Port strategy and performance: empirical evidence from major container ports and implications for role of data analytics

Container ports operate in more challenging and volatile environments at present times. Events such as US-China trade tensions and the COVID-19 pandemic severely affect numerous container ports at various levels. Strategies pursued by container ports are key to port development and management amidst these challenges. Drawing on configuration theory, this research employs Fuzzy-set Qualitative Comparative Analysis to investigate the relation between port strategies and container throughput. The research contributes to the literature by proposing an approach to account for complexity of the port sector and offers insights into strategies adopted by major container ports. The research further identifies 10 port strategies and proposed indicators that can represent the essence of these strategies. Being able to represent strategies in a quantitative format is important for strategy analysis and performance evaluation. Results reveal that major container ports employ a combination of strategies which address both the supply and demand-side aspects of the port business. Growing digitalization and digitization coupled with advancements in information capture, diagnostics capabilities and predictive abilities means a greater role for data analytics to influence container port strategy and performance. Implications for port managers, policy makers and researchers from the perspective of port policy and management are proposed.

How does social responsibility investment strategy contribute to hospitality firms' recovery from public health emergencies? The case of COVID-19 pandemic.

Using fuzzy-set qualitative comparative analysis, this paper explores which configurations of six dimensions of hospitality firms' corporate social responsibility (CSR) result in higher (or lower) levels of total factor productivity. We demonstrate that different categories of stakeholders and hospitality firms' dynamic capabilities complement each other under the framework of configurational theory. The result shows that: 1) The CSR dimensions of product quality, CSR communication, and environmental protection are critical to high levels of firm performance; 2) After the pandemic, hospitality firms should make investment in CSR communication and environmental protection a priority; 3) Hospitality firms' choice to invest in a specific combination of dimensions of CSR practice should depend on their overall level of corporate governance (high or low). This paper contributes to the strategic management and corporate governance literature by identifying the role of hospitality firms' governance on the linkage between CSR investment strategy and firm performance.

Factors Affecting Decision to Adopt Artificial Intelligence During COVID-19 Pandemic Period: Evidence from PLS-SEM and fsQCA

The study investigated the factors influencing the demand for Artificial Intelligence (AI) applications in Vietnam from the perspective of Accounting and Auditing. The data was gathered using a quantitative technique based on questionnaires to study a total of 206 accountants and auditors, and was analysed using the PLS-SEM method to determine influential factors and their relationships. In addition, we compare the PLS-SEM results with a recently established approach of panel data fuzzy-set qualitative comparative analysis (fsQCA). The results reveal that the components of finance, tasks, technology, epidemics, knowledge readiness and trust all have a favourable impact on the use of AI in Accounting and Auditing in Vietnam. Besides, the fsQCA results are consistent with the PLS-SEM method, which means that our findings are robust and valid. This study adds empirical evidence to the scientific literature on AI in Accounting and Auditing, which will be immensely beneficial for legislators and businesses looking to improve company efficiency. Besides, applying the fsQCA approach contributes significantly to the existing literature about the research method. © 2023 MDI.

How value drivers of internet medical business model affect value creation: a configurational approach

PurposeThis paper aims to investigate how value drivers of internet medical business model affect value creation through a configurational approach. The internet medical business model (IMBM) is such a business model that integrates online and offline medical services with the driving force of internet technologies covering prediagnosis, in-diagnosis and postdiagnosis. The outbreak of COVID-19 and the support of national policies have boosted the development of internet health care. However, there are still many challenges in practice, such as the unclear innovation path, as well as difficulties in landing and profiting. Academic research has not yet provided sufficient theoretical insights. Therefore, to better explain and guide practice, it is urgent to clarify the innovation path and mechanism of value creation for IMBM. Design/methodology/approachBased on the sample of 58 internet medical firms in China, this paper adopts fuzzy-set qualitative comparative analysis (fsQCA) to explore the configurational effects of IMBM's value drivers on value creation. FindingsBuilding on the business model canvas and the characteristics of internet health care, five value drivers of IMBM are identified, namely, functional value proposition, emotional value proposition, user involvement, resource capabilities and connection properties. And the five value drivers form three configurations, which are, respectively, labeled as resource-driven configuration, user-operated configuration and product-combined configuration. From the perspective of the integration of traditional and emerging theories, such as resource-based view, internet economics and value cocreation, each configuration leads to value creation and improves value results with different mechanisms behind it. Originality/valueFirst, combined with the business model canvas and the characteristics of internet health care, this paper identifies five value drivers of IMBM, thus improving the relevant research on internet health care. Second, based on the configurational effects, this paper discusses the mechanism behind the configurational effects of IMBM's value drivers on value creation, thus expanding relevant research on the value creation of business models. Third, applying fsQCA and combining the advantages of qualitative research and quantitative research, this paper adds to the configurations of IMBM's value drivers that achieve high-value results.

