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This research is designed to explore the relationship between social media addiction, student engagement and student retention. Social media addiction is dealt with as an independent variable student engagement acts as a mediating variable and student retention as a dependent variable.

This is a cross-sectional and quantitative research. Primary data are collected from 600 respondents (university students) with the help of a structured questionnaire. Multistage sampling techniques, i.e. simple random sampling and judgment sampling, are used for the selection of respondents.

Results indicate that for direct relationships, social media addiction has a significant positive impact on student engagement and student retention, respectively, while student engagement is partially mediating the relationship between social media addiction with student retention.

In the future, these kinds of research may also be conducted on students of different universities in Pakistan, which are located in other cities of Pakistan besides Lahore. This research provides a practical framework for the higher authorities of the universities of Pakistan and explains how the use of media positively fosters the levels of student retention directly and indirectly through the path of student engagement. It is commonly believed that media addiction is bad but the result of this research indicates that anything is not dangerous but depends upon its use, media addiction itself is not bad but if someone uses this for a good purpose in limitation then it has better outcomes. The result indicates that the media addiction of students has a positive impact on student retention. This means that if someone uses media for a positive purpose then he/she will use it as a supporting tool for success. Longitudinal research on these variables will also help to check the status after a specific interval of time.

The current study will help the practitioners or policymakers (Managers) of higher education institutions by providing practical insights into the positive use of media by students for increasing their knowledge and grades. This research can also help practitioners or policymakers to focus their students on the positive use of social media for fostering the levels of student retention.

To the best of the researcher’s knowledge, no previous study has been done to incorporate social media addiction and student engagement in a single model in the Pakistani cultural context. Similarly, the relationship of variables social media addiction with student engagement is rarely checked empirically because the research of Wang et al. (2011) proposed that social media addiction has a relationship with student engagement so that is why this is the rationale of the research is to check this empirically. Moreover, this study is an initial effort to check the mediating effect of student engagement in the relationship between social media addiction and student retention. This research is also proposing the framework of social media addiction, student engagement and student retention based on the social exchange theory (SET).

The authors investigate whether firm-specific vulnerability to climate change influences foreign exchange hedging, using a novel text-based measure of firm-level climate change exposure generated by state-of-the-art machine-learning algorithms.

The authors' empirical analysis includes firm-fixed effects, random-effects regressions, propensity score matching (PSM), entropy balancing, an instrumental-variable analysis and using an exogenous shock as a quasi-natural experiment.

The authors' findings suggest that greater climate change exposure brings about a significant reduction in exchange rate hedging. Companies more exposed to climate change may invest significant resources to address climate change risk, such that they have fewer resources available for currency risk management. Additionally, firms seriously coping with climate change risk may view exchange rate risk as relatively less important in comparison to the risk posed by climate change. Notably, the authors also find that the negative effect of climate change exposure on currency hedging can be specifically attributed to the regulatory aspect of climate change risk rather than the physical dimension, suggesting that companies view the regulatory dimension of climate change as more critical.

Recent studies have demonstrated that climatic fluctuations represent one of the most recent sources of unpredictability, thereby impacting the economy and financial markets (Barnett et al., 2020; Bolton and Kacperczyk, 2020; Engle et al., 2020). The authors' study advances this field of research by revealing that company-specific exposure to climate change serves as a significant determinant of corporate currency hedging, thus expanding the existing knowledge base.

The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO₂ equivalent (CO₂e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.

To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.

Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO₂e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.

This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.

The authors target the interrelationships between non-fungible tokens (NFTs), decentralized finance (DeFi) and carbon allowances (CA) markets during 2021–2023. The recent shift of crypto and DeFi miners from China (the People's Republic of China, PRC) green hydro energy to dirty fuel energies elsewhere induces investments in carbon offsetting instruments; this is a backdrop to the authors’ investigation.

