Integrated Supplier Selection Framework in a Resilient Construction Supply Chain: An Approach via Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA)

Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era

Supply chain organizations should calmly and cautiously take the most accurate and sustainable decisions quickly and put them into practice. It is obvious that traditional time series-based demand and supply planning approaches are insufficient to meet current business needs due to factors such as sharp changes in market and commercial dynamics, pandemics, and natural disasters on the management of green supply chains, especially these days. In the near future, there will be a need for more resilient supply chains with a flexible business models that are not affected by sudden changes and that can make sustainable decisions dynamically. Additionally, all stakeholders must act with a green supply chain approach to conduct production and service activities in a way that causes the least damage to nature. Companies must build more resilient supply chains by considering environmental sensitivities to compete in the market and ensure their continuity. In this context, the green supply chains should be evaluated according to their resilience. For this purpose, Supply Chain Operations Reference (SCOR) model is extended with novel performance attributes to evaluate resilience of green supply chains in this study. The SCOR-embedded novel green supply chain resilience evaluation model is structured as a three-level performance attribute hierarchical structure. Then, the model is handled as a multi-criteria decision-making problem to determine importance of the performance attributes. Best Worst Method integrated Interval Valued Intuitionistic Fuzzy Analytic Hierarchy Process is used to determine the importance of performance attributes. Most important performance attributes are determined in each level of hierarchy. According to results, organizational factors play a key role to build more resilient supply chains. Especially, integrated systems are required for supply chain resilience.

A hybrid framework to model resilience in the generic medicine supply chain of MSMEs

Purpose

One of the most important components of healthcare is the timely delivery of pharmaceutical products, such as life-saving medicines. However, disruptions like COVID-19 bring new challenges and risks to the pharmaceutical supply chain (PSC) and healthcare organizations that impact their operational performance. This study focuses on mitigating risks in India's generic medicine supply chain (GMSC) as a result of various disruptions, which can assist policymakers develop appropriate plans and strategies to build resilience in the Jan Aushadhi Scheme (JAS) of micro, small and medium enterprises (MSMEs) in order to improve their overall performance.

Design/methodology/approach

Risk-causing vulnerabilities and resilience capabilities are identified from the literature review and expert's opinions. Following that, the vulnerabilities are classified into cause-and-effect vulnerabilities, and supply chain resilient capabilities (SCRCs) are measured using a hybrid fuzzy DEMATEL and best worst method (FDEMATEL-BMW) framework.

Findings

The outcome of the study reveals that transportation breakdown, loss of human resources and loss of suppliers are the potential risk-causing vulnerabilities that lead to vulnerabilities like shortages of medicines, loss of in-hand stock qualities and loss of sales/revenue. In addition, the analysis suggests that the sustainability of an organization with maximum weightage is the critical factor for building resilience in GMSC followed by flexibility, agility and visibility.

Practical implications

The integration of resilience into Jan Aushadhi GMSC can help in managing disruptions efficiently and effectively to mitigate risk and optimize MSMEs overall performance.

Originality/value

To the best of the authors’ knowledge, this work will be the first of its kind to model resilience in GMSC of MSMEs using a hybrid framework.

Supplier Selection through Multicriteria Decision-Making Algorithmic Approach Based on Rough Approximation of Fuzzy Hypersoft Sets for Construction Project

The suppliers play a significant role in supply chain management. In supplier selection, factors like market-based exposure, community-based reputation, trust-based status, etc., must be considered, along with the opinions of hired experts. These factors are usually termed as rough information. Most of the literature has disregarded such factors, which may lead to a biased selection. In this study, linguistic variables in terms of triangular fuzzy numbers (TrFn) are used to manage such kind of rough information, then the rough approximations of the fuzzy hypersoft set (FHS-set) are characterized which are capable of handling such informational uncertainties. The FHS-set is more flexible as well as consistent as it tackles the limitation of fuzzy soft sets regarding categorizing parameters into their related sub-classes having their sub-parametric values. Based on these rough approximations, an algorithm is proposed for the optimal selection of suppliers by managing experts’ opinions and rough information collectively in the form of TrFn-based linguistic variables. To have a discrete decision, a signed distance method is employed to transform the TrFn-based opinions of experts into fuzzy grades. The proposed algorithm is corroborated with the help of a multi-criteria decision-making application to choose the best supplier for real estate builders. The beneficial facets of the put forward study are appraised through its structural comparison with few existing related approaches. The presented approach is consistent as it is capable to manage rough information and expert’s opinions about suppliers collectively by using rough approximations of FHS-set.

