TEA-IS: A hybrid DEA-TOPSIS approach for assessing performance and synergy in Chinese health care

2023 | Decision Support Systems | Citations: 0

Authors: Antunes, Jorge; Hadi-Vencheh, Abdollah; Jamshidi, Ali; Tan, Yong; Wanke, Peter

Abstract: This paper presents an assessment of the Chinese healthcare system in 31 provinc ... Expand

Abstract: This paper presents an assessment of the Chinese healthcare system in 31 provinces for a 10-year period in light of relevant physical and human resource variables. First, a novel TEA-IS (Trigonometric Envelopment Analysis for Ideal Solutions) model is developed to assess healthcare efficiency at the province level. Machine learning methods are also employed to predict high-low performance and the synergistic Chinese healthcare province in terms of contextual variables. The results indicate that synergy has played a pivotal role in the Chinese healthcare systems, not only by triggering higher performance levels due to the progressive adoption of best practices over the course of time, but also by being closely related to different socioeconomic and demographic variables, such as the illiteracy rate. It is possible to claim that healthcare performance has remained stable in China over the past two decades, performance and synergy at the province level are still heterogeneous. Collapse

Topics: health information system IT productivity human resource management service quality productivity

Methods: TOPSIS trade-off analysis method machine learning artificial neural network literature study

Value Implications of Sourcing Electronic Health Records: The Role of Physician Practice Integration

2023 | Information Systems Research | Citations: 0

Authors: Bardhan, Indranil R.; Bao, Chenzhang; Ayabakan, Sezgin

Abstract: Should hospitals source electronic health records (EHR) systems from a single ve ... Expand

Abstract: Should hospitals source electronic health records (EHR) systems from a single vendor or multiple vendors to deliver high-value care? We study hospitals’ EHR sourcing strategies based on their degree of integration with physician practices and its impact on the value of healthcare delivered. We propose a novel framework to define healthcare value as the extent to which a hospital effectively expends clinical resources to deliver services that improve patient outcomes. Drawing on modular systems and transaction cost economics theories, we propose a moderated-mediation model that explores the pathways through which EHR sourcing strategies can create value in healthcare. We test our research hypotheses on a large, longitudinal sample of U.S. hospitals and observe that hospitals with EHR configurations closer to single sourcing strategies exhibit greater health information sharing compared with hospitals with multisourced EHR systems. Furthermore, we find that hospital-physician practice integration moderates the impact of single sourcing on health information sharing, which in turn, improves value. Specifically, tighter integration between hospitals and physician practices can create greater value if it is aligned with hospitals’ EHR sourcing strategies. As the healthcare industry moves toward value-based payment reform, our findings provide a useful roadmap to practitioners and policy makers to improve the performance of hospitals and healthcare providers. History: Rajiv Kohli, Senior Editor; Sunil Wattal, Associate Editor. Funding: I.R. Bardhan thanks the Foster Parker Centennial Professorship and the Dean’s Research Excellence Grant at the McCombs School of Business at UT Austin for generous financial support. C. Bao thanks the Spears Fellowship at Oklahoma State University for financial support. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1183. Collapse

Topics: information exchange healthcare data health information system accounting database system

Methods: longitudinal research survey robustness check econometric modeling design artifact

Theories: transaction cost economics general systems theory institutional theory

How Tourist Group Books Hotels Meeting the Majority Affective Expectations: A Group Selection Frame with Kansei Text Mining and Consensus Coordinating

2023 | Group Decision and Negotiation | Citations: 0

Authors: Chang, Jia-Li; Li, Hui; Wu, Jian

Abstract: The decision on which hotel to book is a high-cost process for individuals and e ... Expand

Abstract: The decision on which hotel to book is a high-cost process for individuals and even more for groups due to the information explosion on online travel agent platforms. To assist group selecting the optimal hotel that meets the majority affective expectations, this study proposes a group hotel selection frame for booking with Kansei text mining and consensus coordinating. Firstly, to quantify the tourists’ affective needs for hotels, a Kansei-related dictionary towards hotel domain is constructed by Kansei text mining. Secondly, the bilattice-based Kansei score of hotels is defined and measured to represent hotel affective information scientifically. Then, a group consensus model with minimum adjustment cost is introduced to coordinate consistency of individual preferences in a tourist group. Moreover, a group hotel ranking based on group affective preference is interactively generated to meet the group personalized demands. Finally, a case study on Trip.com is conducted to demonstrate the proposed method. Collapse

Topics: knowledge representation online review personality website

Methods: natural language processing word2vec computational algorithm sentiment analysis case study

Artificial intelligence for decision-making and the future of work

2023 | International Journal of Information Management | Citations: 0

Authors: Dennehy, Denis; Griva, Anastasia; Pouloudi, Nancy; Mäntymäki, Matti; Pappas, Ilias

