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Social media use is prevalent today, but there is a possibility that it might go out of control and cause negative consequences. Furthermore, by using social media at work, businesses may develop their networks, communicate in a productive manner and ultimately expand the efficiency. The purpose of this study is to investigate the effect of social media use (SMU) on job performance (JP) through sequential mediators such as social capital dimensions (SC), self-efficacy (SE), job satisfaction (JS) and knowledge sharing (KS) in Indian Public Universities.

Serial mediation model has been used in the study to analyse the relationship. Data is collected from teaching faculty (n = 702) who use social media in Indian public universities. The study has assessed the association between variables using structural equation modelling.

The findings suggest that the dimensions of SC, SE, JS and KS sequentially mediated the effect of SMU on JP. In light of the results, the SMU specifies prerequisites for the development of various dimensions of SC. Similarly, the rest of the mediating constructs further affect the other constructs, which ultimately positively affect JP. The final result shows that the indirect effect between social media use and job performance is positive and significant.

The study provides practical suggestions for university administration regarding the use of social media for teaching faculty.

No research has been done regarding social media use affecting the job performance of teaching faculty through serial mediation in public universities. In this respect, this study represents an original attempt to conduct such research.

This paper explores the cognitive impacts of social media on employees in workplace environments, focusing on how digital interactions disrupt cognitive functions and employee engagement. It bridges theoretical models of cognitive psychology with practical human resource (HR) strategies to mitigate these effects.

The methodology includes a review of relevant cognitive and psychological theories – namely cognitive load theory (Sweller, 1988), distraction-conflict theory (Baron, 1986), and engagement theory (Schaufeli et al., 2002). The discussion extends to practical interventions such as policy adjustments, employee training and technological solutions, assessing their application within organizational contexts to address social media challenges.

The research findings have significant practical implications. The author reveals that continuous social media notifications can lead to distraction conflicts and decreased employee engagement, impacting cognitive load. Effective HR interventions, such as clear guidelines, digital detox initiatives and technology-based social media access control, can enhance focus and productivity, improving workplace outcomes.

This paper contributes to discussions on social media’s role in workplace dynamics by combining cognitive psychological theories with practical HR applications. It presents a structured approach to understanding and managing digital distractions, offering a new framework for organizations aiming to balance technological advancements with employee well-being.

In the context of green development in China, the circumstance in which Environmental, Social and Governance (ESG) ratings function has changed. As an important external governance mechanism of sustainable development, ESG ratings can also be a two-edged sword for the implementation of carbon emission reduction. This research examines the connection of ESG ratings and corporate carbon emission reduction in the context of green development. This present study postulates that the impact of ESG ratings on carbon emission reduction performance in the context of green development is inverted U-shaped.

To obtain empirical evidence for the hypotheses proposed, this study makes an empirical test based on the two-way fixed effects model. The data is taken from listed Chinese manufacturing firms between 2012 and 2021.

The study reveals that there is a significant inverted U-shape relationship between ESG ratings and carbon emission reduction performance in the context of green development. Managerial myopic behaviour plays a positive moderating role in the above relationship. In addition, it makes the inflection point of inverted U-shaped curve move to left. Heterogeneity analyses show that the above inverted U-shaped relationship is more significant for firms that don’t hire CEO with environmental protection background or big four accounting firms.

In the background of green development, this study helps to understand dual influence of ESG ratings on corporate carbon emission reduction deeply. It is beneficial to guide enterprises to utilize ESG ratings mechanism reasonably, thus enhancing the effectiveness of carbon emission reduction. This study provides decision-making reference for government to accelerate low-carbon transformation in microcosmic field.

Vision transformers (ViT) detectors excel in processing natural images. However, when processing remote sensing images (RSIs), ViT methods generally exhibit inferior accuracy compared to approaches based on convolutional neural networks (CNNs). Recently, researchers have proposed various structural optimization strategies to enhance the performance of ViT detectors, but the progress has been insignificant. We contend that the frequent scarcity of RSI samples is the primary cause of this problem, and model modifications alone cannot solve it.