A Self-Assessment Framework for Global Supply Chain Operations

This research developed an effective supply chain management (SCM) operation model and a corresponding diagnostic methodology in the global competitive environment by combining three phases and methodologies. In Phases 1, a list of impact factors was collected from relevant studies, and a hierarchy for the current complex research issue was established. In Phase 2, an expert survey was conducted for enhancing the content effectiveness of the model. Subsequently, an analytic hierarchy process (AHP) was applied to determine the weights of those factors. In Phase 3, a self-assessment framework was developed to examine the effectiveness of the global SCM. Finally, a case was analyzed to verify the effectiveness of the self-assessment scales. The results show that the concept of global SCM tends to be broader and more comprehensive than traditional one. Especially in the coordination and cooperation between market, organization itself and suppliers, while using information technology as a communication tool.

Core Elements Underlying Supply Chain Management in the Construction Industry: A Systematic Literature Review

The relevance of supply chain management (SCM) is being increasingly recognized in the construction industry. However, its implementation has been limited and is still challenging for researchers and practitioners. An adequate and systematic understanding of context-specific core concepts and practices are considered fundamental to foster its implementation. This paper aims to provide a holistic look into the existing research on elements underlying SCM in the construction industry. It adopts a systematic literature review method to examine almost two decades of publications and uses a comprehensive SCM framework to synthesize the findings. The results revealed a set of 19 core elements clustered in five subject areas (i.e., ‘strategic management’, ‘logistics’, ‘relationships’, ‘best practices’ and ‘organizational behavior’) that have a prominent role in construction SCM. Every core element was analyzed in detail and the results were discussed in the context of other evidence. This study produced the first comprehensive picture of the current state of knowledge, providing relevant contributions to enhance the understanding and implementation of SCM within the construction industry.

Digital Twin for Supply Chain Coordination in Modular Construction

Over the past decades, the construction industry has been attracted to modular construction because of its benefits for reduced project scheduling and costs. However, schedule deviation risks in the logistics process of modular construction can derail its benefits and thus interfere with its widespread application. To address this issue, we aim to develop a digital twin framework for real-time logistics simulation, which can predict potential logistics risks and accurate module arrival time. The digital twin, a virtual replica of the physical module, updates its virtual asset based on building information modeling (BIM) in near real-time using internet of thing (IoT) sensors. Then, the virtual asset is transferred and exploited for logistics simulation in a geographic information system (GIS)-based routing application. We tested this framework in a case project where modules are manufactured at a factory, delivered to the site via a truck, and assembled onsite. The results show that potential logistical risks and accurate module arrival time can be detected via the suggested digital twin framework. This paper’s primary contribution is the development of a framework that mediates IoT, BIM, and GIS for reliable simulation which predicts potential logistics risks and accurate module delivery time. Such reliable risk prediction enables effective supply chain coordination, which can improve project performance and the widespread application of modular construction.

Relative Importance Analysis of Safety Climate Evaluation Factors Using Analytical Hierarchical Process (AHP)

Various studies have confirmed that the increasing quality of safety climate has a positive influence on reducing the occurrence of accidents. The quality of safety climate is comprehensively affected in three domains: management, site, and enterprise. At the company level, it is challenging to manage all areas at a high level due to limited managerial resources. Therefore, it is necessary to establish a strategy that improves the safety climate step by step. For the efficient execution of the strategy, it is necessary to analyze the relative importance of each evaluation factor of the safety climate and allocate managerial resources accordingly. Therefore, this study aims to analyze the relative importance of safety climate evaluation factors using the analytical hierarchical process (AHP) technique. For this study, AHP questionnaire and analysis are conducted, and the relative priorities of safety climate evaluation factors are derived. As a result, (E) workers’ safety priority and risk non-acceptance is the most important dimension among seven dimensions as the weight is 0.1900. In addition, (E1) compliance with safety regulations, even if the process is tight, is the most important one between items as the weight 0.6663. The results of this study will be used as basic data for institutional improvement and policy making for a high-quality safety climate at construction sites.

