Actual Decisions Research Articles

Videoconferences in higher education: The good frame

The Coronavirus lockdown in 2020 pushed videoconference technology as a common means of synchronous communication for emergency remote teaching in Higher Education. In a short period of time, educators and students had to use cameras and stream their images over the Internet to keep on with academic interaction from home. But not all stakeholders had the same experience using this type of communication means, and their values and perceptions on what was an appropriate framing style for educational purposes yielded different types of camera compositions, not all agreeable to watch. To study videoconferencing framing among University stakeholders, a two-tier intervention was conducted to inquire about the values and perceptions of educators, and to observe the actual production decisions they made before and during a videoconference for educational purposes. In this paper, the video references and framing preferences of 6031 teachers were analysed, and a set of categories were constructed and used to conduct observations of 1111 videoconference frames. The findings were used to understand the production decisions academic stakeholders took for the spontaneous production of their home-made real-time video for virtual classes.Keywords: Visual literacy; videoconference; virtual education; academic continuity; higher education; emergency remote teachingPart of the Special Issue Visual literacies and visual technologies for teaching, learning and inclusion <https://doi.org/10.21428/8c225f6e.bf2afe2e>

Model for evaluating the security of wireless sensor network with fuzzy number intuitionistic fuzzy information

Many experts and scholars focus on the Maclaurin symmetric mean (MSM) equation, which can reflect the interrelationship among the multi-input arguments. It has been generalized to different fuzzy environments and put into use in various actual decision problems. The fuzzy data intuitionistic fuzzy numbers (FNIFNs) could well depict the uncertainties and fuzziness during the security evaluation of Wireless Sensor Network (WSN). And the WSN security evaluation is frequently viewed as the multiple attribute decision-making (MADM) issue. In this paper, we expand the generalized Maclaurin symmetric mean (GMSM) equation with FNIFNs to propose the fuzzy number intuitionistic fuzzy generalized MSM (FNIFGMSM) equation and fuzzy number intuitionistic fuzzy weighted generalized MSM (FNIFWGMSM) equation in this study. A few MADM tools are developed with FNIFWGMSM equation. Finally, taking WSN security evaluation as an example, this paper illustrates effectiveness of the depicted approach. Moreover, by comparing and analyzing the existing methods, the effectiveness and superiority of the FNIFWGMSM method are further certified.

Creating informed consumers of aquatic invasive species management programs through online education for nonprofessionals

AbstractThere are limited educational opportunities regarding aquatic invasive species (AIS) management that target laypersons. This is a significant gap, particularly as nonprofessionals are often tasked with making decisions about whether and how to pursue AIS control efforts, for example, through their roles in community lake associations. Thus, there is a need for educational programs to help consumers of AIS management services, “do-it-yourself” lakeshore homeowners, and other engaged nonprofessionals gain a stronger foundation in the science and practice of AIS management. We helped fill this unmet need through development of a new online course, AIS Management 101, that targets lakeshore property owners, lake association members, and other nonprofessionals engaged in AIS decision making, seeking to make them better-informed consumers. The course covers concepts ranging from basic invasive species biology to pesticide science, treatment evaluation, regulations and permitting, and nonchemical management tools. Participants in the course demonstrated significant knowledge gains through check-in and check-out knowledge assessments. Course participants also reported greater understanding of key issues pertaining to AIS management and application of this improved knowledge to actual management decisions following completion of the course. While this program focuses on management ofaquaticinvasive species, similar approaches could be applied to lay audiences engaged in management of terrestrial invasive species or other natural resource issues.

Accuracy of the International Consensus Scoring System for diagnosis of periprosthetic joint infection in revision shoulder arthroplasty

