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Internet use has a high environmental footprint that is often overlooked by end users. This paper contributes to limiting the negative environmental footprint of Information Technology (IT) use by understanding the relationship between environmental concerns and use of IT amongst users who are aware of the environmental footprint of IT use. Second, the paper argues that taking environmental concerns into account in technology acceptance studies is relevant, even in studies concerning ordinary IT (i.e. IT not commonly classified as “green” technology).

The authors conduct two vignette-based surveys in two different countries: the USA and Belgium. Partial least squares structural equation modeling (PLS-SEM) is used to analyse the effect of environmental concerns on the intention to use the webcam during online meetings and binary logistic regression is used to analyse the relationship between environmental concerns and reported actual use of webcams.

The higher the respondents' environmental concerns, the higher their intention to use internet systems in a more environmentally responsible way, provided the respondents are aware of the environmental footprint of internet system use. Moreover, the higher the respondents’ environmental concerns, the more likely they are to use internet systems in a more environmentally responsible way.

This study is the first to distinguish “Greening of IT Use” from “Greening of IT” and “Greening by IT” and to show that environmental concerns has an impact on the way end users (intend to) use internet systems, provided the users are aware of the environmental footprint of that use.

This article aims to understand users' information needs in the metaverse communities and to analyze the similarities and differences between their information needs and those of users in Internet communities.

This study conducted semi-structured interviews with users in the metaverse communities to gather raw data. Grounded theory research methods were employed to code and analyze the collected interview data, resulting in the extraction of 40 initial concepts, 15 subcategories and 5 main categories. Based on Maslow’s hierarchy of needs theory, this paper constructs the hierarchical model of users' information needs in the metaverse communities. It compares the differences between users' information needs in the metaverse and Internet fields.

The user’s information needs in the metaverse communities are divided into two types: deficiency needs and growth needs. Deficiency needs have two levels. The first level is the demand for basic information resources. The second level is the users demand for information assistance. Growth needs have three levels. The first level is the need for information interactions. The second level is the need for community rules. The ownership information in the community rules can provide proof of user status, assets and so on. The third level is the need for users to contribute and share their own created information content.

This article presents the latest research data from in-depth interviews with users in the metaverse communities. It aims to help builders and managers of metaverse communities understand users' information needs and improve the design of virtual communities.

With the increasing use of Internet and mobile handsets, mobile-based electronic payment apps (MEPAs) are becoming very popular around the world due to having various advantages. The intention of this exploratory study is to investigate the role/impact of selected factors in adopting three MEPAs of China: Wechat, Alipay and UnionPay based on the extended technology acceptance model (ETAM). After conducting a thorough and careful literature review, this study identified and divided seven such factors into three broad categories: (1) technological factors: perceived ease of use (PEU) and perceived usefulness (PU); (2) personal factors: perceived trust (PT), perceived privacy (PP) and perceived risk (PR); and (3) social factors: social influence (SI) and peer influence (PI) that were assumed to affect the intention to adopt MEPAs (IAMEPAs).

1,597 Chinese individuals were selected through purposive sampling technique who regularly used MEPAs at the time of collecting data. For collecting primary data from the selected respondents, a cross-sectional survey instrument was used. The study utilized IBM SPSS 25 for descriptive statistics and a second generation covariance-based structural equation modeling (CB-SEM) technique through AMOS 25 for testing the hypothesized relationships.

From statistical analysis, it was identified that five factors: PEU, PU, PT, SI and PI have significant positive impact on the dependent variable, IAMEPAs while PR and PP have insignificant influence on IAMEPAs.

This is one of the studies ever conducted to discover the factors that can have impact on the adoption of MEPAs using ETAM. It is strongly expected that this exploratory study can motivate the scholars to commence additional investigations regarding this increasingly popular financial technology (Fin-Tech). In addition, it can be anticipated that the MEPA service providers can widen their service effectiveness according to the users’ opinion reflected in this study. Furthermore, policymakers involved with Fin-Tech can also formulate and implement effective policies and guidelines based on the empirical outcomes.

Smartphone apps collect users' personal information, which triggers privacy concerns for app users. Consequently, app users restrict apps from accessing their personal information. This may impact the effectiveness of in-app advertising. However, research has not yet demonstrated what factors impact app users' decisions to use apps with restricted permissions. This study is aimed to bridge this gap.