Abstract: ... Expand

Abstract: Collapse

Topics: artificial intelligence human computer interaction human in the loop data governance data quality

Methods: chatbot case study theory development analytic hierarchy process trade-off analysis method

Theories: institutional theory

Causal Relationship and Ranking Technique (CRRT): A Novel Group Decision-Making Model and Application in Students’ Performance Assessment in Indian High School Context

2023 | Group Decision and Negotiation | Citations: 0

Authors: Dhara, Suvojit; Goswami, Adrijit

Abstract: In the field of multi-attribute group decision-making (MAGDM), “decision-making ... Expand

Abstract: In the field of multi-attribute group decision-making (MAGDM), “decision-making trial and evaluation laboratory” (DEMATEL) is a popular method that has been deployed to discover hidden relationships among many inter-twined factors of numerous real-world problems. This paper discusses several limitations of the DEMATEL method in mining the causal relationships and ranking the factors. Also, in this paper, we develop a novel decision-making framework that will be able to overcome the issues found in the DEMATEL method and tackle both formal and informal decisions. This model, which we call “Causal Relationship and Ranking Technique (CRRT)”, uses a data-deterministic expert weighing setup rather than assigning equal weights or pre-defined weights to each expert. The model proposes a better technique to mine factor inter-relations and proposes two new types of digraphs portraying the causal inter-relationships among the factors, and also proposes a new two-step factor ranking method based on the derived causal relationships. The intuitionistic fuzzy setting is considered in this work in order to capture the uncertainty of expert opinions. Furthermore, our proposed framework is applied to a real-life case study on discovering various factors of a high school administration, that have a significant influence on students’ performance. Comparison with standard methods such as TOPSIS and VIKOR for student performance data and also some other datasets such as supplier selection data, and sustainability data proves that the model is able to rank the factors better than the existing models. Collapse

Topics: decision making

Methods: case study TOPSIS trade-off analysis method cross sectional research descriptive statistic

Consensus-trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large-group Decision Making

2023 | Group Decision and Negotiation | Citations: 0

Authors: Gai, Tiantian; Cao, Mingshuo; Chiclana, Francisco; Zhang, Zhen; Dong, Yucheng; Herrera-Viedma, Enrique; Wu, Jian

Abstract: This paper proposes a consensus-trust driven framework of bidirectional interact ... Expand

Abstract: This paper proposes a consensus-trust driven framework of bidirectional interaction for social network large-group decision making. Firstly, the concepts of interaction consensus threshold and interaction trust threshold are defined, which are used to discriminate the interaction modes between subgroups into four categories. Corresponding hybrid feedback strategies are designed in which the consensus level and trust level of subgroups are regarded as reliable resources to facilitate the achievement of group consensus. Secondly, a minimum adjustment bidirectional feedback model considering cohesion is developed to help the interacting subgroups reach mutual consensus with minimum opinion modification. Finally, the proposed consensus framework is applied to a blockchain platform selection problem in supply chain to demonstrate the effectiveness and applicability of the model. Collapse

Topics: blockchain supply chain management decision making social network

Methods: computational algorithm simulation social network analysis trade-off analysis method multi objective optimization

"YOU CAN'T ALWAYS GET WHAT YOU WANT": EXAMINING EMPLOYEES' PREFERENCES AND JOB SATISFACTION IN AGILE TRANSFORMATIONS

2023 | European Conference On Information Systems | Citations: 0

Authors: Fischer, Mareike; Heinz, Matthias; Schlereth, Christian; Rosenkranz, Christoph

Abstract: Agile transformations cause fundamental changes to work designs. To better unde ... Expand

Abstract: Agile transformations cause fundamental changes to work designs. To better understand resistance to transformations, we shed light on employee preferences and the consequences of team and work organization changes for job satisfaction. Using the stated preference method "pairwise comparisonbased preference measurement", we examine our hypothesis on job satisfaction in agile vs. traditional team and work organization. Furthermore, we relate job satisfaction to the gap between perceived and preferred forms of such organizations. In summary, we identified team organization as the most important dimension in agile transformations. For requirements engineering, the distance between employee preferences and the perceived status quo was particularly large. Further, we found evidence that a larger distance between team and work organization preferences and perceptions negatively influenced job satisfaction. Collapse

Topics: job satisfaction marketing management IT personell turnover business model new product development

Methods: survey statistical hypothesis test linear regression analysis conjoint analysis Student's t-test

Influence of digital transformation on the servitization level of manufacturing SMEs from static and dynamic perspectives

2023 | International Journal of Information Management | Citations: 0

Authors: Gao, Jing; Zhang, Wanfei; Guan, Tao; Feng, Qiuhong; Mardani, Abbas

Abstract: The servitization transformation is an important strategic planning and developm ... Expand