BackgroundTotal shoulder arthroplasty (TSA) continues to undergo dramatic growth with expanding indications and improvements in implants and surgical techniques. A major complication following TSA is periprosthetic joint infection (PJI), which remains difficult to diagnose, often relying on clinical judgment. A contemporary definition of PJI was established at the 2018 International Consensus Meeting (ICM) on Musculoskeletal Infection. We sought to retrospectively examine the accuracy of this scoring system in previously performed revision TSA and hypothesized that the ICM scoring system would be reliable in determining the presence of TSA PJI. MethodsOur institutional database was reviewed to identify patients undergoing revision TSA before the advent of the ICM PJI scoring system. Clinical notes and operative reports were reviewed for data regarding the preoperative clinical examination, laboratory values, and intraoperative findings. The findings were assigned scores based on the definition of probable PJI by the ICM scoring system. Scores were compared to treatment plans of infected vs. noninfected patients. The diagnosis of PJI was made using a combination of clinical examination, laboratory values, and intraoperative findings. Sensitivity, specificity, positive and negative predictive values, and accuracy of the ICM scoring system were calculated compared to actual treatment decision, the gold standard. ResultsOf 81 revision arthroplasties, 52 were revision reverse TSA (rTSA), and 29 were revision anatomic TSA (aTSA). Seven rTSA patients were treated as infected (7/52, 13.5%), and the scoring system identified 4 of those as being probable infections (4/7, 57.1%). One additional rTSA patient scored as probable infection, underwent a revision for instability, and was found to have no infection. Three aTSA patients were treated as infected (3/29, 10.3%), with one of those identified as probable infection by the scoring system (1/3, 33.3%). Four patients in the rTSA group and no patients in the aTSA group met the criteria for definite infection. Using the threshold of probable infection to identify PJI, the sensitivity of the scoring system was 0.6, and specificity was 0.99. The positive predictive value was 0.86, and the negative predictive value was 0.95. With the same threshold, the ICM scoring system was 93.8% accurate. ConclusionsIdentifying PJI in TSA remains difficult in the absence of definite signs of joint sepsis. This study found the scoring system to be highly accurate, although with modest sensitivity, and a reliable tool for the diagnosis of PJI following TSA. Level of evidenceLevel IV; Retrospective Case Series with No Comparison Group Treatment Study

Application of cumulative prospect theory in understanding energy retrofit decision: A study of homeowners in the Netherlands

Retrofitting residential buildings can help mitigate the effects of climate change. Cognitive biases are systematic deviations from rationality in decision making and can lead to inaction, delay, and uncertain decisions. Understanding the cognitive biases involved in residential renovation decisions and developing interventions to overcome them can help increase residential renovation rates. Despite their importance, few studies have examined the impact of cognitive biases on energy retrofits. The question addressed in this study is: “Can accounting for cognitive biases improve the prediction of homeowners’ actual investment decisions, and how can the outcomes be used to recommend potential behavioural interventions?”. Expected Utility Theory (EUT) and Cumulative Prospect Theory (CPT) are compared to evaluate which model(s) more accurately describes actual decision-making behaviour regarding energy retrofits. The EUT assumes a rational decision maker. The CPT is a quantitative model that assumes a decision-maker operating under risk and uncertainty and subject to the cognitive biases of reference dependence, loss aversion, decreasing sensitivity, and probability weighting. The influences of cognitive biases on energy retrofit decisions can be quantified if the relative performance of CPT versus EUT is more accurate. The data for these analyses come from housing surveys conducted in the Netherlands in 2012 and 2018, which also collected data on energy modules. 2,784 and 2,878 homeowners were surveyed, respectively. The model is validated by estimating the coefficients of EUT and CPT and identifying the similarities and differences between the results of the two datasets. Before estimating the parameters, four household clusters are identified using grey relational analysis and the K-Means cluster. For the first time, the EUT and CPT parameters are estimated for four clusters and two energy retrofits, double glazing and insulation, using a genetic algorithm because the equations are nonlinear. The results confirm that CPT provides a better description of the actual decision behaviour than EUT using the two previously established initial values of Layard et al. (2008) and Häckel et al. (2017) as well as the parameters estimated by the genetic algorithm. In the latter case, CPT correctly predicts the decisions of 86% of homeowners to renovate their homes to be energy efficient or not. EUT, on the other hand, overestimates the number of decisions to renovate: it incorrectly predicts retrofit for 52% of homeowners who did not renovate for energy efficiency reasons. Using the estimated parameters of CPT, the cognitive biases of reference dependence, loss aversion, diminishing sensitivity, and probability weighting can be clearly seen for different target groups. The groups with the highest average incomes and house values had the highest loss risk aversion parameters. These households invested more in installing insulation and double glazing.

The subjective evaluation of task switch cues is related to voluntary task switching

Task switching refers to the effortful mental process of shifting attention between different tasks. While it is well-established that task switching usually comes with an objective performance cost, recent studies have shown that people also subjectively evaluate task switching as negative. An open question is whether this affective evaluation of task switching is also related to actual decision making. In this pre-registered study, we therefore examined whether individual differences in the negative evaluation of task switch cues are related to less voluntary task switching. To this end, participants first performed a cued task switching paradigm where abstract cues signaled task transitions (repetition or alternation). In a second phase, these transition cues were used as prime stimuli in an affective priming procedure to assess participants' affective evaluation of task switching. In a third phase, participants were allowed to freely choose whether to switch or repeat tasks. We found that a more negative evaluation of task switching cues was related to lower switch rates in the voluntary task switching phase. This finding supports neuroeconomic theories of value-based decision making which suggest that people use their subjective value of control to decide whether to engage in (different) tasks.