The quantile vector autoregression (VAR) approach is employed to examine extreme-quantile-connectedness and spillovers among the NFT Index (NFTI), DeFi Pulse Index (DPI), KraneShares Global Carbon Strategy ETF price (KRBN) and the Solactive Carbon Emission Allowances Rolling Futures Total Return Index (SOLCARBT).

At bull markets, DPI is the only consistent net shock transmitter as NFTI transmits innovations only at the most extreme quantile. At bear markets, KRBN and SOLCARBT are net shock transmitters, while NFTI is the only consistent net shock receiver. The receiver-transmitter roles change as a function of the market conditions. The increases in the relative tail dependence correspond to the stress events, which make systemic connectedness augment, turning market-specific idiosyncratic considerations less relevant.

The shift of digital asset miners from the PRC has resulted in excessive fuel energy consumption and aggravated environmental consequences regarding NFTs and DeFi mining. Although there exist numerous studies dedicated to CA trading and its role in carbon print reduction, the direct nexus between NFT, DeFi and CA has never been addressed in the literature. The originality of the authors’ research consists in bridging this void. Results are valuable for portfolio managers in bull and bear markets, as the authors show that connectedness is more intense under such conditions.

Users' knowledge contribution behaviors are critical for online Q&A communities to thrive. Well-organized question threads in online Q&A communities enable users to clearly read existing answers and their evaluations before contributing. Based on the social comparison and peer influence literature, the authors examine peer influence on the informativeness of knowledge contributions in competitive settings. The authors also consider three levels of moderating factors concerning individuals' perception of competitiveness: question level, thread level and contributor level.

The authors collected data from one of the largest online Q&A communities in China. The hypotheses were validated using hierarchical linear models with cross-classified random effects. The generalized propensity score weighting method was employed for the robustness check.

The authors demonstrate the peer influence due to social comparison concerns among knowledge contribution behaviors in the same question thread. If more prior knowledge contributors choose to contribute long answers in the question thread, the subsequent contributions are more informative. This peer influence is stronger for factual questions and questions with higher popularity of answering but weaker in recommendation-type and well-answered questions and for contributors with higher social status.

This research provides a new cue of peer influence on online UGC contributions in competitive settings initiated by social comparison concerns. Additionally, the authors identify three levels of moderating factors (question level, thread level and contributor level) that are specific to online Q&A settings and are related to a contributor's perception of competitiveness, which affect the direct effect of peer influence on knowledge contributions. Rather than focus on motivation and quality evaluation, the authors concentrate on the specific content of online knowledge contributions. Peer influence here is not based on an actual acquaintance or a following relationship but on answering the same question. The authors also illustrate the competitive peer influence in subjective and personalized behaviors in online UGC communities.

The purpose of this study is to examine research on academic libraries and the social web published from July 1, 2019, to June 30, 2023.

The article search and filtering procedures mirrored those of Choi and Harper (2020) and Carlsson (2015), resulting in a total sample size of 93 articles. These articles underwent examination based on the same eight variables (i.e. journal outlet, research theme, publication year, social web type, method, keyword, study participant type and study country) as employed by Choi and Harper (2020) and Carlsson (2015), with the addition of two new variables (i.e. research purpose and the impact of COVID-19).

The research article volume has consistently maintained a stable trend. A notable difference from Choi and Harper (2020) and Carlsson (2015) is the rise of “user perspectives” as the second most prevalent theme. Unlike Choi and Harper (2020), the “survey” method is predominant. Many research purposes, excluding “marketing and promotion,” lack attention. Additionally, there’s a dearth of studies on the impact of COVID-19.

The findings from the study not only offer a snapshot of the current research landscape on academic libraries and their engagement with the social web but also offer insights for future scholarly endeavors.

There is a limited effort in exploring the recent literature regarding the role of the social web in academic libraries. This study serves as a valuable guide for contributing to this dynamic research stream and provides various up-to-date implications.

