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As an unhealthy dependence on social media platforms, social media addiction (SMA) has become increasingly commonplace in the digital era. The purpose of this paper is to provide a general overview of SMA research and develop a theoretical model that explains how different types of factors contribute to SMA.

Considering the nascent nature of this research area, this study conducted a systematic review to synthesize the burgeoning literature examining influencing factors of SMA. Based on a comprehensive literature search and screening process, 84 articles were included in the final sample.

Analyses showed that antecedents of SMA can be classified into three conceptual levels: individual, environmental and platform. The authors further proposed a theoretical framework to explain the underlying mechanisms behind the relationships amongst different types of variables.

The contributions of this review are two-fold. First, it used a systematic and rigorous approach to summarize the empirical landscape of SMA research, providing theoretical insights and future research directions in this area. Second, the findings could help social media service providers and health professionals propose relevant intervention strategies to mitigate SMA.

The primary objective of this investigation was to explore how employees’ utilization of social media for work-related purposes impacts their service innovation behavior, both directly and through the intermediary mechanisms of knowledge management and employees’ risk-taking.

In developing its conceptual framework, this study has drawn upon the stimulus-organism-response (SOR) theory. To test its hypotheses, this study has surveyed 241 financial analysts from ten Iranian financial companies and has employed variance-based structural equation modeling (specifically, PLS-SEM) with the assistance of “WarpPLS 8.0 software.”

The findings revealed that employees’ work-related use of social media positively influences their service innovation behavior using knowledge management, encompassing knowledge sharing and acquisition capability as well as employee risk-taking. However, this influence is not directly significant.

To the best of our knowledge, this study marks the first instance in which the effect of work-related use of social media on employee service innovation behavior directly and through the mediating roles of knowledge management and risk-taking has been investigated through the lens of the SOR paradigm, especially in the financial sector.

The transition from fossil fuel-based energy systems to renewable energy sources, commonly referred to as the energy transition, is essential for combating climate change. However, comprehensive studies that thoroughly examine the financial mechanisms involved in this process are lacking. Despite the availability of various financial tools, there is a notable absence of extensive research that synthesizes and categorizes these mechanisms into broad groups.

A systematic literature review is used to explore a comprehensive framework for financial mechanisms related to the energy transition and their application across six stages of the process.

The framework of financial mechanisms for energy transition encompasses these six factors: public financing mechanisms, private financing mechanisms, market-based mechanisms, innovative financing mechanisms, risk mitigation instruments and institutional support and capacity building.

This is the first study that thoroughly reviewed the financial mechanisms involved in the energy transition process.

The purpose of this paper is to shed light on the protection motivation theory’s (PMT) maladaptive coping response to anti-Covid-19 preventive persuasive appeals. PMT is based on coping appraisal that may lead to either an adaptive- or a maladaptive coping response. It has been suggested that the maladaptive coping response is not sufficiently investigated and can be represented by individuals’ resistance to anti-Covid-19 persuasive messages. It has been also supposed that resistance is predicted and modeled through a set of cognitive, affective and individual factors such as information processing style, fear arousal, gender and coping self-efficacy.

An experiment and a survey were conducted online on a random sample of 290 individuals. The sample was divided into two groups, each of which was exposed to an anti-Covid-19 persuasive message.

The findings show that resistance to anti-Covid-19 persuasion is not directly predicted by the individual’s exposure to the message, but channeled through an affective and a cognitive process. It was also reported that resistance is predicted by both the reflective and the nonreflective information processing styles, which are in turn predicted by a high versus a low fear arousal. Fear arousal level was shown to be moderated by gender and coping self-efficacy.

This research brings additional insight to the PMT in so far that it highlights the maladaptive coping response through resistance to persuasion in a pandemic context.

The COVID-19 outbreak has been accompanied by a massive “infodemic”, characterized by an overabundance of information, both accurate and inaccurate, making it hard for people to find trustworthy sources and reliable guidance. This study aims to investigate how the COVID-19 infodemic (i.e. information overload and untrustworthiness) influences consumers’ emotions (i.e. fear, anxiety and hope) by shaping their cognitive appraisals of the pandemic (i.e. perceived risk and uncertainty). Additionally, this study also investigates how individual differences (i.e. COVID-19 involvement and infection experience) impact their emotion formation process.

Data were collected from 815 US consumers aged between 18 and 65 in November 2021 via an online survey. Structural equation modeling and multi-group comparison from AMOS 23 were used to test the proposed relationships.

Information overload increased one’s perceived risk and perceived uncertainty of COVID-19, which, in turn, structured the emotional states of fear, anxiety and hope. Information untrustworthiness had a significant impact on risk perception, which led to an increased feeling of fear. Additionally, individuals’ COVID-19 involvement and their infection experience with the coronavirus were found to moderate the cognitive appraisal process in developing emotions.

