conditions where racial identity is prognostically informative. The GUIDE, comprising 31 key items in the development and use of CPMs in healthcare, outlines foundational principles, distinguishes between bias and fairness, and offers guidance for examining subgroup invalidity and using race as a variable in CPMs. This GUIDE presents a living document that supports appraisal and reporting of bias in CPMs to support best practice in CPM development and use.

Involving citizens in monitoring the Kunming–Montreal Global Biodiversity Framework

AbstractThe Kunming–Montreal Global Biodiversity Framework (GBF) and its monitoring framework aims to reverse the decline of nature. The GBF tasks governments to report progress towards 23 targets and four goals but also “invites Parties and relevant organizations to support community-based monitoring and information systems and citizen science” to improve information for decision-making and build support for conservation efforts throughout society. We assessed how Indigenous Peoples, local communities and citizen scientists and professional scientists can help monitor the GBF. Of the 365 indicators of the GBF monitoring framework, 110 (30%) can involve Indigenous Peoples, local communities and citizen scientists in community-based monitoring programmes, 185 (51%) could benefit from citizen involvement in data collection and 180 (49%) require scientists and governmental statistical organizations. A smaller proportion of indicators for GBF targets are amenable to citizen monitoring than for the previous Aichi targets or other multilateral environment agreements—largely because 196 GBF indicators are analytically complex (54%) and 175 require legislative overview (48%). Greater involvement of citizens in the GBF would increase societal engagement in international agreements, harness knowledge from those living close to nature to fill data gaps and enhance local to national decision-making based on improved information, leading to better conservation actions.

The hidden burden of atopic dermatitis in central and Eastern European countries

ABSTRACT Background Atopic dermatitis (AD) imposes a hidden burden through its negative effects on quality of life and productivity. We aim to estimate this hidden burden in adults and adolescents in Central and Eastern European (CEE) countries. Methods We created a burden of disease model to quantify AD’s hidden burden. Humanistic burden was calculated by estimating the monetary value of quality-adjusted life years (QALYs) lost, using prevalence data from the Global Burden of Disease study and gross domestic product (GDP) per capita for each country. Indirect economic burden was estimated based on productivity loss from absenteeism and presenteeism, adjusted for labor force participation and unemployment rates. Total hidden burden was determined by combining productivity losses and QALYs lost. Results QALY loss due to AD ranged from 1,832 to 58,596 annually in CEE countries, equating to 38 million to approximately 1 billion Euros per country. Productivity losses ranged from 3.6 to 148.9 million Euros annually. The total hidden burden of AD represents 0.11% to 0.43% of the GDP. Conclusions Our estimates reflect significant differences in population size, prevalence, and economic strength among CEE countries. Adjusting findings to country-specific GDP provided insights into AD’s true hidden burden, offering valuable information for decision-making.

Systolic anterior motion mediated mitral regurgitation and surgical management in hypertrophic obstructive cardiomyopathy.

Mitral regurgitation (MR) mediated by systolic anterior motion (SAM) is a typical manifestation in patients with hypertrophic obstructive cardiomyopathy (HOCM). Although septal myectomy (SM) is currently the preferred treatment for patients with drug-refractory HOCM. Surgical management of associated MR remains controversial. Whether SM alone or additional valve procedures are required to correct significant MR depends largely on each individual pathophysiology. For intervention purposes, it is important to identify the real SAM-mediated MR and clarify the mitral structural abnormalities, as well as the other conditions, which may alert mitral valve (MV) competence. As a first-line imaging modality in the management of hypertrophic cardiomyopathy, echocardiography could provide crucial information for surgical decision-making. In this article, we focus on elucidating the typical echocardiographic features of SAM-mediated MR and offer the assessment process to determine other contributors to obstruction and MR. Additionally, guidance for surgical decision-making for MR in HOCM patients is been discussed.