Innovation and internationalisation during times of economic growth, crisis, and recovery prior to Covid-19: A configurational approach comparing Spanish manufacturing family and non-family firms

Based primarily on the Resource-Based View and prior evidence, this study gauges the potential differences in innovative behaviour between international family firms and non-family firms when conditions change drastically in the business environment (i.e. from a situation of economic growth to one of downturn, and then to recovery). The research setting is a large sample of Spanish manufacturing firms between 2007 and 2016 (i.e. pre-Covid-19). During this period (2009-2013), the global economic and financial crisis affected Spain. Thus, three sub-periods are distinguished in the empirical analysis: growth, crisis, and recovery. Using Qualitative Comparative Analysis, our findings show that the paths of innovation activities that promote internationalisation via exporting in family and non-family firms are somewhat dissimilar in each sub-period, supporting the argument that the causal effect of innovation on internationalisation is heavily dependent on environmental conditions. Compared to non-family firms, our results show that when family firms internationalise, they follow a wide variety and more stable number of paths in innovation activities. Our findings also provide additional evidence to support the argument of heterogeneity among family firms.

LEARNING AND PROGRESSION IN (TOO MUCH OF?) AN ENTREPRENEURIAL CHALLENGE DURING COVID-19

A venture creation programme (VCP) is an academic programme in which students' creation of a new entrepreneurial venture is a central vehicle for learning. A VCP puts students in the role of entrepreneurs with real opportunities and challenges. The entrepreneurial journey is a bumpy ride, and COVID-19 has added significant challenges for entrepreneurs, including students in VCPs. Previous research emphasises how entrepreneurial learning occurs through handling entrepreneurial challenges. The purpose of the present paper is to investigate the role of COVID-19induced challenges in VCP students' learning. We applied fuzzy-set qualitative comparative analysis (fsQCA) to data from students in a technology-oriented VCP in Scandinavia, collected in April 2021. FsQCA offers the opportunity to investigate complex logic combinations of factors that explain an outcome and is particularly suited for small samples. Multi-item measures assessed (1) the progress of students' ventures, (2) entrepreneurial learning and (3) perceived challenges from COVID-19. We also asked whether students had entered or exited an entrepreneurial project and whether these projects were run by a team or only the individual student. We found that COVID-19-induced challenges impeded VCP students' learning and that students' individual progress was important for learning during crisis situations. Thus, entrepreneurship educators should help students get 'back on the horse-which means being involved in new entrepreneurial projects-if their challenges lead them into stagnation and inactivity. Progress, both in students' ventures and for students as individuals, should be nurtured by entrepreneurship educators. © 2022 SEFI 2022 - 50th Annual Conference of the European Society for Engineering Education, Proceedings. All rights reserved.

Sustainable Path of Food Security in China under the Background of Green Agricultural Development

In light of the increasing global food crisis, this study concentrated on the complex causality of sustainable food security in China. In the context of the agricultural green transformation, a comprehensive evaluation system of agricultural green development is constructed on China Yearbooks' economic data and agricultural greening indices from 2012 to 2020. In addition, the coupling coordination degree model and fuzzy-set quantitative analysis are used to describe the path evolution of sustainable food security development in China. The results revealed that: (1) the comprehensive assessments were increased in recent years, and high score regions changed apparently, from the periphery to midland;(2) China's green development and agricultural economic potential are currently in a transitional phase from basic to moderate synergy, and the higher coordinated degree is allocating to mid and southern areas during this period, and all of them keeps growing as well;and (3) under modern food security framework, the emphasis of China has gradually shifted from grain output and subsidy policies to high resources utilisation and human capital accumulation. Thus, China's agricultural green transformation and sustainable food security are mutually reinforcing.