This study offers insights into the relationships between the information landscape and cognitive appraisals regarding health crises, specifically the COVID-19 pandemic. Not only enriching emotional well-being literature, it also lends managerial implications for effective communication strategies in global health emergencies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-12-2023-0616

Researchers have devoted considerable attention to ecolabel products and their purchase intention. However, empirical research often presents relatively unpredictable and uneven results. Thus, the relationship between the antecedents and outcome variables among ecolabelling studies, such as purchase intention, remains ambiguous. To address this gap in the literature, this study combines the Theory of Planned Behaviour (TPB) and Stimulus, Organism, Response (SOR) theory within a meta-analytic framework, consolidating existing literature on the purchase intention of eco-labelled products to analyse concrete relationships between antecedents and purchase intention.

We conducted a comprehensive analysis of 37 studies and a total sample size of 16,672 participants. The analysis employed a MASEM technique, and the findings of the analysis offer empirical support for the significance of all the proposed relationships within the provided conceptual framework.

The results revealed that environmental advertising significantly impacts green attitude and later substantially influences consumers' intention to make environmentally conscious purchases. The present study also has examined the potential inclusion of different recommended moderators, such as time period and sample size.

The current study focuses on core variables consistently utilized in previous research. Apart from these, additional variables have also been considered in the ecolabelling literature but have not been included in the scope of this study. Future research endeavours may incorporate additional moderators, such as cultural differences and gender dominance, to further enhance the understanding of the subject matter.

Notably, it stands out as one of the initial meta-analyses on ecolabelling, which also incorporated the examination of several moderators.

The study explores the impact of food influencers on consumer behaviour in the social media context. It assesses the interplay between the number of followers an influencer has and the type of content this influencer communicates to the audience. Doing so, the research contributes to the strategic refinement of influencer marketing practices, especially in the food industry.

The study employed an experimental between-subject design 2 (influencer type: micro vs macro) x 2 (content type: informational vs entertaining). It recruited 197 Prolific participants (45.7% female, Mage = 45.076), testing their perceptions towards the influencer and the endorsed product in the social media post.

There was a significant interaction between influencer type and content type on consumers’ attitudes towards and their willingness to buy the advertised product. Specifically, the notion that “the more followers, the better” may only be applicable when consumers peruse the content for entertainment purposes, whereas while they read it for information purposes, a micro influencer (with hundreds to thousands of followers) may have as much impact on consumer behaviour as a macro influencer (with hundreds of thousands to a million followers).

Our findings offer a nuanced understanding into the conventional wisdom that people often follow crowd behaviour. Using the Heuristic-Systematic Model (HSM), we explicate when the number of followers matters and when the content type prevails.

Nanotechnology (NT) advancements in personal protective textiles (PPT) or personal protective equipment (PPE) have alleviated spread and transmission of this highly contagious viral disease, and enabled enhancement of PPE, thereby fortifying antiviral behavior.

Review of a series of state of the art research papers on the subject matter.

This paper expounds on novel nanotechnological advancements in polymeric textile composites, emerging applications and fight against COVID-19 pandemic.

As a panacea to “public droplet prevention,” textiles have proven to be potentially effective as environmental droplet barriers (EDBs).

PPT in form of healthcare materials including surgical face masks (SFMs), gloves, goggles, respirators, gowns, uniforms, scrub-suits and other apparels play critical role in hindering the spreading of COVID-19 and other “oral-respiratory droplet contamination” both within and outside hospitals.

When used as double-layers, textiles display effectiveness as SFMs or surgical-fabrics, which reduces droplet transmission to <10 cm, within circumference of ∼0.3%.

NT advancements in textiles through nanoparticles, and sensor integration within textile materials have enhanced versatile sensory capabilities, robotics, flame retardancy, self-cleaning, electrical conductivity, flexibility and comfort, thereby availing it for health, medical, sporting, advanced engineering, pharmaceuticals, aerospace, military, automobile, food and agricultural applications, and more. Therefore, this paper expounds on recently emerging trends in nanotechnological influence in textiles for engineering and fight against COVID-19 pandemic.

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

This study aims to investigate the relationship between inventory flexibility, digital transformation, supply chain concentration, and productivity in the context of Chinese manufacturing enterprises.

Empirical analysis was conducted using data from listed Chinese manufacturing firms spanning from 2013 to 2022. The study employs a moderated model to examine how digital transformation influences the connection between inventory flexibility and productivity. Additionally, a moderated moderation model is utilized to explore the role of supply chain concentration in moderating the relationship among inventory flexibility, digital transformation, and productivity.

The study reveals a significant positive correlation between inventory flexibility and productivity, underlining the importance of flexible inventory management. Digital transformation moderates this relationship, with digital transformation enhancing the impact of inventory flexibility on productivity. Supplier and customer concentration also positively moderate this connection, suggesting a complementary relationship with digital transformation.

These findings offer valuable insights for managers and policymakers, emphasizing the need for a flexible approach to inventory management that considers the evolving digital landscape and supply chain dynamics.

This study contributes to the literature by providing empirical evidence of the nuanced relationship between inventory flexibility, digital transformation, supply chain concentration, and productivity in Chinese manufacturing enterprises. It underscores the importance of integrating digital transformation and supply chain concentration initiatives with flexible inventory management to optimize productivity in the business landscape.