Dual Perspective Research Articles

Audio-visual event localization with dual temporal-aware scene understanding and image-text knowledge bridging

Audio-visual event localization (AVEL) task aims to judge and classify an audible and visible event. Existing methods devote to this goal by transferring pre-trained knowledge as well as understanding temporal dependencies and cross-modal correlations of the audio-visual scene. However, most works comprehend the audio-visual scene from an entangled temporal-aware perspective, ignoring the learning of temporal dependency and cross-modal correlation in both forward and backward temporal-aware views. Recently, transferring the pre-trained knowledge from Contrastive Language-Image Pre-training model (CLIP) has shown remarkable results across various tasks. Nevertheless, since audio-visual knowledge of the AVEL task and image-text alignment knowledge of the CLIP exist heterogeneous gap, how to transfer the image-text alignment knowledge of CLIP into AVEL field has barely been investigated. To address these challenges, a novel Dual Temporal-aware scene understanding and image-text Knowledge Bridging (DTKB) model is proposed in this paper. DTKB consists of forward and backward temporal-aware scene understanding streams, in which temporal dependencies and cross-modal correlations are explicitly captured from dual temporal-aware perspectives. Consequently, DTKB can achieve fine-grained scene understanding for event localization. Additionally, a knowledge bridging (KB) module is proposed to simultaneously transfer the image-text representation and alignment knowledge of CLIP to AVEL task. This module regulates the ratio between audio-visual fusion features and CLIP’s visual features, thereby bridging the image-text alignment knowledge of CLIP and the audio-visual new knowledge for event category prediction. Besides, the KB module is compatible with previous models. Extensive experimental results demonstrate that DTKB significantly outperforms the state-of-the-arts models.

Behavioral Modeling of Drivers near Speed Control Cameras: A Dual Perspective from Micro and Macro Data

The present study investigates the efficacy of speed cameras in managing vehicle speeds and their influence on various driver demographics within the operational context of the cameras. The research, conducted as a case study in Iran, comprises both macroscopic and detailed analyses, quantifying vehicle speeds at different spatial points relative to the speed camera location—upstream, adjacent to, and downstream of the camera—using a manual laser speedometer. Furthermore, the study examines diverse driver behavior metrics, including vehicle type, speeds at different locations, lane changes, braking actions, and measures such as obscuring license plates. Statistical analyses show that speed cameras effectively reduce speeds across different user groups and lead to increased braking and lane-changing behaviors, particularly among light vehicle categories. Moreover, the study reveals distinct behavioral patterns between indigenous and non-indigenous drivers. In addition, a multi-layer perceptron neural network model successfully approximates user speed selection behaviors within the operational range of speed cameras. Overall, this research provides valuable insights into the effectiveness of speed cameras and their impact on diverse driver demographics, contributing to a deeper understanding of advanced speed control mechanisms.

Leading while playing: How leader fun pursuit affects leadership perceptions and evaluations

AbstractAlthough pursuing fun seems contradictory to work, it may yield beneficial outcomes for not only employees but also leaders in the workplace. The present paper aims to bridge the gap between the workplace fun/play literature and leadership research by introducing the concept of leader fun pursuit and examining its influence on followers' evaluations. Moreover, drawing on the dual perspective model of social evaluation and expectancy violation theory, we examine the effects of leader fun pursuit on followers' perceptions of leader attributes and evaluations of leadership, and posit a gender‐contingent boundary condition. We conducted three studies to develop a scale and examine our hypotheses. Study 1 (four samples, total N = 734) developed a four‐item scale to measure leader fun pursuit and established its reliability and validity. Study 2 (N = 309) used a multi‐wave design to examine the full model. Study 3 (N = 279) used a vignette‐based experiment to strengthen the internal validity of our conceptual model. We found that leader fun pursuit generally enhances followers' evaluations of the leader, and this effect was especially pronounced for female leaders. Overall, we introduce a novel approach to effective leadership and examine the gender differences therein.