To address this, we introduce a faster RCNN-based approach, termed QAGA-Net, which significantly enhances the performance of ViT detectors in RSI recognition. Initially, we propose a novel quantitative augmentation learning (QAL) strategy to address the sparse data distribution in RSIs. This strategy is integrated as the QAL module, a plug-and-play component active exclusively during the model’s training phase. Subsequently, we enhanced the feature pyramid network (FPN) by introducing two efficient modules: a global attention (GA) module to model long-range feature dependencies and enhance multi-scale information fusion, and an efficient pooling (EP) module to optimize the model’s capability to understand both high and low frequency information. Importantly, QAGA-Net has a compact model size and achieves a balance between computational efficiency and accuracy.

We verified the performance of QAGA-Net by using two different efficient ViT models as the detector’s backbone. Extensive experiments on the NWPU-10 and DIOR20 datasets demonstrate that QAGA-Net achieves superior accuracy compared to 23 other ViT or CNN methods in the literature. Specifically, QAGA-Net shows an increase in mAP by 2.1% or 2.6% on the challenging DIOR20 dataset when compared to the top-ranked CNN or ViT detectors, respectively.

This paper highlights the impact of sparse data distribution on ViT detection performance. To address this, we introduce a fundamentally data-driven approach: the QAL module. Additionally, we introduced two efficient modules to enhance the performance of FPN. More importantly, our strategy has the potential to collaborate with other ViT detectors, as the proposed method does not require any structural modifications to the ViT backbone.

In today’s turbulent and complex era, initiative behavior is becoming more drawn to construction projects but challenging to arouse as it is free of the established regulations in project practice. Given the prevalence of social media (SM) in modern workplaces, this study is thereby motivated to investigate whether and how SM use can act to drive initiative behavior of construction project members (PMs) in this context.

This study sharply examines two distinct types of SM use – work-related and social-related – to explore their roles in driving the initiative behavior of construction PMs. Additionally, self-determination theory is employed to explore their underlying translation mechanisms and associated boundary conditions. A survey dataset collected from 229 construction PMs is used to empirically test the proposed theoretical model.

Empirical results show that role-breadth self-efficacy, psychological safety and project identification, by satisfying basic psychological needs respectively, act as crucial bridging roles in translating SM use into initiative behavior of PMs. Such mediation effects are applied to both work-related and social-related SM use with varied mechanisms. Besides, prevention focus is found to be a contingent moderator on these relationships, with a strengthening role toward role-breadth self-efficacy and a weakening role toward project identification.

This study digs into the nuanced mechanisms of how SM use benefits construction projects, especially in terms of PMs’ initiative. The findings of this research afford new insights into effectively invigorating the initiative behavior of construction PMs under the current digital momentum.

Several chaotic system-based encryption techniques have been presented in recent years to protect digital images using cryptography. The challenges of key distribution and administration make symmetric encryption difficult. The purpose of this paper is to address these concerns, the novel hybrid partial differential elliptical Rubik’s cube algorithm is developed in this study as an asymmetric image encryption approach. This novel algorithm generates a random weighted matrix, and uses the masking method on image pixels with Rubik’s cube principle. Security analysis has been conducted, it enhances and increases the reliability of the proposed algorithm against a variety of attacks including statistical and differential attacks.

In this light, a differential elliptical model is designed with two phases for image encryption and decryption. A modified image is achieved by rotating and mixing intensities of rows and columns with a masking matrix derived from the key generation technique using a unique approach based on the elliptic curve and Rubik’s cube principle.

To evaluate the security level, the proposed algorithm is tested with statistical and differential attacks on a different set of test images with peak signal-to-noise ratio, unified average changed intensity and number of pixel change rate performance metrics. These results proved that the proposed image encryption method is completely reliable and enhances image security during transmission.

The elliptic curve–based encryption is hard to break by hackers and adding a Rubik’s cube principle makes it even more complex and nearly impossible to decode. The proposed method provides reduced key size.

We investigated the association of COVID-19 indicators and economic uncertainty indices on payment-based system cryptocurrency (i.e. Bitcoin, Ripple and Dogecoin) returns.

We used an autoregressive distributed lag (ARDL) model for panel data and performed robustness checks by utilizing a random effect model (REM) and generalized method of moments (GMM). There are 25 most adopted cryptocurrency’s countries and the data spans from 22 March 2021 to 6 May 2022.