Capacity planning and production scheduling integration: improving operational efficiency via detailed modelling

Successful capacity planning and production scheduling is built on the understanding of market opportunities and the costs of capacity, production, sourcing, inventory, and distribution over the planning horizon. Increasingly, companies attempt to integrate capacity planning and production scheduling to improve upon the commonly used sequential decision process, but most related research works fail to capture the granularity of actual operational decisions and therefore may overlook potential cost-saving opportunities. The contributions of this study include: (1) a detailed integrated capacity and production scheduling model with multiple discrete and continuous options for varying short and medium-term capacity, (2) a heuristic algorithm that exploits the problem structure to solve the nonlinear mixed integer problem, (3) an evaluation of the value of the integrated model relative to traditional practice and its sensitivity to parameters, (4) a review of past contributions to integrated planning, particularly focused on IJPR, and (5) a case study originated from a world-class automobile manufacturer illustrating how the model can be applied and confirming its value relative to hierarchical and less detailed modelling approaches.

PREFERENCE AGGREGATION MODEL CONSTRUCTION OF GROUP MANAGEMENT DECISION-MAKING BASED ON RELATIVE ENTROPY AND NORM OPERATOR

Due to the complexity of the problem in the actual group management decision, the ambiguity of the information of all parties and the uncertainty of the decision environment, it is often difficult for decision-makers to describe the decision information by quantitative methods, but to give uncertain linguistic variables. Based on the analysis of previous research results, this paper proposes a group management decision-making aggregation model based on relative entropy and norm operator. First, the model uses the operation of [Formula: see text]-norm and new [Formula: see text]-norm operator to make the fuzzy set satisfy the ranking rate and contradiction rate. Then, based on the reliability of relative entropy, the attribute weights of different expert decisions are obtained, and the optimal assembly model of the corresponding group decision is established, respectively. The optimal solution and decision algorithm are given for each optimization model. The last example of the algorithm proves the validity and feasibility of the model, and can effectively avoid the distortion and distortion in the process of group management decision preference aggregation.

Diagnostic Policies Optimization for Chronic Diseases Based on POMDP Model

During the process of disease diagnosis, overdiagnosis can lead to potential health loss and unnecessary anxiety for patients as well as increased medical costs, while underdiagnosis can result in patients not being treated on time. To deal with these problems, we construct a partially observable Markov decision process (POMDP) model of chronic diseases to study optimal diagnostic policies, which takes into account individual characteristics of patients. The objective of our model is to maximize a patient’s total expected quality-adjusted life years (QALYs). We also derive some structural properties, including the existence of the diagnostic threshold and the optimal diagnosis age for chronic diseases. The resulting optimization is applied to the management of coronary heart disease (CHD). Based on clinical data, we validate our model, demonstrate how the quantitative tool can provide actionable insights for physicians and decision makers in health-related fields, and compare optimal policies with actual clinical decisions. The results indicate that the diagnostic threshold first decreases and then increases as the patient’s age increases, which contradicts the intuitive non-decreasing thresholds. Moreover, diagnostic thresholds were higher for women than for men, especially at younger ages.

Making Better (Investment) Decisions by Robert C. Jones (2016): A Journal Review

This article presents a review on the Journal of Robert C. Jones “Making Better Investment Decisions”. The vast literature and academic debates in finance presents a wide array of conceptual and theoretical frameworks on investing and decision making. Robert C. Jones, a Certified Financial Analyst, is an advocate of active investing and is affiliated with Systems Two Advisors. His works revolve around practical applications of making better (investment) decisions, active management in investments and machine learning for stock selection to name a few. His background is reflected in this article under critique, “Making Better (Investment) Decisions” which was published in 2016. In this article, Jones centered on how people make actual investment decisions, and presented advice on how to make better decisions. The main idea of his article states that a decision-making advantage is more feasible than an information advantage. This article is coherently organized, such that the first half presented a review of literature from cognitive psychology about how people make decisions, what are the persistent biases in human judgment and why they arise particularly emphasizing on the implications for investors. In the second part, this article discussed several established practices to improve decision making, especially centered on how investors may possibly use them.