Abstract: The servitization transformation is an important strategic planning and development trend for Chinese small and medium-sized enterprises (SMEs) in manufacturing to break through the low-end locking of the global value chain and achieve high-quality transformation and upgrading. Digital transformation is a new expansion and the main focus of technology and service innovation in the process of enterprise servitization. To comprehensively evaluate the development status of Chinese manufacturing enterprises’ servitization level and explore the het­ erogeneity effect of digital transformation on enterprise servitization level, this study conducts the following research. By analyzing the influencing factors of manufacturing SMEs’ servitization level and the mechanism of digital transformation, this study combines the panel data of SMEs in manufacturing from 2015 to 2020 and evaluates their servitization levels from static and dynamic perspectives using super-efficiency data envelopment analysis (DEA) and Malmquist index methods. Furthermore, this study examines the influence of digital trans­ formation on the servitization level of SMEs in manufacturing by using a digital input index and scenario comparison and analyzes the heterogeneous effects according to industry type. The results show that the ser­ vitization level of Chinese SMEs in manufacturing is not high, and its development is not balanced. Digital transformation plays a significant role in promoting the servitization of SMEs in manufacturing. The effect has obvious heterogeneity owing to differences in industry type. The research results can provide countermeasures and suggestions for the digitalization and servitization innovation development of SMEs in manufacturing, which can promote high-quality transformation and upgrading of Chinese SMEs in manufacturing and increase their position in the global value chain. Collapse

Topics: digital transformation innovation management electronic business productivity big data

Methods: longitudinal research data envelopment analysis trade-off analysis method Student's t-test parametric test

Driving risk prevention in usage-based insurance services based on interpretable machine learning and telematics data

2023 | Decision Support Systems | Citations: 0

Authors: Li, Hong-Jie; Luo, Xing-Gang; Zhang, Zhong-Liang; Jiang, Wei; Huang, Shen-Wei

Abstract: Usage-based insurance (UBI) adjusts premiums based on an individual policyholder ... Expand

Abstract: Usage-based insurance (UBI) adjusts premiums based on an individual policyholder’s dynamic risk evaluation, incentivizing policyholders to maintain safe driving behavior in pursuit of a lower insurance premium. Although post-trip interventions can improve driving behavior significantly, most interventions do not provide risk mitigation strategies tailored to long-term driving behavior. This study proposes a novel approach for driving risk prevention in UBI services, providing risk analysis services and tailoring driving suggestions for policyholders. Advanced prediction models and model interpretation methods were adopted to assess and analyze personal driving risks, respectively. A multi-objective counterfactual model was developed to generate risk mitigation strategies for policyholders. The significance of driving behavior in risk mitigation and its actionability were assessed to provide realistic and actionable suggestions for policyholders. The case study, based on a real dataset from an insurance company in China, showed that the proposed approach can be directly embedded in the existing UBI service framework to provide personalized feedback and services to policyholders. Collapse

Topics: shapley additive explanation decision support system Python decision making logistics management

Methods: experiment computational algorithm machine learning XGBoost factor analysis

Uncertainty Analysis in Group Decisions through Interval Ordinal Priority Approach

2023 | Group Decision and Negotiation | Citations: 0

Authors: Mahmoudi, Amin; Javed, Saad Ahmed

Abstract: In multiple criteria decision-making (MCDM) problems, ranking alternatives is us ... Expand

Abstract: In multiple criteria decision-making (MCDM) problems, ranking alternatives is usually the end. However, in real life, it is rarely an end in itself and serves as a means to an end. Further, in real-life problems, the selection of alternatives is usually made with the aid of unique experts, and thus minimizing the influence of the uncertainty of their subjective judgements on the optimality of the decisions is a critical issue. The current study proposes a novel Interval Ordinal Priority Approach to objectively solve these and other issues by allowing uncertainty analysis and quantification. The study argues that when the model’s input contains uncertainty (even if represented by crisp numbers), expecting the output to be free from uncertainty is an unrealistic conjecture. Therefore, unlike the conventional MCDM models producing crisp weights, the proposed approach yields interval weights with the length of the interval representing the uncertainty (inconsistency among the experts’ judgements). Also, instead of resorting to the subjective measurement of thresholds to qualify or disqualify a set of inputs based on the degree of uncertainty, a novel objective measure of threshold is put forward. The validity of the proposed method is demonstrated through illustrative examples and comparative analysis. Later, the study is concluded with the implications for real-world decision-making. Collapse

Topics: decision making decision support system

Methods: descriptive statistic cross sectional research statistical hypothesis test trade-off analysis method Grey relational analysis

Theories: mathematical theory