Efetividade e segurança do uso do ar ambiente em comparação ao oxigênio a 100% em prematuros em parada cardiorrespiratória: protocolo de revisão sistemática

Introduction: Cardiorespiratory arrest is a clinical situation characterized by the interruption of blood circulation. It is estimated that 11.1% of all live births in the world are premature, generating short and long-term repercussions. One of the main challenges during cardiacarrest in premature infants is providing sufficient, but not excessive, oxygen during assisted ventilation. Objective: To compare the effectiveness and safety of using room air in relation to 100% oxygen in the resuscitation of premature infants in cardiorespiratory arrest. Methods: To this end, we will carry out a systematic review of randomized clinical trials (RCTs). The study protocol was registered on the Prospero Platform (CRD42024519724). We will include preterm infants with gestational age <37 weeks with CA. The searches were carried out in the following databases: Medical Literature Analysis and Retrieval System Online (MEDLINE) via Pubmed, Excerpta Médica dataBASE (Embase) via Elsevier, Cochrane Central Register of Controlled Trials (CENTRAL) via Cochrane Library, Latin American Literature and the Caribbean Doctor in Health Sciences (LILACS) through the Virtual Health Library Portal, without restrictions on language or year of publication. The selection of studies, transmission of data, assessment of the bias of included studies and assessment of the certainty of the evidence will be carried out by two independent investigators. Expected results: Clarify the transit and safety of using room air compared to 100% oxygen, provide useful information for clinical decision-making, and support future high-quality randomized clinical trials on the topic. Conclusion: This study aims to compile existing research to analyze the effectiveness and safety of application of 100% oxygen in the resuscitation of premature infants. Keywords: Heart arrest; infant premature; systematic review.

Experiences and Perceptions of Medication Management Communication During Transitions of Care for Residents in Aged Care Homes and Their Caregivers: A Qualitative Meta-Synthesis.

To explore the experiences and perceptions of communication about managing medication across transitions of care for residents living in aged care homes and their family caregivers. Effective medication communication across transitions of care involves exchanging information, resident, and family caregiver's participation in decision-making, and shared responsibility. A qualitative meta-synthesis. This review was conducted in accordance with the PRISMA 2020 guidelines and the accompanying 27-item checklist. A systematic search of seven electronic databases (Embase, PsycINFO, Medline Ovid, Scopus, CINAHL, EmCare and Web of Science) was performed from inception to December 2023. Studies eligible for inclusion in this review were required to be published in peer-reviewed English journals and focus on medication communication among healthcare providers, residents and family caregivers during transitions of care for aged care residents. The JBI Critical Appraisal Checklist for Qualitative Research was employed for the critical appraisal of the studies, and the COREQ checklist was used to evaluate their quality. Of the 2610 studies identified, 12 met the inclusion criteria. No study was excluded based on quality. Two main themes were generated: (1) Medication information exchange involving residents and families, and (2) resident and family factors influencing medication communication engagement. The findings revealed a lack of supportive structure for effective communication and collaboration among residents, family caregivers and healthcare providers during transitions of care, marked by one-way interactions and limited evidence of shared decision-making or family caregiver engagement in medication management communication, despite varying individual needs and preferences. Communication about medication management during transitions of care focused on sharing details rather than active engagement. Residents and their family caregivers have individual needs and perspectives regarding communication about medication management, which are not well addressed by healthcare providers during transitions of care. Healthcare providers' communication remains limited, and family caregivers are underutilised.