Predictive modeling of preoperative acute heart failure in older adults with hypertension: a dual perspective of SHAP values and interaction analysis

BackgroundIn older adults with hypertension, hip fractures accompanied by preoperative acute heart failure significantly elevate surgical risks and adverse outcomes, necessitating timely identification and management to improve patient outcomes.Research objectiveThis study aims to enhance the early recognition of acute heart failure in older hypertensive adults prior to hip fracture surgery by developing a predictive model using logistic regression (LR) and machine learning methods, optimizing preoperative assessment and management.MethodsEmploying a retrospective study design, we analyzed hypertensive older adults who underwent hip fracture surgery at Hebei Medical University Third Hospital from January 2018 to December 2022. Predictive models were constructed using LASSO regression and multivariable logistic regression, evaluated via nomogram charts. Five additional machine learning methods were utilized, with variable importance assessed using SHAP values and the impact of key variables evaluated through multivariate correlation analysis and interaction effects.ResultsThe study included 1,370 patients. LASSO regression selected 18 key variables, including sex, age, coronary heart disease, pulmonary infection, ventricular arrhythmias, acute myocardial infarction, and anemia. The logistic regression model demonstrated robust performance with an AUC of 0.753. Although other models outperformed it in sensitivity and F1 score, logistic regression’s discriminative ability was significant for clinical decision-making. The Gradient Boosting Machine model, notable for a sensitivity of 95.2%, indicated substantial capability in identifying patients at risk, crucial for reducing missed diagnoses.ConclusionWe developed and compared efficacy of predictive models using logistic regression and machine learning, interpreting them with SHAP values and analyzing key variable interactions. This offers a scientific basis for assessing preoperative heart failure risk in older adults with hypertension and hip fractures, providing significant guidance for individualized treatment strategies and underscoring the value of applying machine learning in clinical settings.

Elite poems and mass proverbs: exploring the historic landscape in Nanchang City, China

The rapid process of urbanisation has led to the erosion of the preservation of features of urban landscape. Research on historical landscapes in ancient urban planning has predominantly concentrated on the elite class, neglecting the broader population. Nanchang, a city with a history spanning over two millennia of urban development, is the focus of this study. The study integrates elite poems and mass proverbs through GIS spatial matching and KH Coder word frequency analysis to research the historic landscape in Nanchang City. The research uncovers that the elite class focuses on the historical, literary, and aesthetic aspects of Nanchang, while the masses emphasise urban structure, functionality, and aspirations. These dual perspectives underscore Nanchang’s evolution from inception to formalisation, highlighting its ability to cater to diverse societal needs. The efforts on the distribution of landscape spots and strict modulus reflect the adaptability and sustainability of Nanchang City.

How does China’s Winter Heating policy impact corporate sustainable development performance?

The China’s Winter Heating policy plays a crucial role in China’s regional environmental regulatory framework, particularly concerning the challenge of atmospheric pollution. This study investigates the impact of this policy on corporate sustainable development performance in the “2+26” cities of the Beijing, Tianjin and Hebei region (BTH2+26) at the micro-level. It employs a dual perspective focusing on emission reduction and efficiency enhancement (i.e., sustainable development), utilizing a DID model based on the policy shock from the first implementation of the China’s Winter Heating policy in 2017. The findings indicate that this policy not only effectively promotes pollution reduction among heavy-polluting companies, thereby enhancing their environmental performance, but also improves their financial performance. Robustness tests confirm the significance of these results. Mechanism analysis reveals that the policy’s facilitative effect on heavy-polluting companies is mediated through promoting green innovation and easing financing constraints, with the innovation investment being the main channel to promote the corporate environmental performance. Heterogeneity analysis shows differential impacts across company nature and industry attributes, highlighting the policy’s varied effects on environmental performance and financial performance across sectors. This research contributes empirical evidence and policy insights into enhancing sustainable development performance among heavy-polluting companies under the China’s Winter Heating policy framework.

IGF-1 levels in the general population, heart failure patients, and individuals with acromegaly: differences and projections from meta-analyses—a dual perspective