This historical example of the creation of the arms industry in the Connecticut River Valley in the 1800s provides new insights into the value of government venture capital (GVC) and government demand in creating a new industry. Since current theoretical explanations of the best uses of governmental venture capital are still under development, there is considerable need for further theory development to explain and predict the creation of an industry and especially those industries where failures in private capital supply necessitates governmental involvement in new firm creation. The purpose of this paper is to provide an in depth historical review of how the arms industry evolved spurred by GVC and government created demand.

This study uses abductive inference as the best way to build and test emerging theories and advancing theoretical explanations of the best uses of GVC and governmental demand to achieve socially required outcomes.

By observing this specific historical example in detail, the authors add to the understanding of value creation caused by governmental venture capital funding of existing theory. A major contribution of this paper is to advance theory based on detailed observation.

The relatively limited research literature and theory development on governmental venture capital funding and the critical success factors in startups are enriched by this abductive investigation of the creation of the historically important arms industry and its spillover into creating the specialized machine industry.

Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.

The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.

The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.

First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.

Online health question-and-answer (Q&A) forums have developed a new business model whereby listeners (peer patients) can pay to read health information derived from consultations between askers (focal patients) and answerers (physicians). However, research exploring the mechanism behind peer patients' purchase decisions and the specific nature of the information driving these decisions has remained limited. This study aims to develop a theoretical model for understanding how peer patients make such decisions based on limited information, i.e. the first question displayed in each focal patient-physician interaction record, considering argument quality (interrogative form and information details) and source credibility (patient experience of focal patients), including the contingent role of urgency.

The model was tested by text mining 1,960 consultation records from a popular Chinese online health Q&A forum on the Yilu App. These records involved interactions between focal patients and physicians and were purchased by 447,718 peer patients seeking health-related information until this research.

Patient experience embedded in focal patients' questions plays a significant role in inducing peer patients to purchase previous consultation records featuring exchanges between focal patients and physicians; in particular, increasingly detailed information is associated with a reduced probability of making a purchase. When focal patients demonstrate a high level of urgency, the effect of information details is weakened, while the interrogative form is strengthened.

The originality of this study lies in its exploration of the monetization mechanism forming the trilateral relationship between askers (focal patients), answerers (physicians) and listeners (peer patients) in the business model “paying to view others' answers” in the online health Q&A forum and the moderating role of urgency in explaining the mechanism of how first questions influence peer patients' purchasing behavior.

There are a variety of benefits associated with the use of YouTube for learning purposes, such as YouTube is a free open-access tool students can use to facilitate their learning. This study investigates whether an attitudinal factor (i.e. perceived usefulness) and the factor's antecedents, resource quality factors (i.e. credibility, currency, coverage and relevance), normative factor (i.e. subjective norm) and control factor (i.e. perceived ease of use) all affect college freshmen's behavioral intentions to use YouTube for academic learning purposes.

This research employs the theory of planned behavior (TPB) to explore the attitudinal, normative and control factors associated with college freshmen's behavioral intentions to use YouTube for academic learning. After developing a quantitative survey given to 182 college freshmen in a Southeastern institution in the United States of America, structural equation modeling (SEM) was used to examine the seven hypotheses and the research constructs.

The results indicate that attitudinal factor (i.e. perceived usefulness) and its antecedents, resource quality factors (i.e. currency, coverage and relevance) and normative factor (i.e. subjective norm) have a statistically significant effect on college freshmen's intentions to use YouTube for academic learning purposes.

This study suggests that individual motivations (i.e. perceived usefulness and subjective norm) and resource quality factors (i.e. currency, coverage and relevance) play into college freshmen's decisions to use YouTube for learning purposes, while other research indicates that the system or application itself factors into students' decisions to use technology for learning.

This study suggests that college freshmen are more likely to use YouTube for academic learning purposes when the freshmen hold favorable attitudes about the platform and when the freshmen believe the freshmen's peers are also using YouTube to supplement in-class learning.

This is an initial study that focuses on college freshmen's behavioral intentions to use YouTube for academic learning purposes. This research demonstrates the roles that peers as well as resource quality factors play in students' decisions to use specific technology to enhance the students' learning.