Factors influencing proactiveness in supply chain risk identification: A fuzzy-set qualitative comparative analysis

Nowadays, organizations pay more attention to introducing proactiveness for managing sudden unprecedented events like COVID-19. Previous studies focused on reactive and predictive methodologies for risk identification. In today's data-driven era, the adoption of proactive approaches is significantly increasing to achieve rapid recovery and accurate decision-making. However, analyzing the influencing factors and their interdependencies for addressing successful risk identification mechanisms is scarce in the literature. Researchers and social scientists adopted the fuzzy-set approach as a useful methodology to do statistical inferences from experts' surveys or interviews. Given this, we exploited fuzzy-set qualitative comparative analysis (fsQCA) to bring out the necessary conditions leading to the expected outcome. The dataset on the missing aspects was obtained based on a literature survey, supply chain (SC) related articles from social media, and discussions with experts. As a result, we aim to investigate the role of four influencing factors of SC risk, namely predicting future risks, continuous monitoring, external factors, and risk prioritization. The findings show the necessary and sufficient configurations of the causal conditions that lead to proactive risk identification. The solutions indicate that all four factors are perceived as necessary conditions. The mechanisms which focus on contemporary risk prediction and continuous monitoring are more likely to be effective. Further, some combinations highlight the significance of external factors like natural disasters (e.g., COVID-19). To the best of our understanding, there is no evidence in the previous studies that investigates the influencing factors of risk identification based on salient configurations using fsQCA. Given this, the findings of this research allow us to understand the essential factors that bring proactiveness to the risk management process. © 2023 Elsevier Ltd

How to enhance psychological security of enterprise employees during the COVID-19 pandemic: Based on MRA and fsQCA.

The economic impact caused by the outbreak and dynamic evolution of COVID-19 has reduced employees' psychological security (PS), which not only threatens the physical and mental health of employees but also seriously affects the stable operation and sustainable development of enterprises. PS has been determined to be closely related to daily life experiences. Therefore, the purpose of this article is to examine the types and combinations of life events that improve employees' PS during the pandemic. Cross-sectional data came from 764 enterprise employees in 8 provinces and cities in China during the pandemic period. The participants completed the PS scale to evaluate their PS, and the PS events scale to evaluate the different types of daily life events they experienced. Multiple regression analysis (MRA) and fuzzy-set qualitative comparative analysis (fsQCA) methods were used to test the research hypothesis. The results of MRA suggest that rich leisure activities (RLA), harmonious family relationship (HFR), stable economic order (SEO) and recognition and support from others (RSO) are important life events that enhance employees' PS. The results of fsQCA suggest that the independent role of SEO, the combined role of sound social security system (SSSS), peace and health events (PHE) and HFR, the combined role of PHE, fulfilling work/life status (FWLS), SEO and RSO can substitute for each other to promote employees' high PS. This article reveals the contribution of daily life events to the PS of enterprise employees, and provides an empirical basis for formulating corresponding intervention measures to promote the physical and mental health of enterprise employees and effective enterprise management.

Understanding Prospective Physicians' Intention to Use Artificial Intelligence in Their Future Medical Practice: Configurational Analysis.

BACKGROUND: Prospective physicians are expected to find artificial intelligence (AI) to be a key technology in their future practice. This transformative change has caught the attention of scientists, educators, and policy makers alike, with substantive efforts dedicated to the selection and delivery of AI topics and competencies in the medical curriculum. Less is known about the behavioral perspective or the necessary and sufficient preconditions for medical students' intention to use AI in the first place. OBJECTIVE: Our study focused on medical students' knowledge, experience, attitude, and beliefs related to AI and aimed to understand whether they are necessary conditions and form sufficient configurations of conditions associated with behavioral intentions to use AI in their future medical practice. METHODS: We administered a 2-staged questionnaire operationalizing the variables of interest (ie, knowledge, experience, attitude, and beliefs related to AI, as well as intention to use AI) and recorded 184 responses at t0 (February 2020, before the COVID-19 pandemic) and 138 responses at t1 (January 2021, during the COVID-19 pandemic). Following established guidelines, we applied necessary condition analysis and fuzzy-set qualitative comparative analysis to analyze the data. RESULTS: Findings from the fuzzy-set qualitative comparative analysis show that the intention to use AI is only observed when students have a strong belief in the role of AI (individually necessary condition); certain AI profiles, that is, combinations of knowledge and experience, attitudes and beliefs, and academic level and gender, are always associated with high intentions to use AI (equifinal and sufficient configurations); and profiles associated with nonhigh intentions cannot be inferred from profiles associated with high intentions (causal asymmetry). CONCLUSIONS: Our work contributes to prior knowledge by showing that a strong belief in the role of AI in the future of medical professions is a necessary condition for behavioral intentions to use AI. Moreover, we suggest that the preparation of medical students should go beyond teaching AI competencies and that educators need to account for the different AI profiles associated with high or nonhigh intentions to adopt AI.