BackgroundThe complex relationship between insulin-like growth factor 1 (IGF-1) levels and heart failure (HF) is not fully understood, particularly across different populations and conditions. This meta-analysis aims to elucidate the dual perspectives of IGF-1 levels in the general population, HF patients, and individuals with treatment-naïve acromegaly, highlighting IGF-1 as a biomarker and potential therapeutic target in HF management.MethodsStudies were searched across multiple electronic databases up to January 2024 and independently identified by reviewers. The outcomes were analyzed using RevMan 5.4 and STATA 15.ResultsA total of 25 articles were ultimately included in the analysis. Six studies compared IGF-1 levels between HF patients and non-HF controls, revealing significantly lower IGF-1 levels in HF patients (mean difference −20.93; 95% CI −37.88 to −3.97; p = 0.02). This reduction was consistent across various HF subtypes and severities. In addition, individuals with intermediate IGF-1 levels had a lower risk of developing HF [risk ratio (RR) 0.78; 95% CI 0.74–0.83; p < 0.01] and HF-related mortality (RR 0.98; 95% CI 0.97, 0.99; p < 0.01) compared to those with low IGF-1 levels, suggesting a protective role for maintaining adequate IGF-1 levels. Conversely, treatment-naïve acromegaly patients, characterized by excessively high IGF-1 levels, showed a significantly higher incidence of both diastolic HF [odds ratio (OR) 9.08; 95% CI 6.20–13.29; p < 0.01] and systolic HF (OR 13.1; 95% CI 6.64–25.84; p < 0.01), implicating supraphysiological IGF-1 levels in adverse cardiac outcomes.ConclusionsOur meta-analysis highlights the complex interplay between IGF-1 levels and HF. We found that reduced IGF-1 levels are commonly observed in HF patients and are associated with an increased risk of HF and higher HF-related mortality. Conversely, excessively high levels, as observed in acromegaly, are linked to a higher incidence of HF. Based on these results, it is recommended that cardiac function be closely monitored in patients with reduced IGF-1 levels and in those with acromegaly. These findings suggest that IGF-1 could hold potential prognostic value for risk stratification in HF.

Impacting Elements of Metaverse Platforms’ Intentional Use in Cultural Education: Empirical Data Drawn from UTAUT, TTF, and Flow Theory

This study aims to address the need for design guidelines in developing a cultural-heritage-based metaverse educational system. Using the UTAUT, the TTF model, and Flow Theory, a theoretical framework is constructed. Through qualitative research based on the GT, three user perception factors—presence, interactivity, and narrativity—are introduced as external variables to explore the relationship between these factors and users’ willingness to adopt the cultural heritage metaverse system. The study examines this relationship from the dual perspectives of user perception and technology acceptance. A scale was designed to test the theoretical model empirically, and 298 valid responses were collected through a structured process involving GT coding, pre-testing, and formal surveys. The findings indicate that interactivity, narrativity, and presence significantly enhance the flow experience, while factors such as performance expectancy, effort expectancy, social influence, facilitating conditions, technology–task fit, and flow positively influence users’ intention to adopt the system. Among these, technology–task fit emerged as the most influential factor. This integrated approach reduces subjectivity and bias in criteria determination, enhancing the objectivity and precision of cultural heritage metaverse system assessments and making the system more responsive to user needs.

Text analysis and optimization strategy of an app’s privacy policy from the perspective of dual perception: taking Chinese shopping apps as an example

Purpose This paper aims to conduct an in-depth analysis of the shortcomings of apps’ privacy policies and to propose improvement and optimization strategies, which are of great significance for establishing a transparent and responsible privacy protection framework that ensures compliant collection and use of users’ information and effective protection of their privacy. Design/methodology/approach This paper obtained privacy policy texts for 100 shopping apps through Web crawlers and manual downloads. Based on the perspective of perceived usefulness, thematic analysis is conducted through the latent Dirichlet allocation topic model and comparison with existing policies. Based on the perspective of perceived ease of use, readability analysis is conducted through content analysis and formula calculation. Findings The apps privacy policies can be divided into seven themes. The authors benchmark these seven topics with the Personal Information Protection Law of the People’s Republic of China, the E-Commerce Law of the People’s Republic of China and the General Data Protection Regulation. It is found that there are omissions in the information collection and use and juvenile protection of the existing apps. Through the indicators’ readability analysis and calculation, it is found that the existing apps privacy policies have good performance in the readability indicators such as naming method, frame directory and so on. However, text personalization and text readability need to be improved and optimized. Originality/value At the theoretical level, this paper constructs a model from the dual perception perspectives of perceived usefulness and perceived ease of use and analyses the apps’ privacy policy texts at a fine-grained level. At the practical level, based on large-scale apps’ privacy policy text data, this paper conducts multi-dimensional research from theme analysis, authoritative law benchmarking analysis, content analysis and text readability calculation and analysis. At the same time, this paper identifies the current problems of apps’ privacy policies and puts forward countermeasure suggestions for their content improvement and optimization.

