Quality Of Decisions Research Articles

Digital technologies in territorial development: Opportunities and challenges of application in state and municipal administration

Digital technologies are introduced into state and municipal administration with a view of strengthening interaction of authorities of different levels with each other and the population, as well as increasing the speed and quality of decision-making. At the same time, digital transformation processes at regional and municipal levels are highly differentiated. The paper delves into theoretical, methodological and practical aspects of the use of digital technologies in territorial development and looks at oppor tunities for their application in state and municipal administration. Methodologically, the study rests on the theories of regional growth and strategic management, spatial theory, and the concept of digital society. Synthesis, data analysis, visualization, and ex pert assessment are applied as research methods. Empirical data are retrieved from the Federal State Statistics Service (Rosstat) and regulatory documents on the development of the RF subjects. Our study confirms that digitalization is becoming a critical factor in long-term territorial development. We have systematized the types of digital technologies employed in governance processes and revealed that their use by state authorities and local self-governments (SAs and LSGs) is highly differentiated. The Ural and Central Federal Districts are leaders in the use of digital technologies. The findings indicate the need for cultivating mutual consistency and integration of digital transformation strategies and regional development strategies. To ensure effective digitalization of territories at different levels, it is necessary to define the boundaries and standards for the use of digital technologies, develop technical com petencies of decision-makers, guarantee information security and protection of personal data, and reduce fraud risk.

Shared Decision-Making in Solid Organ Transplantation: A Review

Solid organ transplantation entails numerous complex medical and ethical decisions. Shared decision-making (SDM) has been advocated as the optimal model for navigating these decisions, providing a collaborative framework that enhances person-centered care. This approach involves patients, caregivers, and healthcare professionals in the decision-making process, ensuring that clinical decisions align with patient preferences, values, and individual circumstances alongside clinical indications. This paper reviews the implementation of SDM throughout the transplantation journey, from diagnosis and transplant referral, pre-transplant assessments, waiting lists, to the organ offer, perioperative period, and long-term follow-up. Barriers to SDM include factors at the patient, provider, and system levels, including inadequate patient–provider communication. Effective SDM requires tailored educational resources, prognostic tools, clinician training, collaborative care models, and supportive policies. Additionally, leveraging technology, such as artificial intelligence and mobile applications, can enhance patient engagement and decision quality. SDM promotes equity by involving all patients—including those from more vulnerable groups—in meaningful conversations about their treatment options, thereby mitigating disparities in access and outcomes. Future research should focus on the long-term impacts of SDM interventions, the development of comprehensive prognostic tools incorporating patient-reported outcomes, and systemic changes to integrate SDM into clinical practice, aiming to improve patient outcomes and person-centered care.

Doomed in din or synced with signal: a study of dissent within Indian monetary policy committee

ABSTRACT The paper investigates the effect of latent discord present amongst Indian Monetary Policy Committee members on the accuracy of inflation and growth forecasts. We use FinBERT, a deep learning model, to propose a refined measure of Implicit Dissent and use it to further investigate how such discord can affect the forecast accuracy. Our results show that lower levels of implicit dissent increase uncertainty and impair forecasters’ ability to make accurate predictions. In contrast, higher levels of implicit dissent mitigate uncertainty and help anchor forecasts. Our study concludes that heterogeneity in signals by central bankers increases the mean decision quality of forecasters.

Financial Reporting Quality and Investment Decisions Making in Organizations: An Empirical Analysis of Selected Listed Manufacturing Firms in Nigeria

The study examined the effect of financial reporting quality on investment decisions in ten listed manufacturing firms in Nigeria. The study used data from annual financial statements published between the period of 2013 to 2022. Also, unit root testing and co-integration were used as the pre-test technique; while, panel data, fixed effect result, random result, fixed effect result and Hausman’ test were applied for the formulated objectives. The Levin, Lin & Chut, Im, Pesaran and Shin W-stat and ADF - Fisher Chi- unit root techniques demonstrated that return on investment, accounting conservation, timely loss recognition and earning quality were integrated at order one and at level. Kao co-integration technique test confirmed a long-term association between the variables. Hence, indicating a long-term connection between return on investment, earning quality and accounting conservation, timely loss recognition. Also, the outcome indicates that the Hausman's test probability value was greater than 0.05 (p>0.05) levels of significance, indicating that Random effect estimate is the best estimator to explain the result. The result from the Random technique showed that earning quality and accounting conservation were significant at 5% significant level and directly related to return on investment; while, timely loss recognition was positively related to return on investment but non-significant at 5%. This suggests that 1% increase in earning quality (EAQ) and accounting conservation brought about 5.2% and 0.9% increase in return on investment (ROI) respectively; while, timely loss recognition had zero effective on return on investment (ROI). The study concluded that financial reporting quality boosts investment decisions made by investors, which promotes the rate of return on investments in listed manufacturing corporation. It is recommended that management of manufacturing organization should ensure that their respective financial reporting provide valuable knowledge for decision-making, with respect to the standard of financial statements through complying within commonly agreed accounting standards.