A Hybrid MCDM Approach towards Resilient Sourcing

Achieving a supply chain that is resilient to potential unforeseen disruptions (e.g., strikes, floods, tsunamis, etc.) remains one of the vital concerns of decision makers (DMs). To build up a reactive supply chain plan towards resilience, the purchasing department needs to pay the strictest attention to sourcing decisions. This study contributes to the literature through developing an efficient resilient supplier selection approach based on a new holistic framework that enables the identification of key resilience pillars (RPs) and traditional business criteria (TBC) in light of a thorough literature review and experts’ opinions. To this end, the relative importance of TBC/RP was measured by applying the DEMATEL (D) method. This was followed by the application of MABAC-OCRA-TOPSIS-VIKOR (MOTV) methods to verify the suppliers’ ranking. Furthermore, the Spearman rank correlation coefficient (SRCC) approach was used to investigate the correlation among the suppliers’ ranking, revealed via the four methods. In this work, a real sourcing problem of scrap metal for a steel manufacturing company was solved to prove the applicability of the proposed approach. The research outcome revealed that the TBC of “trust” is the most important criterion, followed by the “cost”, leaving the “geographical location” criterion as the least important one. In this context, the RP of “flexibility” attained the highest relative weight compared to “agility”, which secured the lowest weight. The results also showed “absolute” correlation among MABAC, VIKOR, and OCRA compared to “very strong” correlation between TOPSIS and the others. This research can support supply chain managers to achieve supply chain systems that reduce not only sourcing costs, but also potential losses because of disrupting threats, by building resilient supply chains.

An Integrated Organizational System for Project Source Selection in the Major Iranian Construction Companies

Studies show that procurement management and its processes strongly affect project success in the construction industry, because the project-oriented organizations in the construction industry prefer to buy goods and services from outside the project team and benefit from outsourcing. Hence, these organizations are continually facing different levels of procurement processes, and the establishment of a robust outsourcing system is crucial for success of their projects and development of their businesses. On the other hand, the housing projects are considered a significant sector of the construction industry in terms of the number of projects and the impact on the national economy. Traditionally, the key sources in conventional housing projects are the general contractors, the consultants and the suppliers. In this study, essential elements of an organizational system have been investigated by expert opinions and through the Delphi method, and all effective aspects of the source selection problem have been identified and integrated. Based on the research findings, procurement of housing construction projects should be organized in three organizational levels: development of the long list, preparation of the short list and selection of the most appropriate source by focusing on four main elements of the source identification method, criteria definition, evaluation arrangement and assessment model.

A Simplified CityGML-Based 3D Indoor Space Model for Indoor Applications

With the continuous development of indoor positioning technology, various indoor applications, such as indoor navigation and emergency rescue, have gradually received widespread attention. Indoor navigation and emergency rescue require access to a variety of indoor space information, such as accurate geometric information, rich semantic information and indoor spatial adjacency information; hence, a suitable 3D indoor model is needed. However, the available models, such as BIM and CityGML, mainly represent geometric and semantic information of indoor spaces, and rarely describe the topological adjacency relationship of interior spaces. To address the requirements of indoor navigation and emergency rescue, a simplified 3D indoor model is proposed in this research. The building components and indoor functional spaces of buildings are described in a simplified way. The geometric and semantic information are described based on CityGML, and the topological relationships of indoor adjacent spaces are represented by CityGML XLinks. While describing the indoor level of detail (LOD) of buildings in detail, the model simplifies building components and indoor spaces, which can preserve the characteristics of indoor spaces to the maximum extent and serve as a basis for indoor applications.

Selecting the Optimal Green Agricultural Products Supplier: A Novel Approach Based on GBWM and PROMETHEE II

Due to the uncertainty of natural factors and a larger global population, the work of supplying sustainable agricultural materials, especially green agricultural products, faces enormous challenges. How to effectively evaluate and select the most desirable green agricultural material supplier is an urgent issue for both agribusiness and government. In this paper, an integrated q-rung orthopair fuzzy (q-ROF) group best–worst method (GBWM) and the PROMETHEE II was introduced to availably solve such issue. Firstly, by taking similarity degree into account to solve incomplete weight information, a novel technique was constructed to determine the experts’ weight reasonably under the q-ROF context. Secondly, to improve consistency for group decision making and obtain a highly reliable selection result, the GBWM was used to derive criteria weights. Then, based on the proposed generalized p-norm knowledge-based score function, the PROMETHEE II was further improved to rank the feasible alternatives. After that, a representative case under the background of green agricultural material supplier selection was investigated in depth. Finally, the detailed comparative technique was conducted to verify the validity and superiority of the improved method.