The Impact of Free Trade Zones on Corporate Sustainability Performance: An Empirical Examination from the Dual Perspectives of Financial and Environmental Performance

As a “testing ground” for a new round of institutional innovation, China’s pilot free trade zones (FTZs) have created favorable development conditions for listed companies and significantly influenced their sustainability performance. Utilizing data from Shanghai and Shenzhen A-share listed companies from 2010 to 2022, this study uses the establishment of FTZs as a “quasi-natural experiment” and measures corporate sustainability performance by combining financial and environmental performance. A PSM-DID model is constructed to explore the impact of FTZ construction on corporate sustainability performance. The findings are as follows: (1) The establishment of FTZs significantly enhances both the financial and environmental performance of companies. (2) FTZs promote corporate sustainability performance by reducing transaction costs and improving corporate innovation levels. (3) The establishment of FTZs has a significantly positive impact on the sustainability performance of companies in highly competitive industries, non-labor-intensive industries, high-tech enterprises, and large-scale companies. This study reveals the impact and transmission mechanisms of FTZs on corporate sustainability performance, providing new empirical evidence for the future direction of corporate sustainable development in China.

Transformations in Rural Community Order: A Case Study of Puqian Village, Jiangxi Province, from 1978 to 2022

Since the reform and opening-up, village communities in China have undergone significant transformations alongside rapid modernization. The reconstruction of these communities is a key issue in China’s rural revitalization efforts and necessitates an analysis of the evolutionary characteristics and drivers of village community order. This study defines the concept of village community order and develops corresponding evaluation indicators and quantitative methods. Taking Puqian Village in Ji’an County, Jiangxi Province, as a case study, the research explores the evolution of village community order across distinct development stages—1978, 1985, 2003, and 2022. Data for the study were collected through participatory rural appraisal, remote sensing image processing, and GIS spatial analysis. The results reveal that since the reform and opening-up, Puqian Village has experienced increasing spatial complexity, disordered spatial structures, unbalanced population dynamics, and a weakening social network. These changes were especially pronounced during the periods of market-oriented development and urban–rural integration. The evolution of village community order is influenced by factors such as livelihood transformations, the decline of local culture, the dissolution of public authority, and weakened governance structures. By analyzing village community order from the dual perspectives of social and spatial order, this study provides a systematic framework for understanding village community changes.

Cyber resilience in organisations and supply chains: from perceptions to actions

PurposeThis empirical study investigates the direct and indirect effects on managers’ perceptions of cyber risks, the implementation of cyber resilience strategies and the perceived effectiveness of these strategies for supply chains. Cyber risks pose significant threats to organisations and supply chains. Yet they remain insufficiently addressed and managed.Design/methodology/approachPrimary data were collected from a sample of Italian organisations using a survey. The structural equation modelling methodology was employed to empirically investigate cyber resilience strategies in supply chains.FindingsResults indicate that effective cyber resilience is linked to awareness of the negative impacts of cyber risks, particularly supply chain disruptions. This awareness leads to the adoption of various cyber resilience strategies. According to managers' perceptions, several strategies are identified in the study as the most effective in enhancing the cyber resilience supply chains. The findings offer insights for managers regarding the relationship between cyber risk perceptions, supply chain cyber resilience strategies and their effectiveness. These relationships are studied using the theory of perceived risk and the dynamic capabilities theory.Originality/valueThis study advances knowledge for academics and practitioners in the fields of supply chain resilience and supply chain risk management. It contributes to the development of a risk-based thinking model in organisations and supply chains by drawing upon a dual theoretical perspective.

Assessing the impact of the national revitalization plan for old revolutionary base areas on green development

Achieving green development in Old Revolutionary Base Areas (ORBAs) is an urgent task to narrow the regional gap and promote high-quality development. Starting from the dual perspective of development and environment, this paper used the Multi-period DID model to assess the impacts of the National Revitalization Plan (NRP) for ORBAs on economic growth and environmental quality, as well as its transmission mechanism, and to explore whether the implementation of the plan can promote the covered areas to achieve green development. The results find that the implementation of NRP boosts the ORBAs to achieve green development. The NRP realize green development through industrial restructuring, technological progress, ecological space governance, and public service provision. The ORBAs of Jiangxi-Fujian- Guangdong, Left-Right River, and Sichuan-Shaanxi, counties situated in mountainous terrain and with higher quartile of economy and environment play a more prominent role in promoting green development. This study provides practical inspiration and theoretical reference for ORBAs to realize green development.

