Uncertain Situations Research Articles

A sustainable integrated model for multi-objective planning of an agri-food supply chain under uncertain parameters: A case study

The extended and complex nature of agri-food supply chain systems results in food loss and an asymmetrical flow of information. It is vital to integrate the cultivation, harvest, processing, and distribution decisions for designing a sustainable agri-food supply chain to minimize overall cost and create employment opportunities alongside considering global concerns. A multi-objective, integrated, sustainable mathematical model is presented in this study to maximize the revenue and employment generated while reducing the environmental impacts. The criteria for the evaluation of farmlands are derived from literature, and Geographical Information System (GIS) is used to obtain geospatial data to assess the performance of diverse farmlands across various criteria. The farmlands are then assessed and prioritized using the Best Worst Method (BWM). Among all criteria for selecting the farmlands, favorable temperature and land-use have the highest and lowest impact, respectively. Furthermore, a pricing model is proposed to estimate the price in various customer zones. The robust possibilistic model is suggested to take into account weather patterns, transportation costs, and customer zone demand under uncertain situation. The proposed model is illustrated in the Stevia processing plant in Iran and the tradeoffs between different model parameters and objective functions are studied, and the validity of the model is assessed by sensitive analyses. The outcomes show that to meet robustness, the number of active farmlands and warehouses should be increased by about 11%, which imposes a 10% cost on the model. Based on sensitive analysis, increases in production capacity and demand result in a significant rise in the profit function (12% and 16%, respectively), despite the fact that improvements to farmland and warehouse capacity have little effect on profit, indicating the need for managers to prioritize production rate and advertising. Moreover, the results show the best location for planting stevia, the optimum production rate, the proper number of warehouses, and their capacities in each period.

Factors Affecting Cattle Insurance Purchase and its Effects on the Financial Situation of Dairy Farmers

The results of the study indicated that the age of the respondents, the type of animals reared, herd size, and membership in dairy cooperatives and districts significantly influenced the adoption of cattle insurance. The education of the respondent, herd size, the type of animal holding, and membership in dairy cooperatives significantly influenced the willingness to pay for cattle insurance. Willingness to pay was found to be less than the actual payment for the cattle insurance premium, and it was more in the case of crossbreds than other categories of animals. The type of animal and membership in dairy cooperatives had a positive and significant influence on the actual level of payment for cattle insurance. The landholding size, animal herd size, and non-farm occupation, along with dairying, had a positive influence, and the loss of animals had a negative impact on the net- income of the farmers. Finally, it can be concluded that cattle insurance is one of the best risk mitigation strategies to help farmers stabilize their income under risks and uncertain situations.

On the Construct of Subjective Risk Intelligence and Its Relationships with Personality, Emotional Intelligence and Coping Strategies: A Comparison between Adolescents and Adults.

The complexity of today's scenario has made it necessary to investigate the need for individuals to make choices that entail increasing exposure to risk and uncertainty. Among the individual resources that could help people to cope with situations of uncertainty, the new construct of subjective risk intelligence (SRI), known as a person's ability to effectively weigh the pros and cons of a decision in situations where not all the outcomes are foreseen, would seem to play a prominent role. Considering that personality and coping strategies have been shown to be significantly related in previous research, the present study investigates the relationships between subjective risk intelligence, emotional intelligence, personality traits and coping strategies in both adults and adolescents. This cross-sectional study was conducted on 1390 Italian people, divided into two subsamples of 641 adolescents and 749 adults. The results showed that SRI mediated the roles that personality traits and emotional intelligence have in coping strategies differently in the adult sample, in which the mediating role of SRI was found for avoidance coping, and in the adolescent sample, in which SRI influenced all of the antecedents analysed in the study for almost all of the identified coping strategies. In light of these findings, subjective risk intelligence could be activated to deal with uncertain and risky situations, influencing the choice of effective or ineffective strategies in both adults and adolescents.

Trust and reliance on AI — An experimental study on the extent and costs of overreliance on AI

Decision-making is undergoing rapid changes due to the introduction of artificial intelligence (AI), as AI recommender systems can help mitigate human flaws and increase decision accuracy and efficiency. However, AI can also commit errors or suffer from algorithmic bias. Hence, blind trust in technologies carries risks, as users may follow detrimental advice resulting in undesired consequences. Building upon research on algorithm appreciation and trust in AI, the current study investigates whether users who receive AI advice in an uncertain situation overrely on this advice — to their own detriment and that of other parties. In a domain-independent, incentivized, and interactive behavioral experiment, we find that the mere knowledge of advice being generated by an AI causes people to overrely on it, that is, to follow AI advice even when it contradicts available contextual information as well as their own assessment. Frequently, this overreliance leads not only to inefficient outcomes for the advisee, but also to undesired effects regarding third parties. The results call into question how AI is being used in assisted decision making, emphasizing the importance of AI literacy and effective trust calibration for productive deployment of such systems.