Drivers for agility in times of crisis

Purpose: Agile organisations do not arise from a single characteristic but comprise a combination of various aspects. Thus, this study aims to examine the combined effects on organisational agility regarding firms' utilisation of digital technology to create value during the COVID-19 pandemic, how firms perceive uncertainty related to their own organisational response and the degree to which they have an entrepreneurial mindset. Design/methodology/approach: Using a fuzzy-set qualitative comparative analysis, this study investigates 355 established firms and start-ups in Norway. Findings: This study finds digitalisation is required for agility to develop, but that it needs to be combined with having an entrepreneurial mindset or being a start-up and lower levels of perceived uncertainty. Hence, entrepreneurial mindset and low uncertainty are important factors for digitalisation, and in turn, for agility to be developed. Originality/value: Agility is recognised as being pivotal for firms' competitiveness and innovation and argued to be significant in overcoming sudden economic shocks. However, lacking empirical scrutiny are investigations into the relationship between digitalisation and agility, and how digitalisation might act as a driver for building agility, which the authors tackle herein. © 2020, Emerald Publishing Limited.

Adoption of AI in response to COVID-19-a configurational perspective.

Although the importance of artificial intelligence (AI) has often been highlighted in strategic agility and decision outcomes, whether it helps firms strengthen their competitiveness and the means firms use to achieve such competitiveness are still under-researched. Our research thus joins the recent discussion on digitalization trends and strategic responses to COVID-19 to better understand how firms strengthen their competitiveness during such challenging times. Namely, this study incorporates the strategic responses to COVID-19 into the technology-organization-environment (TOE) framework by investigating the impacts of different configurations of TOE contexts and strategic responses on a firm's competitive advantage. We used fuzzy-set qualitative comparative analysis to investigate how TOE contexts and strategic responses integrate into configurations and impact a firm's competiveness. By applying a configurational approach with data from 514 exporting firms in China, we find a strong indication of the equifinality of different strategies, indicating that multiple strategic paths can be used to respond to crises. The adoption of AI, while important, is not sufficient to enhance a firm's competitiveness. Our results stress the significance of data quality, organizational resources and capabilities, and digital business model innovation for AI adoption. We also identify successful strategic paths of AI adoption aversion and ambidextrous strategies. The findings have practical implications for firms seeking effective strategies to respond to future crises and sustain their competitive advantages.

A Qualitative Comparative Analysis to explore the predictors of individuals' willingness towards vaccination.

The emergence of COVID-19 traumatized individuals from all walks of life and while the demand for vaccines increased exponentially, the authorities seem to encounter greater challenges on their road to create herd immunity. Governments initiated numerous campaigns to influence individuals to opt for vaccination and India being a diverse country makes it difficult to understand the motivating factors for getting COVID-19 vaccination. The study aimed to explore the predictors of individuals' willingness to get vaccinated using Qualitative Comparative Analysis (QCA). After screening using the vaccine hesitancy scale, a semi-structured interview was conducted among 30 respondents from India. Crisp Set QCA was utilized to analyse the data which lead to nine conditions. A solution combination of seven conditions showed a consistency of 1 and coverage of 0.6. They included knowledge about vaccines, perceived severity of the COVID-19 virus, family and peer influence, media and health department's influence, a sense of social responsibility, trust in the authorities and vaccine efficacy. This study contributes to the relevance of QCA's use in psychological research, especially to identify predictors of willingness to immunize. The findings of this study would help in designing appropriate interventions to enhance willingness to get vaccinated.

Configurational patterns for COVID-19 related social media rumor refutation effectiveness enhancement based on machine learning and fsQCA.