A novel hybrid forecasting system for crude oil futures prices: A dual perspective of deterministic forecasting and uncertainty analysis

The crude oil market occupies a crucial place in the composition of the global economy, however, the high level of uncertainty in crude oil prices makes it a challenging task to construct reliable forecasting techniques to obtain reliable expected results. Therefore, to effectively cope with the high uncertainty and the technical limitations of existing forecasting studies, this study constructs a hybrid forecasting system from the dual perspectives of deterministic forecasting and uncertainty analysis. With the concept of “denoising-integration” as the core, the system integrates several denoising techniques, econometric methods, and artificial intelligence methods, and establishes a hybrid forecasting model with high accuracy and robustness with the assistance of multi-objective optimization theory. Furthermore, by introducing fuzzy theory onto the basis of deterministic prediction results, an interval forecasting model with a narrower interval width and better comprehensive performance is constructed under the premise of ensuring that the coverage of prediction intervals meets the requirements of the confidence level. In this study, the forecasting system is applied to four global core crude oil futures markets, and the empirical study finds that the performance is improved by more than 50 % compared with the benchmark model, which has an impressive performance advantage.

How to Bridge Cognitive and Cultural Models of Religious Evolution

The scientific study of religion has roots in at least two traditions: a cognitive tradition which typically uses experimental studies to examine the proximal psychological processes underlying religious belief and ritual, and an anthropological tradition which uses historical and ethnographic data to examine how religious systems culturally evolve in social groups. In Religion Evolving, Purzycki and Sosis bridge both traditions and encourage a more integrated evolutionary science of religion. In this essay, I present three suggestions for how to make this science as ambitious and collaborative as possible. These suggestions are: (1) to move beyond straw man debates that pit byproduct models against functional models of religious evolution and acknowledge that these models are compatible from a dual inheritance perspective, (2) to evaluate functionalist claims with caution, recognizing how and when religion is adaptive vs. maladaptive for secular society, and (3) to avoid reductive definitions of religion and embrace religious pluralism. With these lessons in mind, we can usher in a bolder evolutionary science of religion that draws from both cognitive and cultural traditions.

Discourse analysis on academic integrity generative AI: Perspectives from science and mathematics students in higher education

Artificial Intelligence (AI) has significantly influenced the current educational system, offering various benefits to teachers and students. However, the integration of AI in education also poses challenges, particularly in maintaining academic integrity. This study investigates the perspectives of 24 science and mathematics students on the impact of Generative AI (GAI) on academic integrity, a core principle in higher education. Using an exploratory design, the findings reveal a dual perspective: GAI can enhance learning and research by providing advanced tools and resources, yet it also risks undermining ethical standards if misused. The study highlights the importance of balancing technological advancements with the maintenance of academic integrity, emphasizing the need for responsible AI usage and the development of policies to mitigate potential negative impacts. Further research is needed to explore the impact of GAI on academic integrity across different disciplines and educational contexts.

DPNet: Scene text detection based on dual perspective CNN-transformer.

With the continuous advancement of deep learning, research in scene text detection has evolved significantly. However, complex backgrounds and various text forms complicate the task of detecting text from images. CNN is a deep learning algorithm that automatically extracts features through convolution operation. In the task of scene text detection, it can capture local text features in images, but it lacks global attributes. In recent years, inspired by the application of transformers in the field of computer vision, it can capture the global information of images and describe them intuitively. Therefore, this paper proposes scene text detection based on dual perspective CNN-transformer. The channel enhanced self-attention module (CESAM) and spatial enhanced self-attention module (SESAM) proposed in this paper are integrated into the traditional ResNet backbone network. This integration effectively facilitates the learning of global contextual information and positional relationships of text, thereby alleviating the challenge of detecting small target text. Furthermore, this paper introduces a feature decoder designed to refine the effective text information within the feature map and enhance the perception of detailed information. Experiments show that the method proposed in this paper significantly improves the robustness of the model for different types of text detection. Compared to the baseline, it achieves performance improvements of 2.51% (83.81 vs. 81.3) on the Total-Text dataset, 1.87% (86.07 vs. 84.2) on the ICDAR 2015 dataset, and 3.63% (86.72 vs. 83.09) on the MSRA-TD500 dataset, while also demonstrating better visual effects.