Customer satisfaction antecedents in uncertain hospitality conditions: an exploratory data mining approach

PurposeInformed by trait and self-determination theories, the present study aims to extend the knowledge regarding the link between customer satisfaction (CS) and its antecedents, including job autonomy (JA), conscientiousness, customer uncertainty (CU) and extra-role customer service (E-RCS) in the hospitality industry.Design/methodology/approachA total of 306 frontline employees were selected from the hotels in North Cyprus, Turkey. Psychometric properties, including the validity and reliability of study variables, were assessed in the first step using confirmatory factor analysis. Then, the data were analyzed utilizing machine learning methods, mainly three exploratory data mining techniques, including lasso regression, decision trees and random forest, as well as partial dependence plots to visualize the role of suggested predictors on the outcome variable.FindingsData mining analysis shows that employees who can modify their job objectives are better equipped to satisfy customers in uncertain situations (JA8). In addition, the findings reveal that employees who believe they work hard to accomplish their personal and organizational goals (CON7) while also having the freedom to decide how to approach their job (JA1) and choose the procedures to utilize (JA2) are more likely to contribute to CS. In general, CS peaked when JA was high, but conscientiousness was moderate, while CU was low.Practical implicationsThis study bridges the gap among various factors at the employee and customer individual, corporate and macro-environmental levels. Hospitality organizations can cultivate a culture of autonomy and independence by promoting open communication and offering growth and development opportunities. This approach enhances conscientious employees’ engagement, leading to exceptional customer service performance, particularly, in uncertain situations.Originality/valueFrom the methodology perspective, this work proposes an opportunity for prospective scientists to broaden the trait and self-determination theories research model by relying on the riches of exploratory techniques without the limits imposed by traditional analytical techniques. Further, this study advances the current knowledge about service agility under uncertainty by extending organizational and service management research to consumer behavior literature.

Strategic Agility and Performance of Pay Television Industry in Kenya.

The Pay TV market in Kenya operates in a highly competitive business environment, which in turn calls for aggressiveness and more efficient ways of keeping the business afloat. Advancement in technology also comes with several options for Pay TV customers such as online streaming which poses more threat to the market. This research seeks to assess the influence of strategic agility on the performance of the Kenyan Pay TV industry using Multichoice Kenya Limited as the case study. The objectives of this study were to establish the influence of leadership agility, determine the influence cultural agility, assess the influence of business agility, and to determine the influence of career agility on organizational performance in the Kenyan Pay TV industry. The study is of great significance to the government of Kenya since the improved performance of the Pay TV companies can generate more revenue for the government in form of taxes and license fees. New and existing Pay TV companies may also benefit from this study by employing agile strategies for competitive advantage as well as getting more information on how to handle uncertain situations in the business environment. Additionally, academicians who may want to research more on strategic agility may benefit by accessing more information from this study. The concept of strategic agility has not been sufficiently researched especially on the variables such as leadership agility, cultural agility, business agility, career agility and how they influence organizational performance. This research was anchored on four theories namely; The Great Man Theory, Theory of Change, Theory of Constraints, and the Broaden and Build Theory. The reviewed literature on these theories indicates that there is a positive influence of strategic agility on organizational performance. This is a cross-sectional study which involves 60 employees with managerial roles. Descriptive design was used in this study adopting qualitative and quantitative methods. Data collection was done through closed and open-ended questionnaires, keeping a register of questionnaire distribution and feedback collection. A pilot study was carried out to determine the accuracy, clarity and relevance of the study questionnaire. Data analysis was carried using SPSS (V29) and multiple regression analysis. The study found that leadership agility, cultural agility business agility and career agility all have a significant effect on the performance of Pay TV firms in Kenya. The top leadership of firms in Pay TV industry should establish cross-cultural collaboration initiatives to encourage knowledge-sharing and teamwork among employees from different cultural backgrounds, foster a culture that encourages and rewards agile leadership behaviors, such as risk-taking and experimentation and encourage leaders to seek mentorship and coaching to enhance their agility capabilities, should invest in technology and infrastructure that support flexibility and adaptability in responding to market changes and also develop cross-functional teams that can quickly adapt to changing business requirements and address emerging challenges, implement career development plans and pathways that align with the organization's strategic objectives and employees' career aspiration and encourage a growth mindset among employees.