A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain

The challenges of global economies foster supply chains to have to increase their processes of collaboration and dependence between their nodes, generating an increase in the level of vulnerability to possible impacts and interruptions in their operations that may affect their sustainability. This has developed an emerging area of interest in supply chain management, considering resilience management as a strategic capability of companies, and causing an increase in this area of research. Additionally, supply chains should deal with the three dimensions of sustainability (economic, environmental, and social dimensions) by incorporating the three types of objectives in their strategy. Thus, there is a need to integrate both resilience and sustainability in supply chain management to increase competitiveness. In this paper, a systematic literature review is undertaken to analyze resilience management and its connection to increase supply chain sustainability. In the review, 232 articles published from 2000 to February 2020 in peer-reviewed journals in the Scopus and ScienceDirect databases are analyzed, classified, and synthesized. With the results, this paper develops a conceptual framework that integrates the fundamental elements for analyzing, measuring, and managing resilience to increase sustainability in the supply chain. Finally, conclusions, limitations, and future research lines are exposed.

SUPPLIER SELECTION FOR HOUSING DEVELOPMENT BY AN INTEGRATED METHOD WITH INTERVAL ROUGH BOUNDARIES

Residential whole-decoration is an important initiative for housing industrialization in China. Selecting the most suitable component supplier for housing development is of great significance for both property developers and buyers in the implementation of such a strategy. To address such a problem, this study uses hesitant fuzzy linguistic term sets to express the inaccurate judgments of individuals and then introduces a novel probability aggregation approach based on interval rough boundaries to enable a realistic presentation of the collective evaluations of a group. Then, we propose a hybrid multi-expert multiple criteria decision-making model by integrating the Best Worst Method (BWM) and Combined Compromise Solution (CoCoSo) method based on the interval rough boundaries. A case study about the supplier selection for housing development is carried out, which demonstrates the feasibility and applicability of our proposed hybrid model. A comparison study is also performed to further validate the robustness of the model.

Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic

The increasingly global context in which businesses operate supports innovation, but also increases uncertainty around supply chain disruptions. The COVID-19 pandemic clearly shows the lack of resilience in supply chains and the impact that disruptions may have on a global network scale as individual supply chain connections and nodes fail. This cascading failure underscores the need for the network analysis and advanced resilience analytics we find lacking in the existing supply chain literature. This paper reviews supply chain resilience literature that focuses on resilience modeling and quantification and connects the supply chain to other networks, including transportation and command and control. We observe a fast increase in the number of relevant papers (only 47 relevant papers were published in 2007–2016, while 94 were found in 2017–2019). We observe that specific disruption scenarios are used to develop and test supply chain resilience models, while uncertainty associated with threats including consideration of “unknown unknowns” remains rare. Publications that utilize more advanced models often focus just on supply chain networks and exclude associated system components such as transportation and command and control (C2) networks, which creates a gap in the research that needs to be bridged. The common goal of supply chain modeling is to optimize efficiency and reduce costs, but trade-offs of efficiency and leanness with flexibility and resilience may not be fully addressed. We conclude that a comprehensive approach to network resilience quantification encompassing the supply chain in the context of other social and physical networks is needed to address the emerging challenges in the field. The connection to systemic threats, such as disease pandemics, is specifically discussed.

Analytic Hierarchy Process-Based Construction Material Selection for Performance Improvement of Building Construction: The Case of a Concrete System Form

Selecting the best materials that ensure maximum performance is crucial in the construction engineering design of any construction project. However, this is challenging and usually not properly considered because of the lack of systematic and scientific evaluation methods for the performance of materials. This paper proposes a new approach of selecting material to satisfy the performance goal of material designers in building constructions based on the analytic hierarchy process method. To validate the suggested model, a case study was conducted for a concrete system form, the performance of which is susceptible to its materials and has a strong effect on overall project productivity. The newly developed form comprising polymers and alloys showed that the proposed material selection model provided a better combination of materials, and the solution was technically more advanced and ensured better performance. This paper contributes to the body of knowledge by expanding the understanding of how construction material properties affect project performance and provides a guideline for material engineers to select the best-performing building materials while considering a performance goal.

Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic

The increasingly global context in which businesses operate supports innovation, but also increases uncertainty around supply chain disruptions. The COVID-19 pandemic clearly shows the lack of resilience in supply chains and the impact that disruptions may have on a global network scale as individual supply chain connections and nodes fail. This cascading failure underscores the need for the network analysis and advanced resilience analytics we find lacking in the existing supply chain literature. This paper reviews supply chain resilience literature that focuses on resilience modeling and quantification and connects the supply chain to other networks, including transportation and command and control. We observe a fast increase in the number of relevant papers (only 47 relevant papers were published in 2007-2016, while 94 were found in 2017-2019). We observe that specific disruption scenarios are used to develop and test supply chain resilience models, while uncertainty associated with threats including consideration of "unknown unknowns" remains rare. Publications that utilize more advanced models often focus just on supply chain networks and exclude associated system components such as transportation and command and control (C2) networks, which creates a gap in the research that needs to be bridged. The common goal of supply chain modeling is to optimize efficiency and reduce costs, but trade-offs of efficiency and leanness with flexibility and resilience may not be fully addressed. We conclude that a comprehensive approach to network resilience quantification encompassing the supply chain in the context of other social and physical networks is needed to address the emerging challenges in the field. The connection to systemic threats, such as disease pandemics, is specifically discussed.

Green-Building-Material Supplier Selection with a Rough-Set-Enhanced Quality Function Deployment

Building material supplier evaluation and selection is a significant strategic-decision problem for reducing construction costs and ensuring the quality of a residential product. As people are increasingly concerning about the green level of a residential product and the competition in the housing market is becoming increasingly fierce, it becomes important to select a green customer-oriented material supplier for property developers. Quality function deployment (QFD) has been proven to be an effective quality-control technique to take customer voices into consideration. However, the relationship matrix in the QFD technique, as a key to translate customer requirements into technical attributes, was subjectively given by decision-makers in previous studies, which failed to reflect customer requirements accurately. The aim of this study is to put forward a neighborhood-rough-set-based quality function deployment model for a green-building-material supplier selection. The neighborhood rough set, as a nonparametric and flexible data-mining approach, can effectively and objectively determine the core relationships between a variety of factors. A rough number-based aggregation approach is applied to effectively and objectively aggregate the evaluations given by a group of experts. Then, the classical double normalization-based multiple aggregation method, which considers two types of normalization methods, three aggregation models, and a comprehensive score formula, is extended in rough-number form in order to rank the alternatives. Afterward, an attempt is made to evaluate and rank eleven alternative building-material suppliers for a repute property developer in mainland China, and the corresponding comparative and sensitive analyses verify the effectiveness and robustness of the proposed hybrid model.

An Efficient Ensemble VTOPES Multi-Criteria Decision-Making Model for Sustainable Sugarcane Farms

The role of Information Technology based decision models for sustainable agriculture has gained immense prominence in recent years. Ranking of agriculture farms based on their yield plays a vital role in sustainable agriculture. In this work, an ensemble decision-making model, namely VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje), TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), entropy, and standard deviation (VTOPES), is proposed for ranking the sustainable sugarcane farms. VTOPES system model comprises of four significant steps: (i) determination of significance scores of the sub-parameters, (ii) transformation of sub-parameter sequences into main parameter values, (iii) computation of significant scores of main parameters, and (iv) generation of assessment values and deploying it for ranking the sugarcane farms. The ranking results of the proposed VTOPES model are compared with the ranking patterns obtained from five years average yield data acquired from the selected sugarcane farms. Moreover, the outcomes of the VTOPES model are also compared with other prevalent methods. Subsequently, Spearman’s rank correlation method is applied for evaluating the impact of correlation of VTOPES ranks in comparison with the average yield ranks. Thus, it can be noticed that the empirical results of the VTOPES model provide reliable and sustainable results. Therefore, it suffices to be a sustainable decision model for any problem where multiple parameters are involved.