The Influence of Personality Traits and Domain Knowledge on the Quality of Decision-Making in Engineering Design

The Influence of Personality Traits and Domain Knowledge on the Quality of Decision-Making in Engineering Design

Design and implementation of a stakeholder consultation process for rapid health technology assessments in Argentina

IntroductionHealth technology assessment (HTA) is a standardized methodology that allows the assessment technologies’ value. By incorporating the perspective of stakeholders in a public consultation process, transparency and quality of decisions can be improved. ObjectiveTo describe the active stakeholder consultation process for rapid HTAs in an Argentinean, independent, academic, non-profit HTA agency, assessing its initial five years. MethodsSince 2017, we have been conducting an active public consultation process for rapid HTA documents, inviting producers, healthcare professionals, and patient organizations to provide comments, and their input may lead to changes in the HTA documents. Changes were classified as major (changes to the coverage recommendation), intermediate (changes in efficacy, net benefit, or cost-effectiveness that did not change coverage recommendations), and minor modifications (other changes). ResultsFrom May 2017–August 2022, 308 rapid HTA (rHTA) reports were published, and 3,438 invitations were sent. 140 rHTA (45.5%) received a total of 228 comments. Comments came from producers in 53% (n = 112) and healthcare professional organizations in 31.2% (n = 66). Technologies evaluated were drugs in 37% (n = 114), procedures in 35.5% (n = 109), diagnostic methods in 15.3% (n = 47), and devices in 12.2% (n = 38). Out of 308 rHTA documents, 120 (39%) were modified—mostly minor adjustments (n = 100; 80%), followed by major (n = 12; 10%) and intermediate modifications (n = 8; 6.4%). ConclusionImplementing an active stakeholder involvement process in HTA is feasible in a low- to middle-income country context and strengthens and improves the HTA process.

A managerial perspective on the determinants and outcome of digital transformation in multinational corporations in Malaysia

The primary objective of this study was to examine the antecedents of digital transformation (DT) within multinational corporations (MNCs) in Malaysia, from the perspectives of corporate managers. Amidst limited research on DT within the MNC context, this paper examines the key drivers of DT in Malaysian MNCs. A quantitative method using non-probability sampling was used to gather the required data via the distribution of questionnaires among the MNCs’ managers. To evaluate the underlying theoretical model based on the collected data, we chose SmartPLS as the preferred method. Findings revealed that business value, digital leadership, inter-functional coordination and decision-making quality were significant drivers of DT, while DT exerted a positive influence on business performance. However, collaborative innovation did not have a significant relationship with digital transformation adoption in MNCs. The findings offer novel insights for both academics and international corporate managers, enhancing their understanding of the drivers behind DT adoption from the perspective of managers within MNCs in Malaysia.

ПРИМЕНЕНИЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В АНТИКРИЗИСНОМ УПРАВЛЕНИИ ОРГАНИЗАЦИЕЙ

In recent years, there has been active digitalization of various industries. One of the promising end-to-end technologies is artificial intelligence. The introduction of tools based on its application helps to optimize business processes and management, including anti-crisis management, which is especially sensitive to the speed and objectivity of decisions made. This is due to the dynamism of the external environment and the inefficiency of applying methods that made it possible to diagnose and resolve crises earlier in the new conditions. At the same time, there is a lag in the scientific and methodological base from the demands of practical activities. The article provides an overview of the opportunities provided by the use of artificial intelligence technologies for solving anti-crisis management problems (analysis of the external environment, internal potential, competitive advantages, strategic restructuring and a posteriori analysis of the causes of crisis situations). Special attention is paid to assessing the readiness of Russian organizations to implement the relevant tools. As a result of the study, the scale of AI use at the current stage of digital transformation was determined, as well as the prospects for its further development at various levels of management. Conclusions are made about the positive effects (increased speed, quality and objectivity of decisions taken, reduced costs of crisis management) of the use of new technologies, provided that they are comprehensively implemented taking into account risks.