Conversations in couple relationships: a trustful foundation when making future parenthood “real”

Sociologists often argue that communication in long-term couple relationships is the basis on which expectations, trust, and equality are created in contemporary society. However, what is the role of these everyday conversations in uncertain life situations such as expecting one’s first child? This article examines concerns reported by prospective Swedish parents in order to explain the role of communication to alleviate these. Concerns, related to the formation of new relationships with one’s partner, oneself, and one’s future child, are mitigated by referring to the couple’s “good” communication. In the present prenatal situation, the communication pattern (established in the past) seems to serve three functions in mitigating future concerns: (1) the communication generates a trust capital in the relationship, allowing the couple to venture into the uncertain future, (2) the communication makes social perceptions of family life “real” by constructing a common nomos that is internalized in the individual as an existential motto, and (3) the communication legitimizes family practices as democratic when referring to future plans as emerging from responsive and consensual dialogs. In the article it is emphasized that welfare policy needs to be based on an existential legitimacy, often developed in couple conversations, and particularly shaped in life situations characterized by change. However, the stability offered at the conversational micro level may simultaneously prevent macro level changes, a complexity that needs to be considered when developing a gender equality policy that is to resonate with people’s existential meaning making. With the aim of consensus, and the means of balancing conflicts, there is a risk that the conversation will consolidate the interests of the stronger party. In this way, the responsive conversations in long-term relationships may consolidate gender inequality and counteract the welfare policy goal of equalizing power relationships.

Whole-exome sequencing as the first-tier test for patients in neonatal intensive care unit: a Chinese single-center study.

Genetic disorders significantly affect patients in neonatal intensive care units, where establishing a diagnosis can be challenging through routine tests and supplementary examinations. Whole-exome sequencing offers a molecular-based approach for diagnosing genetic disorders. This study aimed to assess the importance of whole-exome sequencing for neonates in intensive care through a retrospective observational study within a Chinese cohort. We gathered data from neonatal patients at Tianjin Children's Hospital between January 2018 and April 2021. These patients presented with acute illnesses and were suspected of having genetic disorders, which were investigated using whole-exome sequencing. Our retrospective analysis covered clinical data, genetic findings, and the correlation between phenotypes and genetic variations. The study included 121 neonates. Disorders affected multiple organs or systems, predominantly the metabolic, neurological, and endocrine systems. The detection rate for whole-exome sequencing was 52.9% (64 out of 121 patients), identifying 84 pathogenic or likely pathogenic genetic variants in 64 neonates. These included 13 copy number variations and 71 single-nucleotide variants. The most frequent inheritance pattern was autosomal recessive (57.8%, 37 out of 64), followed by autosomal dominant (29.7%, 19 out of 64). In total, 40 diseases were identified through whole-exome sequencing. This study underscores the value and clinical utility of whole-exome sequencing as a primary diagnostic tool for neonates in intensive care units with suspected genetic disorders. Whole-exome sequencing not only aids in diagnosis but also offers significant benefits to patients and their families by providing clarity in uncertain diagnostic situations.

Multi-Regional Integrated Energy Economic Dispatch Considering Renewable Energy Uncertainty and Electric Vehicle Charging Demand Based on Dynamic Robust Optimization

Aiming at the problem of source-load uncertainty caused by the increasing penetration of renewable energy and the large-scale integration of electric vehicles (EVs) into modern power system, a robust optimal operation scheduling algorithm for regional integrated energy systems (RIESs) with such uncertain situations is urgently needed. Based on this background, aiming at the problem of the irregular charging demand of EV, this paper first proposes an EV charging demand model based on the trip chain theory. Secondly, a multi-RIES optimization operation model including a shared energy storage station (SESS) and integrated demand response (IDR) is established. Aiming at the uncertainty problem of renewable energy, this paper transforms this kind of problem into a dynamic robust optimization with time-varying parameters and proposes an improved robust optimization over time (ROOT) algorithm based on the scenario method and establishes an optimal scheduling mode with the minimum daily operation cost of a multi-regional integrated energy system. Finally, the proposed uncertainty analysis method is verified by an example of multi-RIES. The simulation results show that in the case of the improved ROOT proposed in this paper to solve the robust solution of renewable energy, compared with the traditional charging load demand that regards the EVs as a whole, the EV charging load demand based on the trip chain can reduce the cost of EV charging by 3.5% and the operating cost of the multi-RIES by 11.7%. With the increasing number of EVs, the choice of the starting point of the future EV trip chain is more variable, and the choice of charging methods is more abundant. Therefore, modeling the charging demand of EVs under more complex trip chains is the work that needs to be studied in the future.