RESEARCH METHODS AND GEOINFORMATION MODELS OF CHANGES IN LAND RESOURCES OF ALMATY REGION UNDER THE INFLUENCE OF HOUSEHOLD WASTE

This article deals with the solution of scientific problems, including the development of holistic conceptual models for presenting, processing and analyzing geographic information, and comprehensively assesses the extent of the impact of regional systems on many dangerous natural and artificial processes. This makes it possible to resolve the contradiction between the need to analyze the state of various territorial systems in order to prevent the occurrence of emergencies due to the influence of natural and man-made processes.On the one hand, providing information and support in decision-making, and on the other, ensuring the provision of cartographic models of transport systems risk assessment of dangerous natural and man-made processes and their mapping. Integrated environmental assessment and modeling of industrial systems. A method for mapping payment systems and assessing the health of the population. Since the city of Almaty is a large metropolis, the ecological situation is very poor. This directly affects the ecology of the City, Public Health. We manage, process data by processing GIS data. In solving upcoming environmental problems, in developing new solutions, a special data card will come to the rescue. This will lead to solving problems from this point of view. It is possible to create monitoring maps by combining space surveys and statistical data. One of the most effective aspects of GIS data is that it allows you to optimally consider problems and work in any area. From this point of view, the GIS industry is developing rapidly. In the country, this industry is developing rapidly and is gaining a lot of demand.

Including dynamic capacity impact in an improved model for optimal flood control operation in river-type reservoirs

Flood control operations in river-type reservoirs are significantly affected by both the dynamic reservoir capacity and flood propagation within the reservoir area. However, the traditional reservoir flood control optimal operation (RFCOO) model is usually based on the static capacity method, which may bring large errors in scheduling calculations for river-type reservoirs. To address this issue, an improved model, the reservoir dynamic capacity flood control optimal operation (RDCFCOO) model, that includes the influence of the dynamic reservoir capacity and flood propagation, was developed to improve the accuracy of flood regulation calculations in river-type reservoirs. This improved model includes a 1D unsteady flow simulation and a rederived objective function based on the maximum peak clipping criterion, and expresses the state transformation equations using the de Saint-Venant equations. Furthermore, a multi-core parallel DP (PDP) algorithm that incorporates reduction of state dimensionality (RSD) was developed to effectively derive optimal operation schemes. The improved model and algorithm developed herein were validated through an application to the Xiangjiaba Reservoir, China. The results show that: (1) By adding the item (qiw) to the objective function and substituting the de Saint-Venant equations for the water balance equation, the RDCFCOO model developed in this paper can account for the impact of dynamic capacity and flood propagation. As a result, it exhibits a more accurate and detailed flood control process that was closer to the actual conditions of river-type reservoirs compared to the RFCOO model; (2) By removing the invalid discrete state points from the search space and fully utilizing multi-core processors, the proposed PDP with RSD can significantly improve the computational efficiency of the DP in solving RDCFCOO problems. The improved model and algorithm can effectively improve the calculation accuracy of flood control optimal scheduling in river-type reservoirs and provide more information for decision-makers.

Desertification of Bengal Dryland Areas Possible under Projected Climate Conditions

Drylands are some of the most sensitive areas to climate change and human activities around the globe. Assessment of future climate trend scenarios provides valuable practical information for dryland management decision-making. According to Huang et al. (2017), more than 50% of global drylands will expand by this century, with a maximum (78%) of newly expanded dryland occurring in developing countries. To understand the potential for expansion of drylands and desertification, we examine critical predictor variables (temperature and precipitation) of Bengal dryland expansion to guide early actions to mitigate and prevent desertification. Using trend analysis of bias-corrected CMIP6 projected climate change data for temperature and precipitation (2022-2041), results indicate future dryland expansion is possible from increases in temperature and declines in monsoonal precipitation. Over the next two decades (2022-2041), Bengal dryland areas will be 0.1-0.5°C warmer, and rainfall will decrease by 2.57-13.43cm total during the monsoon period. Given these variables are critical predictors of dryland expansion because of their role in driving evapotranspiration and soil moisture deficits; we anticipate an increase in the population affected by water scarcity, land degradation, and desertification. Our work provides information critical for effective dryland management, biodiversity conservation, and land-use planning under future climate conditions.