A Political Agenda in Conflict with Environmental Protection: A Critical Policy Essay from Brazil

Current Brazilian policies on environmental protection have become a worldwide concern since President Bolsonaro’s election in 2018. Not only have his speeches been aggressive and critical of environmental protections, but many of his actual decisions have shown a very dangerous negligence of populations and interests affected by environmental harms. As a consequence, different environmental crises have plagued the country without any adequate response by public agencies or emergency plans to diminished harms. This essay uses a regulatory approach to demonstrate how the recent large withdrawal of environmental protection instruments in Brazil have supported a harmful and unlawful political agenda. First, we reconstruct the historical narrative of Brazilian environmental policy between the years 2018 and 2021, demonstrating through journalistic reports and social organizations’ alerts, how the speeches, actions and omissions of the Brazilian government may have contributed to the present environmental situation. Using an environmental justice perspective, we demonstrate a lack of legitimate influence on political decisions related to environmental protection. Subsequently, we discuss the existing legal instruments to respond to the political abuses in the Brazilian legal system, in order to demonstrate their insufficiency to deal with this scenario. Finally, we evaluate international criminal law as a possible answer to the ongoing environmental abuses in Brazil.

Smart farming technologies adoption: Which factors play a role in the digital transition?

Smart Farming Technologies (SFT) are smart devices part of a cyber-physical system able to improve farm management. Compared to other digital technologies' functionalities, SFT generate a multitude of data that once combined can be used not only on-farm but across the entire supply chain. Although recent studies highlighted how the lack of users’ resources and competences might hinder the diffusion of digital agriculture technologies overall, few studies so far focused specifically on SFT. Moreover, the extant literature interprets the adoption decision mostly as “one-off binary” process, and limited attention is given to individual aspects of users and farms. Therefore, this study investigates the adoption of SFT analyzing various aspects of its complex nature; on the one hand, the analysis considers the multi-step nature of the adoption decision process: first, intention formation and then, actual adoption decision. On the other hand, the SFT adoption process is interpreted as being determined by several typologies of determinants beyond the most studied ones, with a particular focus on the role that organizational conditions and the supply chain governance structure play in influencing farmers' adoption of SFT.An empirical analysis is run on a sample of 474 responses, collected through an on-line survey. Structural Equation Modeling (SEM) and a Zero-Inflated Poisson Regression (ZIP) were used to investigate respectively the intention to use and the actual adoption of SFT. Results show that farmers' intention to use mainly relies on technologies' performance expectancy, technologies' complexity and social influence exerted on farmers, while organizational supporting conditions do not play a significant effect. Nonetheless, when the actual adoption decision is observed, the likelihood that non-adopters intend to adopt SFT in their farms increases when formal integration along the supply chain is high and with the dimension of the farm (in terms of both land size and sales). When the adopters are analyzed instead, the decision to adopt is positively affected only by the individual intention to use and by farmers' specialization in the arable sector.Findings reveal what factors need to be considered to guarantee a fairer and more inclusive agricultural digitalization, such as the role of social influence exerted by some figures around farmers and the still weak facilitating organizational conditions.

Purchase intention and actual purchase of cargo cycles: Influencing factors and policy insights

To support the penetration of cargo cycles in commercial transport, this research aims at identifying the significant influencing factors for their purchase, using data from Europe’s largest cargo cycle testing project “Ich entlaste Städte”. This is achieved by developing binary logit models for the intention to purchase (stated at the end of a 3-month vehicle trial), and the actual purchase decision made (queried three months or later, after the end of the trial). Prior to the estimation of the logit models, latent variables have been constructed using explanatory factor analysis. Based on the estimation results, factors that influence the actual purchase decision include catchment area of cargo cycle trips, daily usage during the trial phase, trial phase season, type of cargo cycle tested, mode substituted by cargo cycles during the trial phase and business sector. Furthermore, four other factors, which are latent variables constructed through exploratory factor analysis, are found to have significant influence: perception of operational, soft and cost benefits, as well as importance of deterioration of conditions for conventional vehicles. Based on the influence of these factors, policy measures are suggested under the following categories: (i) Regulation, (ii) Infrastructure, (iii) Finance, (iv) Campaigns and (v) Trial schemes. The data from the project shows the existence of a difference between the intention and the actual purchase decision (around 50% higher intent compared to realized purchase). This implies that there is a need to convert intention to actual decision, when making conclusions based on intention. A comparison, made between the binary logit models of intention and actual purchase decision, brings out the reality that the latter is influenced by hard facts like the deteriorating conditions (e.g., vehicle access restrictions) for conventional vehicles, while the former is influenced by operational concerns towards cargo cycles. This observation suggests the necessity of formulating measures to foster the market penetration of cargo cycles.