Подходы к формализации организационно-технологических задач интеграции искусственного интеллекта в систему управления ОАО «РЖД»

Annotation: the issues of automation of the processes of collection, storage, transmission, analytical processing of information in the interests of improving the quality of management decisions in the railway management system, as well as the introduction of artificial intelligence systems in relation to the management bodies of Russian Railways are considered. Purpose: formalization of regulatory approaches for the implementation of artificial intelligence systems. Methods: harmonization, system analysis, simplex planning. Results: in the course of the research, approaches to the regulation of regulatory and legal measures have been identified that allow the development and improvement of NTDs based on unified approaches. Practical significance: the definition of approaches to the regulation of regulatory and legal measures will allow specialists involved in system design, development, implementation, operation of AI systems, developers of standards, as well as specialists of regulatory authorities, to improve the regulatory framework based on unified approaches, and developers of AI technologies will allow them to form new requirements for software and hardware being developed.

FORMATION OF AN ENTERPRISE MANAGEMENT SYSTEM IN THE CONDITIONS OF THE DIGITAL ECONOMY

The purpose of the article is to study the features of the formation of an enterprise management system in the conditions of digital transformation of the economy. Attention is focused on the importance of building an enterprise management system in the conditions of digitalization. Key changes that the transition to a digital economy leads to are identified. Factors that contribute to the development of the digital economy are highlighted (development of the information and communication technologies industry, strong educational institutions, competitiveness of innovations). The stages of digital transformation that an enterprise must go through are characterized. The conceptual principles of the enterprise management system in the conditions of digital transformation of the economy are defined. The goal of enterprise management in the conditions of digital economy is established. Management tasks are defined, the implementation of which ensures the achievement of the goal. The principles (innovation, adaptability, digitalization, automation, customer-orientation, flexibility, transparency, accountability) and functions (planning, organization, motivation, control, communicative, adaptive) of management in the conditions of digital transformation of the economy are revealed. The principle of omnichannel is proposed for use, which involves the integration of various communication channels, which will ensure the efficiency and quality of management decisions. The list of functions is supplemented with communicative and adaptive functions. Management methods in the digital economy are characterized, which are based on the use of digital technologies and allow for the development of effective management solutions (management method based on digital transformations, data-driven management method, management method based on the use of Agille principles, management using cloud technologies, management using robotics and process automation (Robotic Process Automation (RPA)), management based on multichannel, management using digital platforms). The main directions of development of the management system in the context of digitalization are determined.

The Role of AI, IoT, and MIS in Facilitating the Digital Transformation of Supply Chains

Management Information Systems (MIS) have gradually become the technical cornerstone to help enterprises optimize the quality of decision-making. However, relying only on the data support provided by MIS is insufficient to help enterprises complete the supply chain's efficient allocation and high-frequency management. This paper aims to explore the feasibility of promoting the digital transformation of the supply chain in China's transportation industry by combining emerging technologies such as the Internet of Things (IoT), Artificial intelligence (AI), and Management Information Systems (MIS). It has been found that a strong combination of AI, IoT, and MIS technologies can effectively promote the digital transformation of the supply chain. However, there are still many challenges in practical application. Therefore, this paper proposes the interaction model of these three technologies. IoT inputs the information generated in the operation and stores it in MIS, providing data support for AI's intelligent analysis. Then, the instructions issued by AI are transmitted directly to MIS. Finally, the IoT controls the physical entity that executes these decisions. In addition, this paper summarizes the problems and reasons that may exist in applying MIS, IoT, and AI technology in the transportation industry at this stage. It is found that many problems, including low utilization efficiency of MIS, low willingness of front-line operators to use it, differences in information transmission protocols, and high cost of AI training, hinder these three technologies to promote the digital transformation of the supply chain.

Metacognitive processes, situational factors, and clinical decision-making in nursing education: a quantitative longitudinal study.