Restricting access to AI decision-making in the public interest: The justificatory role of proportionality and its balancing factors

In the European Union, individuals subject to fully automated AI-based decisions by the government have the right to request access to the processing information under Article 15(1)(h) of the General Data Protection Regulation (GDPR). However, this right may be restricted on public interest grounds, such as preventing system manipulation to ensure the effectiveness of the law or reducing excessive burdens on public officials to maintain efficiency in government operations. The principle of proportionality is a key instrument to assess the legality and legitimacy of such restrictions, yet its application has been largely overlooked in discussions concerning the competing public interests under Article 15(1)(h) of the GDPR. This paper draws on legal and interdisciplinary scholarship, as well as the case law of the Court of Justice of the European Union (CJEU) to explore the role of proportionality and its balancing factors in shaping justifications for public interest restrictions on the data protection right of access to AI decision-making information.

Web search results processing in an information support system for decision-making processes

Objectives. The problem of the web search results processing in an information support system for decision[1]making is solved in order to create and correct a meaningful description of a problem situation. An approach to solving this problem is proposed based on the use of thematic text corpora (collections of texts on a specific topic) as knowledge about the subject area, as well as a knowledge representation model based on verbal associations. When solving problems of the web search results processing in a decision-making information support system, five main goals are pursued: the formation of an extended description of a problem situation, the synthesis of a search prescription, an Internet search for information about decisions made, the synthesis of a retelling of the information found, and an assessment of the quality of the found analogues of the decisions made.Methods. Methods of set theory, graph theory and mathematical linguistics are used.Results. A mathematical model has been developed for the web search results processing in an information support system for decision making. The concepts of verbal association of words and texts, as well as pragmatically complete lexical structure, are formalized. The proven properties of such structures provide algorithmization of information processes in the model under consideration.Conclusion. The approach to modeling is based on the formalization of the concepts of the informativeness of words, sentences, texts and the informativeness of verbal associations between them. As an implementation of the model proposed in the article, algorithms have been developed for creating a dictionary of pragmatically complete lexical structures, creating structural-lexical templates for sentences, texts and subject areas, synthesizing a brief retelling of the information found, and assessing the quality of the found analogues of the decisions made.

Digital transformation of the future of forestry: an exploration of key concepts in the principles behind Forest 4.0

This paper looks at the incorporation of blockchain and Internet of Things (IoT) technologies into Forest 4.0, a sector that harnesses advanced tools such as artificial intelligence and big data for efficient and sustainable forest monitoring and management. The synergy of blockchain and IoT has gained significant attention, offering a secure and decentralized framework for data management, traceability, and supply chain oversight. The provided use cases demonstrate how these technologies improve forest practices, with insight into smart contract implementation and decentralized systems for sustainable forest management. The major findings imply that digital technologies such as blockchain, IoT, AI, WSNs, etc. can help improve forest management sustainability, efficiency and transparency, and integration of these technologies can provide significant information for decision-making and resource allocation, as well as improve supply chain transparency and sustainable forest practices.

A Methodological Framework for New Product Development in Fuzzy Environments

New product development (NPD) is crucial for helping companies to maintain competitive advantages. In this study, a methodological framework is presented combining a novel Kano model and fuzzy axiomatic design (FAD) for improving the product development capability in the whole NPD process. In the Kano model, a novel mixed-class classification method is presented to classify each evaluation indicator agreed on by the majority, and to calculate the affiliation value based on category strength (CS) to display the degree to which the indicator belongs to a certain attribute. A new importance ratio is also proposed to adjust the importance of each indicator attribute. This helps to achieve higher customer satisfaction and improve the attractiveness of the product or service. FAD is then used to measure the gap between customer satisfaction and the company’s expected levels of satisfaction in terms of product functions. This enables the company to obtain more comprehensive information for decision-making. A case study is provided to verify the practicability of the proposed method. Sensitivity analysis proves the robustness of the results based on the number of respondents. Finally, comparative analysis with existing approaches demonstrates the strengths of the proposed method.