Maintenance Supplier Evaluation and Selection for Safe and Sustainable Production in the Chemical Industry: A Case Study

Chemical industry plays a pivotal role in the economy in every country. As chemical hazardous materials are usually characterized as inflammable, explosive, toxic, corrosive, and carcinogenic, if accidents happen in chemical company it can lead to irreversible environmental and health damage to the public. The chemical industry attaches great importance to safe production, technical professionalism, and service standardization. Nowadays, under the trend of equipment maintenance service outsourcing in chemical companies, the selection of maintenance suppliers with safe and sustainable records come first and foremost in the supplier selection process. However, these concerns from the chemical industry are currently inadequately addressed by most general supplier selection models. Therefore, this paper proposes an applicable methodology for selecting and evaluating equipment maintenance suppliers in the chemical industry, compatible with a safe and sustainable production context. To achieve the goal of “safe operation and sustainable development in the future”, we established an evaluation criteria framework for equipment maintenance suppliers by combining the general supplier selection criteria and safe production characteristics together. Eight main criteria and 24 sub-criteria based on market acceptance, resource conditions, and safe production were included. Then a fuzzy TOPSIS model was presented to select the best equipment maintenance service supplier. Finally, by analyzing a case in W petrochemical company, the empirical results indicate that the proposed framework is of great practical value to select and evaluate equipment maintenance suppliers for safety and sustainable development in the chemical industry.

Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain

Modern supply chains are vulnerable to high impact, low probability disruption risks. A supply chain usually operates in such a network of entities where the resilience of one supplier is critical to overall supply chain resilience. Therefore, resilient planning is a key strategic requirement in supplier selection decisions for a competitive supply chain. The aim of this research is to develop quantitative resilient criteria for supplier selection and order allocation in a fuzzy environment. To serve the purpose, a possibilistic fuzzy multi-objective approach was proposed and an interactive fuzzy optimization solution methodology was developed. Using the proposed approach, organizations can tradeoff between cost and resilience in supply networks. The approach is illustrated using a supply chain case from a garments manufacturing company.

Supply chain resilience: a systematic literature review and typological framework

Purpose

The study of supply chain resilience (SCRES) continues to gain interest in the academic and practitioner communities. The purpose of this paper is to present a focused review of the SCRES literature by investigating supply chain (SC) capabilities, their relationship to SCRES outcomes and the underpinning theoretical mechanisms of this relationship.

Design/methodology/approach

The paper uses the systematic literature review approach to examine 383 articles published between 2000 and 2017, ultimately down selecting to the most relevant 228 peer-reviewed studies. Context-interventions-mechanisms-outcomes (CIMO) logic is applied to organize and synthesize these peer-reviewed studies. A typological framework is developed from the CIMO-based classification of the SCRES literature.

Findings

The findings of this study outline the gaps in the SCRES literature and present an agenda for future research.

Research limitations/implications

This paper presents an exploratory research; therefore, the typological model presented is just one of the possible perspectives.

Practical implications

The typology of SCRES literature can help practitioners to understand SCRES and to measure and assess the resilience of SCs.

Originality/value

The paper provides clear definitions of SCRES constructs, develops a typological framework to further understand SCRES and identifies SCRES measures and assessment techniques.

Balanced scorecard-based performance evaluation of Chinese county hospitals in underdeveloped areas

Objective Since the Guangxi government implemented public county hospital reform in 2009, there have been no studies of county hospitals in this underdeveloped area of China. This study aimed to establish an evaluation indicator system for Guangxi county hospitals and to generate recommendations for hospital development and policymaking. Methods A performance evaluation indicator system was developed based on balanced scorecard theory. Opinions were elicited from 25 experts from administrative units, universities and hospitals and the Delphi method was used to modify the performance indicators. The indicator system and the Topsis method were used to evaluate the performance of five county hospitals randomly selected from the same batch of 2015 Guangxi reform pilots. Results There were 4 first-level indicators, 9 second-level indicators and 36 third-level indicators in the final performance evaluation indicator system that showed good consistency, validity and reliability. The performance rank of the hospitals was B > E > A > C > D. Conclusions The performance evaluation indicator system established using the balanced scorecard is practical and scientific. Analysis of the results based on this indicator system identified several factors affecting hospital performance, such as resource utilisation efficiency, medical service price, personnel structure and doctor-patient relationships.