This study examined the longitudinal development of metacognitive skills and clinical decision-making abilities in nursing students, focusing on the interactions between metacognitive processes, situational factors, and individual differences. A longitudinal, quantitative design was employed, following 185 third-year nursing students from a major university in China over one academic year. Data were collected at six time points using the Metacognitive Awareness Inventory, Nursing Decision-Making Instrument, and custom-designed clinical scenario assessments. Latent Growth Curve Modeling, Multilevel Modeling, and Moderation Analysis were used to analyze the data. Significant positive growth trajectories were observed for both metacognitive awareness (mean slope = 0.07, p < .001) and decision-making skills (mean slope = 0.08, p < .001). Metacognitive regulation emerged as the strongest predictor of decision-making outcomes (β = 0.188, p < .001 for quality; β = 0.168, p < .001 for efficiency). Task complexity negatively impacted decision-making quality (β = -0.129, p < .001), while time pressure more strongly affected efficiency (β = -0.121, p < .001). Cognitive style and emotional intelligence moderated the relationship between metacognitive processes and decision-making outcomes. The effectiveness of metacognitive strategies in mitigating the negative effects of situational factors varied across individuals and over time. This study provides robust evidence for the complex interplay between metacognitive processes, situational factors, and individual differences in the development of clinical decision-making skills among nursing students. The findings highlight the importance of tailoring educational interventions to enhance specific metacognitive skills, particularly regulation, while considering the impact of situational factors and individual cognitive styles. These insights can inform the design of more effective, personalized approaches to nursing education, potentially enhancing the preparation of nursing students for the complexities of clinical practice.

Efficacy, Safety, and Recurrence in Older Thyroid Eye Disease Patients Undergoing Teprotumumab Treatment.

Increasing life expectancy and an aging population have preserved quality of life decisions into older adulthood, defined by some clinical standards as greater than 75 years of age. While teprotumumab may represent a breakthrough in the treatment of thyroid eye disease, the teprotumumab phase III trial included only 2 patients aged over 75. Four female patients between the ages of 78 and 86-of whom 3 completed 8 infusions and 1 completed 7 infusions before discontinuation-were included in our study with a mean initial Clinical Activity Score score of 5.5, subjective diplopia, and proptosis. All patients experienced reduction in Clinical Activity Score with teprotumumab treatment. Two patients were subjective diplopia responders. Of the 6 eyes with collected measurements, all demonstrated a ≥2 mm reduction in post-treatment Hertel measurements. Most common adverse events were hyperglycemia, dysgeusia, fatigue, and alopecia. One patient with diabetes experienced an A1C rise requiring insulin. One patient had recurrence with increasing proptosis and recurrence of diplopia.

The IMproving treatment decisions for Patients with AortiC stenosis Through Shared Decision Making (IMPACT SDM) Study: study protocol for a cluster randomized stepped wedge trial

BackgroundThe American College of Cardiology, American Heart Association, and Centers for Medicare and Medicaid Services recommend shared decision-making (SDM) for patients with severe aortic stenosis choosing between transcatheter aortic valve replacement (TAVR) and surgical aortic valve replacement (SAVR). Although tools such as patient decision aids (DAs) and training in SDM have been shown to improve SDM, implementation of SDM and DAs is limited. The IMproving treatment decisions for Patients with AortiC stenosis Through Shared Decision Making (IMPACT SDM) study aims to (1) determine the effectiveness of the interventions (a DA and clinician SDM training) in achieving SDM (primary outcome) and improving the quality of decisions about aortic valve replacement, (2) determine the reach of the DAs and adoption of training, and (3) explore potential mechanisms of effectiveness and implementation at the patient-, clinician-, and clinic-level.MethodsThe study is a hybrid type II effectiveness-implementation study using a cluster randomized batched stepped wedge trial with 8 sites across the USA. Eligible patients will be surveyed before and after visits with the heart valve team; clinicians will be surveyed after visits. Reach of DAs and adoption of training will be tracked. Clinicians will be interviewed regarding barriers and facilitators to implementation.DiscussionThe IMPACT SDM Study seeks to provide evidence of the ability of the interventions to improve SDM and decision quality, and also to shed light on barriers and facilitators to SDM implementation to promote future implementation efforts.Trial registrationClinicalTrials.gov NCT06171737. Registered on December 15, 2023.

Experience Minimizes the Pull-to-Center Effect in Newsvendor Decisions

Problem definition: The asymmetric pull-to-center effect for newsvendors is a robust finding in operations, and understanding why newsvendors make suboptimal decisions is key for identifying ways to improve decision-making quality in this critical task. Although prior studies have indicated that experience does not substantially mitigate the pull-to-center effect, the experience levels achieved in those previous studies are limited in comparison with the experience level that a near-continuous time environment can provide. Methodology/results: We conduct a set of laboratory experiments using a near-continuous time environment to determine the effect that extensive experience has on newsvendor behavior and the extent to which resultant learning is transferable across conditions. Observed behavior clearly demonstrates that the pull-to-center effect is substantially reduced, if not eliminated, with sufficient experience and that this learning can have positive spillovers to more traditional settings. Further, the experiments suggest that it is the repeated feedback regarding a given inventory decision rather than the ability to explore many strategies that drives improved decision making. Managerial implications: Experience can mitigate the pull-to-center effect, and near-continuous time environments can be an effective training tool for gaining such experience. Funding: This work was supported by the Ministerstvo školstva, vedy, výskumu a športu Slovenskej republiky [Grants VEGA 1/0660/23 and VEGA 1/0721/24] and the Slovak Research and Development Agency [Grant APVV-19-0573]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0439 .