Higher Education and Higher Inequality

Background: This case study focuses on gender inequality in a higher education setting. It involves both human resources and leadership management situations. By participating in this study, students will be able to do the following: critically examine a gender inequality case study; recommend a solution or outcome regarding a case of gender inequality in a global setting; and justify and defend their decision-making skills in uncertain and complex ethical situations and gender inequality. This case study is best suited for undergraduate students in a human resource, ethical leadership, or social change theory course. In addition, this case study is also appropriate for business professionals in the human resource field. Objectives and Learning Outcomes: Learning outcomes include: 1) Critically examine a gender inequality case study; 2) Recommend a solution or outcome regarding a case of gender inequality in a global setting; 3) Justify and defend their decision-making skills in uncertain and complex ethical situations and gender inequality; 4) Research examples of gender inequality in the workplace. Some information has deliberately been excluded from the case study to promote further research and discussion to give students an opportunity to give an end to the story. Teaching Notes: Teaching notes are available with this case study.

Entrepreneurship, subjective risk intelligence and SMEs’ financial stability: evidence from Italy

PurposeThis paper applies an original construct of “subjective risk intelligence (SRI)” to the small business context. By leveraging on its multidimensionality, it aims to shed light on the existing ambiguities in the analysis of the relationship between the entrepreneurial attitude towards risk evaluation and firms’ financial stability.Design/methodology/approachThe empirical investigation refers to the Italian context, where an ad hoc survey has been administered to a sample of small businesses. Based on both a linear and a semiparametric regression, results show a significant relationship between SRI and firm’s financial structure, and that such relationship is basically nonlinear.FindingsEvidence shows that entrepreneurs with a high level of risk intelligence run highly leveraged firms. Moreover, in the light of the non-linearity of such relationship, higher levels of risk intelligence are associated with a greater capacity of the entrepreneur to govern the financial balance of the enterprise only up to a certain threshold. Over this threshold, risk intelligence generates overconfidence leading the entrepreneur to a reckless behaviour in taking financial risks.Originality/valueFrom a theoretical point of view, the paper contributes to the literature by shedding lights on the complexity of the relationship between risk intelligence and small businesses. From a policy point of view, findings suggest that, to train new entrepreneurs, the educational system aims should focus on the development of two specific “soft skills”: the ability to manage emotions and the ability to glimpse opportunities even in uncertain situations.

A Prompt for Generating Script Concordance Test Using ChatGPT, Claude, and Llama Large Language Model Chatbots

Medical education always evolves to incorporate more tools for specific needs in assessing clinical reasoning skills. Among these tools, Script Concordance Test (SCT) has a particular importance due to its focus on assessing decision-making in uncertain clinical situations. However, development of SCT items is effortful. Artificial intelligence tools, such as large language models, offer significant benefits. These models are already used for generating multiple-choice questions, and their use in generating SCTs offers great promise. However, this requires well-designed prompts to generate SCTs. This article proposes a generic prompt for the ChatGPT-4, Claude 3, Llama 3, and ChatGPT-4o large language model chatbots to generate SCTs, which can be tailored to various fields of medicine and different stages of medical education. It can help to streamline the development process of SCTs. Initial findings are promising, and there is a need for generating SCTs using large language models and conducting research to assess the quality of SCTs.

Integrated learning framework for multistep pick-place-arrange of arbitrarily shaped objects in a narrow crate

To maximize the space occupied by unknown objects in a narrow crate and handle uncertain situations, we propose a novel human-like system-level learning framework: sequential infiltration synthesis of combined learning (SISCL). This framework leverages the synergies between picking by grasping, three-dimensional modeling, preferable placement, and seamless arranging by pushing in a systematic perspective. Within SISCL, a closed-loop system organizes different designing methods including reinforcement learning, knowledge induction, and analytic methods. This integration trains the system to autonomously package unknown objects and accommodate for uncertainties in measurements or executions, combining efficiency and flexibility. Initially trained in simulations, the SISCL framework underwent comprehensive evaluation in the laboratory. Furthermore, an initial validation was conducted on an extraterrestrial test ground. The results demonstrate the adaptability of the proposed framework to different shapes, materials, and stiffness of objects, as well as the capacity for uncertainties, thereby considerably reducing the need for precision in each sub-procedure in a human-like manner, facilitating seamless operations and efficient utilization of limited space.