Understanding the decision-making process in homeowner energy retrofits

In 2020, owner-occupied housing accounted for 57% of the housing stock in the Netherlands. Homeowners are fully responsible for the implementation of energy retrofits. Moreover, the processes of energy retrofitting are complex and homeowners face problems such as finding financial support, reliable information and contractors. The complexity of implementing energy retrofits may discourage homeowners from continuing the process and achieving the expected benefits. Behavioural aspects and transaction costs (TC) are among the most important factors influencing consumer decision-making processes. Behavioural factors primarily illustrate a range of personal, contextual, and external factors that influence the decision-making process of homeowners. These include cognitive awareness and biases, attitudes and beliefs, experience and skills, homeowner characteristics, sociodemographic characteristics, property characteristics, and the behaviour of others. TC are any hidden costs that influence decision making but are not included in the direct physical costs of renovation services and products. This dissertation developed an integrated framework of behavioural factors and TC that impede the decisionmaking process for energy retrofits. Key findings include (1) the significant importance of behavioural factors and TC barriers. (2) the behavioural factors are particularly important in the early stages of energy retrofits and the TC barriers after the final decision. (3) the importance of behavioural factors and TC barriers differs according to the type of energy retrofit and non-energy retrofit. (4) Accounting for cognitive biases significantly improves the prediction of households' actual decisions about energy retrofits. This modelling is more accurate than the model that assumes households make rational decisions.

A Perfect Storm: The Extraordinary Constitutional Attack against the Istanbul Convention in Bulgaria

On 27 July 2018, Bulgaria’s Constitutional Court delivered a judgment declaring the Istanbul Convention “incompliant” with the country’s Constitution. This article examines the origin and nature of the extraordinary constitutional attack against this Convention in Bulgaria which can be described as a “perfect storm” - diverse, unrelated factors concurred and conditioned an event with long-lasting repercussions that are difficult to overcome. It first analyses the political context which permitted a misinformation campaign and motivated Boyko Borissov’s GERB party to seek a constitutional review of the document. Then, it explains why the method of appointing judges in Bulgaria’s Constitutional Court and the particularities of its jurisdiction make this institution susceptible to political influences. After critically evaluating the questionable legal reasoning in the actual decision, the article explores its consequences. Among them, the most notable damage concerns the current legal impossibility to ratify the Istanbul Convention in Bulgaria. At this stage, the country can only count on piecemeal legislative solutions to introduce to Bulgarian legislation the spirit of relevant provisions of the Convention that have not been contested.

Rapid fulfillment of online orders in omnichannel grocery retailing

Establishing innovative fulfillment options for online orders has become a key challenge for bricks-and-mortar retailers. A mere focus on store sales is no longer affordable due to the competition by pure online players. Retailers are continuously developing new approaches for online order fulfillment and last-mile logistics. Further shortening lead times is becoming even more important in this context. One recently developed concept is the omnichannel approach where existing structures are utilized and distribution centers (DCs) and local stores are integrated into a holistic fulfillment concept. This concept is especially relevant when retailers are providing fast delivery services (e.g., same hour delivery). It resembles a multi-depot vehicle routing problem where all facilities act as depots and orders are assigned based on processing and transportation costs as well as available delivery capacity. We address this new concept and present the novel problem for rapid integrated order fulfillment in grocery retailing. We empirically identify decision-relevant costs for order processing in stores and develop an approach for the evaluation of overall fulfillment costs. Our work considers the order assignment to heterogeneous depots and vehicle routing for each depot depending on depot-specific fulfillment costs using a tailored cluster-first-route-second heuristic. We show that integrated rapid order fulfillment can reduce costs by an average of 7.4% compared to order fulfillment from DCs. However, as order processing costs at stores remain a significant cost factor, DCs will always have some relevance and cannot entirely be replaced by delivery from stores. Our results highlight the importance of modeling order processing costs in stores for actual order fulfillment decisions in a heterogeneous network. • Retailers are developing new approaches for online order fulfillment. • We present a formulation for rapid order fulfillment in grocery retailing. • We identify decision-relevant costs for order processing in stores. • Integrated order fulfillment can reduce costs compared to fulfillment from DCs.