Understanding Informational Bottlenecks in Complex Systems: Strategies for Enhancing Decision Quality in Financial and Non-Financial Markets

Informational bottlenecks in complex systems represent a critical challenge, influencing the quality and timeliness of decision-making across financial and non-financial markets. This research investigates the origins and dynamics of informational bottlenecks, exploring their impact on system efficiency, resilience, and decision quality. By examining theoretical models and real-world case studies, the study identifies key mechanisms through which bottlenecks emerge, including data overload, communication inefficiencies, and cognitive biases. Additionally, it evaluates strategies for mitigating these bottlenecks through advanced analytics, machine learning, and organizational design interventions. Special attention is given to the role of technology in enabling effective data flow and enhancing decision-making processes. This interdisciplinary analysis spans financial markets, where rapid information processing is vital, and non-financial systems such as supply chains and healthcare networks, highlighting universal challenges and tailored solutions. The findings contribute to a deeper understanding of how informational bottlenecks disrupt system performance and propose actionable strategies for fostering robust and adaptive decision-making frameworks in complex environments.

Advanced Design Validation Planning Techniques for Commercial Vehicle E-Axles

&lt;div&gt;Design validation plays a crucial role in the overall cost and time allocation for product development. This is especially evident in high-value manufacturing sectors like commercial vehicle electric drive systems or e-axles, where the expenses related to sample procurement, testing complexity, and diverse requirements are significant.&lt;/div&gt; &lt;div&gt;Validation methodologies are continuously evolving to encompass new technologies, yet they must be rigorously evaluated to identify potential efficiencies and enhance the overall value of validation tests. Simulation tools have made substantial advancements and are now widely utilized in the development phase. The integration of simulation-based or simulation-supported validation processes can streamline testing timelines and sample quantities, all the while upholding quality standards and minimizing risks when compared to traditional methods. This study examines various scenarios where the implementation of advanced techniques has led to a reduction in the e-axle design validation plan (DVP), particularly in relation to the start of production (SOP) decision-making quality gates.&lt;/div&gt; &lt;div&gt;Many DVPs incorporate tests in a specific order to enhance the validation impact of each sample and to guarantee that preconditioning tests are implemented when necessary. An instance of preconditioning is subjecting a system to thermal cycling. Thermal cycle preconditioning ensures that the sample accurately represents a real-world system when undergoing sealing-related tests, such as ingress protection testing according to ISO 20653 [&lt;span&gt;1&lt;/span&gt;]. Assessing the necessary thermal cycling to “bed-in” a sample would be highly elaborate using a physical sample, but it is a straightforward aspect to extract from modern finite element analysis (FEA). A case study will be presented to evaluate the minimum required thermal cycling and determine the cost savings for the DVP.&lt;/div&gt; &lt;div&gt;Furthermore, the validation supported by simulations will be showcased in the context of accelerated lifetime testing. Often, accelerating such tests necessitates a balance between the distribution of damages and the overall testing duration. By incorporating safety factors from simulations as an initial input, the distribution of damages can be adjusted to allow for some over-testing on more secure components, thereby reducing the overall testing time.&lt;/div&gt; &lt;div&gt;Efficiency assessment will additionally be considered for virtual validation due to the complexity of the measurement and data acquisition, contributing to measurement uncertainty. Furthermore, simulation-based validation will be considered for the case of lubrication testing, which can be hampered by a largely qualitative assessment criteria.&lt;/div&gt; &lt;div&gt;Overall, these scenarios will be evaluated for their potential to streamline the overall DVP process in terms of testing time, sample quantity, and critical path duration. This underscores the potential benefits of leveraging advanced DVP techniques for cost and time savings.&lt;/div&gt;

Investigating the Impact of the Hospital Information System on the Performance of Management Units at Pasteur Hospital in Bam from the Perspective of Managers