Managing uncertainties in fault avoidance zone of urban areas: a case study of Karaj, Iran

Purpose This study aims to develop the application of the strategic choice approach (SCA) in Karaj City (Iran) as the case study for facilitating the decision-making process concerning uncertainties associated with determining fault trace, fault buffer zone and fault setback, as well as inherent uncertainties related to urban issues – known as wicked problems – which make a clear definition unachievable for them. Design/methodology/approach The SCA was recycled in this study to manage uncertain situations in planning. It is designed to deal with problems caused by uncertainty, insufficient knowledge and unpredictable policy outcomes. In combination with the risk-based planning approach, the paper proposes a new model to deal with uncertainty and hazard risk at the same time. Findings The results indicated that such decision-making tools are helpful for urban planners who impose changes in the fault zone to save lives and properties where the process seems problematic and ambiguous. Further analysis from the SCA development not only shows that urban planning restrictions should be applied gradually and in pace with the completion of fault displacement geological data but also reveals that defining the implementation process and institutional structure is as important as the preparation of binding fault zoning documents. Originality/value The paper will push forward global research and practice because the results can be generalized for use in other earthquake-prone countries, as the considerations and obstacles have a universal character and more specifically because many earthquake-prone countries have not started to define fault avoidance zone restrictions up to now.

Improved Decision Support System for College Sports Training Based on Id3 Algorithm

A Decision Support System (DSS) is a computer-based tool designed to assist individuals and organizations in making informed decisions. It utilizes data analysis, modeling techniques, and interactive interfaces to provide users with relevant information and insights. DSSs help streamline decision-making processes by synthesizing large amounts of data from various sources, generating forecasts, and evaluating alternative courses of action. They are particularly valuable in complex and uncertain situations where decisions have significant implications. DSSs can be used in a wide range of domains, including business, healthcare, finance, and logistics, to support strategic, tactical, and operational decision-making processes. This paper introduces an Integrated Hybrid Feature Subset Decision Support System (HFS-DSS) designed to optimize decision-making processes in student performance evaluation within educational institutions. The HFS-DSS combines feature subset selection techniques with decision support algorithms to identify key attributes and make accurate predictions regarding student performance. Through experimental evaluation, the system demonstrates its effectiveness in accurately assessing student performance based on selected features, with predictions closely aligning with actual observations. The results underscore the system's reliability and effectiveness in supporting informed decision-making processes, offering valuable insights for educators and administrators to enhance academic outcomes. The adaptability and versatility of the HFS-DSS make it well-suited for various educational contexts, providing potential applications in curriculum planning, student support services, and performance monitoring. The present paper highlights the significant contributions of the Integrated HFS-DSS towards enhancing decision-making processes and improving academic outcomes in educational institutions.

Uncertain world: How children's curiosity and intolerance of uncertainty relate to their behaviour and emotion under uncertainty.

Curiosity and intolerance of uncertainty (IU) are both thought to drive information seeking but may have different affective profiles; curiosity is often associated with positive affective responses to uncertainty and improved learning outcomes, whereas IU is associated with negative affective responses and anxiety. Curiosity and IU have not previously been examined together in children but may both play an important role in understanding how children respond to uncertainty. Our research aimed to examine how individual differences in parent-reported curiosity and IU were associated with behavioural and emotional responses to uncertainty. Children aged 8 to 12 (n = 133) completed a game in which they were presented with an array of buttons on the screen that, when clicked, played neutral or aversive sounds. Children pressed buttons (information seeking) and rated their emotions and worry under conditions of high and low uncertainty. Facial expressions were also monitored for affective responses. Analyses revealed that children sought more information under high uncertainty than low uncertainty trials and that more curious children reported feeling happier. Contrary to expectations, IU and curiosity were not related to the number of buttons children pressed, nor to their self-reported emotion or worry. However, exploratory analyses suggest that children who are high in IU may engage in more information seeking that reflects checking or safety-seeking than those who are low in IU. In addition, our findings suggest that there may be age-related change in the effects of IU on worry, with IU more strongly related to worry in uncertain situations for older children than younger children.