A novel illustration of real options analysis to address the problem of probabilities under deep uncertainty and changing climate risk

Changing risk profiles over time that are exacerbated by climate change, challenge assessments of the relative value of investing in different adaptation options. There is a growing discourse around methods that are better suited to addressing changing risk and uncertainties for large infrastructure projects — robust decision making (RDM), real options analysis (ROA) and those based on dynamic adaptive pathways planning (DAPP). While such approaches are receiving greater attention in the academic literature, there is a gap in critiques of them in real-life decision practice. Here we present two novel applications from New Zealand of real options analysis that formed part of actual decision processes — a flood risk management plan and a coastal hazards strategy, both based on DAPP over 100 years. In both cases, we examined the value of pursuing adaptation options that are flexible under peak river flows, coastal erosion, imminent inundation, storm surge and long-term sea-level rise. From lessons learned we examined three questions relating to ROA: 1) is ROA ‘fit for purpose’ for investment evaluations in situations of both imminent threat and deep uncertainty and its scalability? 2) can ROA address path dependency and move beyond static applications? 3) can ROA be used alongside DAPP to address managed retreat as an adaptation option. We conclude the affirmative for each question and provide a method for using ROA within a DAPP and RDM framework.

Approaches to Multiple Attribute Decision-Making with Fuzzy Number Intuitionistic Fuzzy Information and Their Application to English Teaching Quality Evaluation

Many experts and scholars focus on the Maclaurin symmetric mean (MSM) operator, which can reflect the interrelationship among the multi-input arguments. It has been generalized to different fuzzy environments and put into use in various actual decision problems. The fuzzy number intuitionistic fuzzy numbers (FNIFNs) could well depict the uncertainties and fuzziness during the English teaching quality evaluation. And the English teaching quality evaluation is frequently viewed as the multiple attribute decision-making (MADM) issue. We expand the MSM equation with FNIFNs to propose the fuzzy number intuitionistic fuzzy MSM (FNIFMSM) equation and fuzzy number intuitionistic fuzzy weighted MSM (FNIFWMSM) equation in this study. A few MADM tools are developed with FNIFWMSM equation. Finally, taking English teaching quality evaluation as an example, this paper illustrates the depicted approach.

Managing and Disclosing Environmental Risks: A Tale of Two Utilities

ABSTRACTThis case introduces students to the topic of contingent liabilities by examining the actual management decisions of two energy companies facing increased regulatory scrutiny over the environmental risks associated with coal ash. The case learning objectives include (1) researching and summarizing the guidance governing the recognition and disclosure of contingent liabilities; (2) critically assessing a company's decisions regarding the recognition and disclosure of environmental liabilities; (3) accounting for asset retirement obligations; and (4) articulating the ethical implications of a company's management and disclosure of environmental risks from the perspectives of various stakeholders. The case is designed for use in an intermediate accounting course at the undergraduate level. Students reported improvement in their knowledge and comprehension of contingent liabilities and their appreciation for the ethical implications of accounting decisions. Students also noted that they enjoyed discussing these issues in the context of real companies facing complex environmental challenges.

Treatment Decision-making in Chinese Inflammatory Bowel Disease Patients.

Inflammatory bowel disease (IBD) is rising in China, and the tendency for lifelong recurrence decreases patients' quality of life. However, no studies on treatment decision-making in Chinese patients with IBD exist. Thus, this study aimed to determine the actual and ideal decision-making, as well as factors affecting decision-making in Chinese IBD patients. A multicenter online questionnaire was distributed among patients diagnosed with IBD. To assess factors that influence treatment decision-making, univariate and multivariate logistic regression analyses were performed. From March 20, 2018, to May 20, 2018, a total of 866 patients completed the questionnaires, including 222 patients with ulcerative colitis, 588 patients with Crohn's disease, and 56 patients with unclassified IBD. There was a significant difference between ideal and actual decision-making in Chinese IBD patients (P< .005). The factors affecting ideal decision-making included income, education, illness severity, religiosity, the importance of the treatment decision, the employment situation, and occupation area. The factors affecting actual decision-making included age, illness severity, religiosity, the employment situation, economic anxiety, concern about the side effects, and the importance of the treatment decision. There is a significant difference between ideal and actual decision-making in IBD patients in China. That is, the economy, religiosity, illness severity, and concern about the side effects of treatment are the most important factors affecting treatment decisions in Chinese IBD patients.