Infodemics are intertwined with the COVID-19 pandemic, affecting people's perception and social order. To curb the spread of COVID-19 related false rumors, fuzzy-set qualitative comparative analysis (fsQCA) is used to find configurational pathways to enhance rumor refutation effectiveness. In this paper, a total of 1,903 COVID-19 related false rumor refutation microblogs on Sina Weibo are collected by a web crawler from January 1, 2022 to April 20, 2022, and 10 main conditions affecting rumor refutation effectiveness index (REI) are identified based on "three rules of epidemics". To reduce data redundancy, five ensemble machine learning models are established and tuned, among which Light Gradient Boosting Machine (LGBM) regression model has the best performance. Then five core conditions are extracted by feature importance ranking of LGBM. Based on fsQCA with the five core conditions, REI enhancement can be achieved through three different pathway elements configurations solutions: "Highly influential microblogger * high followers' stickiness microblogger", "high followers' stickiness microblogger * highly active microblogger * concise information description" and "high followers' stickiness microblogger * the sentiment tendency of the topic * concise information description". Finally, decision-making suggestions for false rumor refutation platforms and new ideas for improving false rumor refutation effectiveness are proposed. The innovation of this paper reflects in exploring the REI enhancement strategy from the perspective of configuration for the first time.

Fuzzy-set qualitative comparative analysis in consumer research: A systematic literature review

The traditional symmetrical methods may not be sufficient for effectively examining the asymmetries that are evident in the real-world complex consumption context in the form of pandemic, and other technological, sociocultural, environmental, and geo-political factors. As a result, the use of innovative and asymmetrical methods such as fuzzy-set qualitative comparative analysis (fsQCA), which draws from the complexity theory could help better predict and explain consumer decisions in the age of disruptions. Through a comprehensive method-based systematic literature review of 129 research articles published in the consumer behavior research literature, this study helps to identify the key trends, leading publication sources and contributors, and the current knowledge structure of consumer research using fsQCA. In doing so, this review also sheds light on the state of diversity within this particular area of research. The findings help identify the key future avenues for utilizing fsQCA within consumer research. This review is a useful resource for practitioners to gain a direct access to key consumer research scholars for identifying the constructs (e.g., antecedents, mediators, moderators, enablers, inhibitors) shaping consumer behaviors to inform strategic decisions.

Combined effects of cues influencing patients' purchasing behavior in online health-care communities: qualitative comparative analysis based on cue utilization theory.

BACKGROUND: The sudden outbreak of COVID-19 in early 2020 pushed the online health-care communities (OHCs) into the public eye in China. However, OHCs is an emerging service model, which still has many problems such as low patient trust and low patient utilization rate. Patients are the users and recipients of web-based medical services, as well as the core of medical services. Thus, based on cue utilization theory, this paper studies combination effect of influencing factors in patients' purchase of web-based medical services through the qualitative comparative analysis method of fuzzy sets (fsQCA). METHODS: This paper discards statistical methods based on variance theory-based relationships between explanatory and explained variables and uses a construct theory-based fuzzy set qualitative comparative analysis (fsQCA) approach to elucidate such complex relationships of patients' online purchasing behavior. We use a crawler to automatically download information from Haodf.com. This study crawled data in August 2020, involving 1210 physicians. RESULTS: Service price, reputation and service quality are the key factors for patients' purchasing behavior. Physician's online reputation, online medical service price, number of published articles, mutual-help group, and appointment registration affect patients' purchasing behavior by means of weighted variation. Only when a high scope of internal attribute-related cue elements and a low scope of external attribute-related cue elements are combined with each other in a specific form, patients will generate purchase behavior. CONCLUSION: This paper clarifies the complex causes that promote to patients' purchasing behavior of web-based medical services, enriches and develops the relevant theories in the field of consumer purchasing behavior and online health-care communities market research, and has implications for governments, platforms, physicians and patients in the event of web-based medical service purchases.

Drivers for agility in times of crisis

Purpose Agile organisations do not arise from a single characteristic but comprise a combination of various aspects. Thus, this study aims to examine the combined effects on organisational agility regarding firms' utilisation of digital technology to create value during the COVID-19 pandemic, how firms perceive uncertainty related to their own organisational response and the degree to which they have an entrepreneurial mindset. Design/methodology/approach Using a fuzzy-set qualitative comparative analysis, this study investigates 355 established firms and start-ups in Norway. Findings This study finds digitalisation is required for agility to develop, but that it needs to be combined with having an entrepreneurial mindset or being a start-up and lower levels of perceived uncertainty. Hence, entrepreneurial mindset and low uncertainty are important factors for digitalisation, and in turn, for agility to be developed. Originality/value Agility is recognised as being pivotal for firms' competitiveness and innovation and argued to be significant in overcoming sudden economic shocks. However, lacking empirical scrutiny are investigations into the relationship between digitalisation and agility, and how digitalisation might act as a driver for building agility, which the authors tackle herein.