TO ASSESS SLEEP DISTURBANCE AND INTOLERANCE OF UNCERTAINTY MEDIATED BY EMOTIONAL INTELLIGENCE AMONG YOUNG ADULTS DURING A PANDEMIC OUTBREAK

Covid-19 Pandemic has created a lot of uncertainty in young adults. Daily lifestyle has changed a lot because of this uncertain situation especially sleep pattern has been disturbed. Hence, this study aims to examine the Sleep disturbance (improper sleep pattern) and Intolerance of uncertainty mediated (viewing uncertainty as negative) by Emotional intelligence (having awareness and regulating of one’s and others’ emotions) among young adults during a pandemic outbreak. An online questionnaire, including socio-demographics, the Pittsburgh Sleep Quality Index (PSQI), Intolerance of Uncertainty Scale (IUS), and Emotional Intelligence Scale (EIS), was administered to young adults (n=200). There is a significant positive correlation between sleep disturbance and intolerance of uncertainty (.367**), a significant negative correlation between sleep disturbance and emotional intelligence (-.329**), and Intolerance of uncertainty and emotional intelligence is negatively correlated (-.450**). On mediational analysis is revealed that emotional intelligence is partially mediating between Sleep disturbance and Intolerance of uncertainty. On Chi-square, it was seen that there is an association between Sleep disturbance and domicile and person’s tested, covid positive in the past 1 year. Emotional intelligence has an association with family type. Sleep disturbance and Intolerance to uncertainty can be improved by enhancing Emotional intelligence. KEYWORDS: Covid-19 Pandemic, Young adults, Sleep disturbance, Intolerance to uncertainty, and Emotional intelligence.

Understanding Mass Panic

Mass panics can arise in response to a variety of situations, such as the spread of pathogens, bank failures, or insecurities about economic supplies. Such panics can produce contagious behaviors such as fleeing social contacts, bank withdrawals, and panic buying. In such situations, the processing of external stimuli, mediated by the perceptions and biases of the individual, can reach a threshold point at which panic behaviors are triggered. Due to the human propensity to imitate the behavior of others in uncertain crisis situations, one individual’s panic behavior can spread contagiously. This paper looks at the similarities among case studies of mass panic around the world and from these cases synthesizes a conceptual model to aid our understanding. Decision-makers can use this model to strengthen national resilience against panic-generated behaviors and ensure an orderly and successful public response to future biological, financial, or economic crises.

Conspiracy beliefs and perceptual inference in times of political uncertainty.

Sociopolitical crises causing uncertainty have accumulated in recent years, providing fertile ground for the emergence of conspiracy ideations. Computational models constitute valuable tools for understanding the mechanisms at play in the formation and rigidification of these unshakeable beliefs. Here, the Circular Inference model was used to capture associations between changes in perceptual inference and the dynamics of conspiracy ideations in times of uncertainty. A bistable perception task and conspiracy belief assessment focused on major sociopolitical events were administered to large populations from three polarized countries. We show that when uncertainty peaks, an overweighting of sensory information is associated with conspiracy ideations. Progressively, this exploration strategy gives way to an exploitation strategy in which increased adherence to conspiracy theories is associated with the amplification of prior information. Overall, the Circular Inference model sheds new light on the possible mechanisms underlying the progressive strengthening of conspiracy theories when individuals face highly uncertain situations.

Images Connect Us Together: Navigating a COVID-19 Local Outbreak in China Through Social Media Images

Social media images, curated or casual, have become a crucial component of communicating situational information and emotions during health crises. Despite its prevalence and significance in informational dissemination and emotional connection, there lacks a comprehensive understanding of visual crisis communication in the aftermath of a pandemic which is characterized by uncertain local situations and emotional fatigue. To fill this gap, this work collected 345,423 crisis-related posts and 65,376 original images during the Xi'an COVID-19 local outbreak in China, and adopted a mixed-methods approach to understanding themes, goals, and strategies of crisis imagery. Image clustering captured the diversity of visual themes during the outbreak, such as text images embedding authoritative guidelines and "visual diaries" recording and sharing the quarantine life. Through text classification of the post that visuals were situated in, we found that different visual themes highly correlated with the informational and emotional goals of the post text, such as adopting text images to convey the latest policies and sharing food images to express anxiety. We further unpacked nuanced strategies of crisis image use through inductive coding, such as signifying authority and triggering empathy. We discuss the opportunities and challenges of crisis imagery and provide design implications to facilitate effective visual crisis communication.