Comparison of the Achieved and Expected Competence Level of New Graduate Nurses: Two Cross-Sectional Studies.

To explore and compare the self-perceived competence level of new graduate nurses with the expected competence level that nurse managers believe new graduate nurses should have in general. Two cross-sectional empirical studies. Two independent cross-sectional studies were carried out in 12 tertiary hospitals in September 2020 and November 2021, respectively. Participants were 1017 new graduate nurses with less than 2 years of work experience and 306 nurse managers who completed an online survey. The score of self-perceived nursing competence of new graduate nurses was 74.77 ± 14.35, and the expectation of nurse managers was 74.21 ± 15.04. The values of 18 items were significantly different between the two of them (p < 0.05), and there were only three items showed higher expectations of nurse managers than the self-rated values of new graduate nurses. Results of latent profile analysis revealed that this cohort of new graduate nurses could be divided into three subgroups, named risky competent (11.1%), medium competent (46.0%) and advanced competent (42.9%). When comparing, the nurse managers' expected competence level was between the value of 'medium competent' group and 'advanced competent' group. Our study adopted a dual perspective comparison of nurse managers and new graduate nurses, which broke through the limitations of the previous single perspective study of new graduate nurses' nursing competence. This study highlights the importance of the consistency in new graduate nurses' nursing competence from the perspectives of new graduate nurses and nurse managers. This study showed a generally good match of actual nursing competence level of new graduate nurses and the expected level from nurse managers. While there was significant individual heterogeneity in the competence score of new graduate nurses, three subgroups were identified through the individual-centred analysis of latent profile analysis. Therefore, Nurse managers need to systematically adjust the standardized training programs and teaching methods for new graduate nurses according to the population characteristics and take precise interventions to improve nursing competence of new graduate nurses. We adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. No Patient or Public Contribution.

Classical Sociologists' views of the Nation and its Main Paradigms About the Origin of the Kurds

This interdisciplinary article addresses two primary investigations: the sociological standpoint on the notion of nation and fundamental approaches concerning the Kurds' origin. Consequently, we seek responses to the following pair of inquiries: Firstly, it delves into the foundational aspects of understanding the origin of Kurds and Kurdish nationalism, questioning its historiography. Secondly, it investigates the categorization of fundamental ideas and approaches regarding nation and nationalism and examines the extent of their influence on Kurdish literature in the related field. The study takes a dual perspective. Initially, it explores the perspectives of classical sociologists such as Karl Marx, Emile Durkheim, Max Weber, and George Simmel on the concept of nation. In contrast to historical perspectives, sociologists analyze the notion through the prisms of social solidarity, moral environment, citizenship, Western rationality, and the nation as a superstructure. The second part of the article delves into the core approaches of primordialism, constructionism, and ethno-symbolism. The study concludes that the investigation into the origins of Kurds is a relatively recent development, influenced by a myriad of external and internal factors. Kurdish researchers have conducted their studies within the framework of the three above-mentioned methods, with visible differences of opinion regarding the origin of Kurds and Kurdish nationalism. Simultaneously, a distinct approach is emerging, asserting the uniqueness of the Kurdish issue and suggesting it transcends common modern paradigms.

Environmental regulation and enterprise green innovation: a dual heterogeneity perspective

ABSTRACT Based on institutional theory, environmental regulation (ER) is considered the primary factor in stimulating green innovation (GI) in enterprises. The existing literature has extensively explored the ER-GI relationship, but conclusions are still inconsistent, which is related to neglecting the dual heterogeneity in this relationship. Hence, we divide ER into command ER (CER) and incentive ER (MER), and GI into compliant GI (CGI) and strategic GI (SGI) to address this research gap. Employing a questionnaire survey of Chinese manufacturing enterprises, we re-examined the ER-GI relationship and tried to identify the moderating effect of environmental ethics (EE). The results show that CER and MER positively affect CGI and SGI. Furthermore, under the CER, there is increased accessibility to adopting CGI. Under the MER, the likelihood of choosing SGI is higher. Moreover, we find that heterogeneous ERs are more conducive to SGI under the moderating effect of EE. This study has significantly contributed to the literature on the ER-GI relationship.