This research discovered four findings: (1) the index of COVID-19 vaccine confidence (VCI) recovers the economic and Bitcoin has become more attractive, causing investors to shift their investment from Dogecoin to Bitcoin. However, the VCI was revealed to be insignificant to Ripple; (2) during uncertain times, Bitcoin could perform as a diversifier, while Ripple could behave as a diversifier, safe haven or hedge. Meanwhile, the movement of Dogecoin prices tended to be influenced by public figures’ actions; (3) public opinion on Twitter and government policy changes regarding COVID-19 and economy had a crucial role in investment decision making; and (4) the COVID-19 variants revealed insignificant results to payment-based system cryptocurrency returns.

This study contributed to verifying the vaccine confidence index effect on payment-based system cryptocurrency returns. Also, we further investigated the uncertainty indicators impacting on cryptocurrency returns during the COVID-19 pandemic. Lastly, we utilized the COVID-19 variants as a cryptocurrency returns’ new determinant.

Entrepreneurial passion is constantly considered a core driver of the entrepreneurial process. In reality, however, many passionate entrepreneurs still fail to persist in their ventures. Whether entrepreneurial passion negatively affects entrepreneurial persistence is not well known. The current study explores how entrepreneurial passion inhibits entrepreneurial persistence based on self-regulation theory. The moderating role of the perceived entrepreneurial institutional environment on the relationship is further investigated.

The study collected data from 200 entrepreneurs using a two-stage questionnaire. In the first stage, demographic information was obtained from the respondents, and their entrepreneurial passion, self-regulatory assessment mode and perceived entrepreneurial institutional environment were measured. Three months later, in the second stage, entrepreneurial persistence was evaluated.

The results show that entrepreneurial passion has a positive effect on self-regulatory assessment mode. Further, self-regulatory assessment mode negatively impacts entrepreneurial persistence and mediates the negative relationship between entrepreneurial passion and persistence. In addition, the greater the perceived level of the entrepreneurial institutional environment is, the weaker the positive association between entrepreneurial passion and self-regulatory assessment mode and the weaker the mediating effect of self-regulatory assessment mode on the relationship between entrepreneurial passion and entrepreneurial persistence and vice versa.

This paper clarifies the unknown negative effects of entrepreneurial passion, contributes to the theoretical relationship between the constructs of entrepreneurial passion and persistence and provides insights for decision-making by entrepreneurs, government and venture capital institutions.

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

This research purpose was to develop a Value-Focused Thinking (VFT)-based framework for implementing an Agile-BIM in public institutions in Brazil. The framework is used for structuring an action plan for implementing the Agile-BIM.

The methodology used to structure the Agile-BIM implementation framework is based on the VFT method, which enables a decision-maker’s strategic, fundamental and means-end objectives for the context analyzed to be more easily identified and better understood. The network developed shapes the decision context, shows possible paths toward achieving the fundamental objectives and guides the institution under study on the implementation process. Based on the networks of two decision-makers and the implementation factors identified, the Agile-BIM implementation framework is proposed.

The study developed an Agile-BIM implementation framework that provides guidance for creating an Agile-BIM implementation plan in a public sector construction project and supports decision-making, in addition to clarifying the decision context for decision-makers and other actors involved. The framework consists of three main dimensions: “Project Stakeholder,” “Technology Infrastructure” and “Standardization and Procedures.” Each dimension comprises several factors that contribute to the Agile-BIM implementation process. The findings show that a structured approach to Agile-BIM implementation can support institutions in achieving a smooth and structured transition to BIM usage, thereby ensuring enhanced performance and compliance with legal requirements.

The proposed framework can support the assessment of organizational needs and serves as a basis for guiding the implementation of Agile-BIM in public institutions. This framework for Agile-BIM implementation can guide other public institutions in formulating their action plans for implementing Agile-BIM. The framework demonstrates potential for being applicable in different contexts and being able to adapt to these. It can be transferred to other emerging and/or developing countries that are seeking to embrace Agile-BIM while considering the requisite adjustments inherent to each organization.

The originality of this study lies in addressing the implementation of BIM in the public sector as a decision problem and using the values of the manager who is in charge in the institution to structure the Agile-BIM implementation, based on the VFT method. Furthermore, it proposes an implementation framework that integrates agile methodologies and BIM, known as Agile-BIM.