Background: The Hospital Information System (HIS) is a comprehensive information management system in hospitals that plays a significant role in the quality of managers' decisions. Therefore, this study aimed to examine the impact of the HIS on the performance of management units at Pasteur Hospital in Bam from the managers' perspective in the year 2023. Method: The present study was an applied, descriptive, and cross-sectional study conducted in 2023. The performance of management units was examined in three clinical, human resources, and financial indicators. The study population consisted of all the managers at Pasteur hospital in Bam at three levels: executive, middle, and top management, who were entered into the study through a census (38 individuals). Information was collected using a standardized questionnaire, and for data analysis, SPSS 27 software and appropriate descriptive and analytical statistical tests (independent t-test and ANOVA) were used. Results: Participating managers were 76.30 % women and 23.70 % men. 73.70 % of them had a bachelor's degree and most of them were in the category of operational and middle managers. From the point of view of the managers of the HIS, the greatest impact on the indicators of the trend of treatment activities (28.60 ± 5.35), cost (50.00 ± 3.60), productivity and training (32.35 ± 12.81) and the least impact on the indicators of information exchange (25.50 ± 4.67), income (32.33 ± 0.57), salary and wages (10.50 ± 5.00). In this study, three components—clinical, financial, and human resources—were examined separately by gender, education level, and management levels. The results of the independent t-test indicated that there was a significant difference only in the clinical component based on gender (p = 0.04) Conclusion: To enhance the effectiveness of the HIS on managers' performance, it is essential to first conduct a comprehensive needs assessment of all management units. This needs assessment should identify the essential tasks and specific needs of each unit, and based on that, the enhancement of the HIS should be aligned with these needs. Moreover, paying special attention to the dimensions and indicators that receive less impact from this system can help improve the overall performance of the system and enhance its effectiveness in all aspects.

Integrating Symmetry in Attribute-Based Sentiment Modeling with Enhanced Hesitant Fuzzy Scoring for Personalized Online Product Recommendations

Online product reviews provide valuable insights on user experiences and product qualities. However, issues such as information overload and the limited utilization of review features persist, particularly in personalized rankings for popular items like movies. To address these challenges—information overload in online reviews, limited review feature utilization, and personalized decision-making for high-demand products like movies—we introduce a personalized online decision-making framework that integrates a sentiment model for product attributes with an enhanced hesitant fuzzy scoring function. This framework incorporates the concept of symmetry in sentiment analysis. It employs feature words, sentiment terms, and modifiers to assess user sentiments within a hesitant fuzzy setting, utilizing symmetrical relationships between positive and negative sentiments. The improved fuzzy score function efficiently quantifies sentiment values for product features by considering the symmetrical balance of user opinions. Additionally, review quality assessment incorporates both content and reviewer characteristics, resulting in final attribute evaluations. An attribute weighting system, tailored to diverse product types, further captures product specifics and user inclinations, leveraging symmetry to balance varying user preferences. Validation through multi-genre movie sorting demonstrates the method’s capacity to handle review data across varied products and user tastes, offering a robust tool for enhancing online decision quality, especially for high-demand items.

Assess the efficacy of China's Inter-provincial Government Services policy: A quantitative evaluation based on PMC-Index model.

To face with the challenges of governance in the digital age, such as insufficient coordination between regional governments and low quality and efficiency of government services, China has proposed the Inter-provincial Government Services Policy. The policy is capable of realizing the government's ability to handle service matters for the public in different regions, thus facilitating the regional government's coordination and upgrading the level of government services. This paper collects and organizes the texts of 28 Inter-provincial Government Services policies, and uses ROSTCM6 text mining software to screen and identify the policy text content. Then a quantitative evaluation method based on the PMC model is proposed to examine the consistency and efficacy of the policy in this paper. The results show that: (a) The policy design is generally considered to be rational, with the majority of policies rated as excellent and a few rated as acceptable. There are no policies considered bad or perfect. From a certain point of view, these policies show obvious advantages in terms of policy nature, policy content and policy function. (b) The equilibrium of various policy indicators implies a high level of policy consistency. It indicates the overall coherence and coordination of the policies, contributing to enhanced predictability, credibility, and operationalization of policies, thereby establishing the foundation for their effective implementation. (c) There are still several weak points with the current policies, including the narrow scope of areas, the lack of medium- and long-term planning, and the insufficiently scientific nature of the instruments, evaluations and citations. This paper presents optimization recommendations aimed at addressing the aforementioned issues, which include expanding the scope of the policy, bolstering the long-term impact of the policy, and enhancing the quality of decision-making.