From aggregations to multimethod case configurations. Case diversity in quantitative analysis when explaining COVID-19 fatalities

Three quantitative methods are compared for their ability to understand different COVID-19 fatality ratios in 33 OECD countries. Linear regression provides a limited overview without sensitivity to the diversity of cases. Cluster Analysis and Dynamic Patterns Synthesis (DPS) gives scrutiny to the granularity of case similarities and differences, and reveals case exceptions. Qualitative Comparative Analysis (QCA) develops causal theory about what conditions are sufficient for explaining outcomes by using robust and transparent conventions. Configurational case-based methods offer important advantages over inferential statistics when there is a need to focus on diversity in small n. These techniques can be combined as multi-methods. DPS and QCA can be used concurrently to aid research insights. These methods are also strengthened by additional qualitative evidence about the cases. [ FROM AUTHOR] Copyright of International Journal of Social Research Methodology is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A Study on the Path to the Sustainable Development of Sports-Consuming Cities-A Qualitative Comparative Analysis of Fuzzy Sets Based on Data from 35 Cities in China.

The prospects of China's sports sector hinge on how sports cities can thrive sustainably in the context of the new global pandemic, unlocking consumer potential and boosting domestic demand. In this study, 35 Chinese cities were chosen as research samples, and research methods such as literature, logical analysis, and fuzzy-set qualitative comparative analysis were used to select conditional variables such as government policy promotion and assistance, expert human resources, sports competitions and events, stadiums and facilities, and sponsorship by sports enterprises to examine how Chinese sports-consuming cities can develop sustainably. The research discovered that sports contests and events, as well as stadiums and facilities, are the essential prerequisites for the sustainable growth of sports-consuming cities, and that diverse combinations of the two may play a vital role in different circumstances. For the sustainable development of sports-consuming cities, there are four clusters and three models, which correspond to the "Venue + Event" model (Clusters 1 and 2), the "Event-led" model (Cluster 3), and the "Venue-led" model (Cluster 4). To encourage the high-quality growth of China's sports business, each city may establish its development strategy based on its unique qualities. The goal is to supply Chinese expertise for the long-term growth of Western sports cities.

Identifying conditions for a third dose intention of COVID-19 vaccination in college students: A fuzzy-set qualitative comparative analysis.

Background: During the pandemic, a third dose of the COVID-19 vaccine effectively reduces the proportion of severe cases in those infected, but vaccine hesitancy impedes this reasonable prevention method. Epidemic control in China is being tested due to the large population base, especially in crowded places like college campuses. This study aimed to explore the configuration paths of psychological antecedents for college students to receive a third COVID-19 vaccine. Methods: An anonymous cross-sectional survey was carried out in five universities in Wuhan using convenience sampling. A long version of the 5C 7-point Likert scale was used to measure college students' intention and psychological antecedents on the third dose of the COVID-19 vaccine. A fuzzy-set Qualitative Comparative Analysis (QCA) approach was performed to explore the configuration of conditions to the vaccination willingness. Results: 31.67% of respondents surveyed did not receive their third dose of the COVID-19 vaccine. The score of intention to get the vaccine for college students who did not receive the booster vaccine was 4.93 (±1.68). Average scores of 5.19 (±1.24), 4.35 (±1.75), 4.02 (±1.45), 5.84 (±1.23), and 4.61(±1.32) were reported for confidence, complacency, constraints, calculation, and collective responsibility in them. QCA showed high confidence and collective responsibility playing a central role in third dose vaccination intention. Meanwhile, low confidence and collective responsibility are the core conditions of low vaccination willingness. Conclusion: Eliminating vaccine hesitancy necessitates focusing on the psychological antecedents of vaccination intentions to identify critical targets for policy and interventions. This study identified trust and collective responsibility are core elements of the psychological antecedents of college students' intention to receive the booster vaccine for COVID-19. To achieve herd immunity as soon as possible, health administration and campus can start with vaccine confidence-building and collective responsibility cultivation to take appropriate actions and measures to improve coverage of the booster vaccination.