Using a quantitative research method, the authors collected the data from 384 app users via a structured questionnaire. The data were analysed using AMOS and fuzzy-set qualitative comparative analysis (fsQCA).

The findings suggest privacy concerns and risks have a significant positive effect on app usage with restricted permissions, whilst reputation, trust and perceived benefits have significant negative impact on it. Some app-related factors, such as the number of apps installed and type of apps, also impact app usage with restricted permissions.

Based on the findings, the authors provided several implications for app stores, app developers and app marketers.

This study examines the factors that influence smartphone users' decisions to use apps with restricted permission requests. By doing this, the authors' study contributes to the consumer behaviour literature in the context of smartphone app usage. Also, by explaining the underlying mechanisms through which the principles of communication privacy management theory operate in smartphone app context, the authors' research contributes to the communication privacy management theory.

To understand the mechanisms underlying social media discontinuance behavior, this study explores factors affecting social media discontinuance behavior from the perspective of social cognitive theory (SCT).

Based on SCT, this study puts forward a theoretical model incorporating habit, excessive use and negative emotions to predict social media discontinuance behavior. The proposed research model was empirically tested with 465 responses collected from WeChat users in China via an online survey. WeChat is one of the most popular social media in China. However, WeChat also faces the challenges of reduced or terminated usage among its users. Partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the data.

The research results in this study show that habit exerts a negative effect on social media discontinuance behavior, while exhaustion and regret have positive influences. In addition, habit positively affects excessive use, which further leads to negative emotions of social media exhaustion and regret. Moreover, gender moderates the relationship between habit and social media discontinuance behavior.

This study adds to the literature of information system (IS) use lifecycle by investigating user behavioral changes regarding a transition from habituated to excessive use and further to discontinuance behavior. This study also helps elucidate the complex role of habit by explaining social media discontinuance from the social cognitive view. Furthermore, this study advances the current understanding of gender difference in social media discontinuance in the Chinese context. The study also offers insights to practitioners on how to prevent individuals from discontinuing their use of social media.

In response to growing concerns over the negative consequences of Internet addiction on adolescents’ mental health, coupled with conflicting results in this literature stream, this meta-analysis sought to (1) examine the association between Internet addiction and depressive symptoms in adolescents, (2) examine the moderating role of Internet freedom across countries, and (3) examine the mediating role of excessive daytime sleepiness.

In total, 52 studies were analyzed using robust variance estimation and meta-analytic structural equation modeling.

There was a significant and moderate association between Internet addiction and depressive symptoms. Furthermore, Internet freedom did not explain heterogeneity in this literature stream before and after controlling for study quality and the percentage of female participants. In support of the displacement hypothesis, this study found that Internet addiction contributes to depressive symptoms through excessive daytime sleepiness (proportion mediated = 17.48%). As the evidence suggests, excessive daytime sleepiness displaces a host of activities beneficial for maintaining mental health. The results were subjected to a battery of robustness checks and the conclusions remain unchanged.

The results underscore the negative consequences of Internet addiction in adolescents. Addressing this issue would involve interventions that promote sleep hygiene and greater offline engagement with peers to alleviate depressive symptoms.

This study utilizes robust meta-analytic techniques to provide the most comprehensive examination of the association between Internet addiction and depressive symptoms in adolescents. The implications intersect with the shared interests of social scientists, health practitioners, and policy makers.

Millions of social media users over the last two decades have become dependent on social media that has negatively affected their lives, both physically and mentally. Earlier attempts on social media addiction (SMA) scale development have not been made in India which makes it essential to undertake such a study in this region. One of the objectives of this study was to explore and identify the relevant dimensions of the SMA in the literature. The main study objective was to develop and validate a scale on SMA in India.

The research design applied in this work was both qualitative and quantitative. Based on the literature review, some themes of SMA were recognized that were used to conduct semi-structured interviews with the concerned subjects. The interviews conducted were then transcribed, and using NVivo software application, content analysis was carried out. This helped in the identification of relevant themes that were used for preparing the questionnaire. After that an exploratory study was conducted to explore the factors of SMA. This was followed by a confirmatory analysis on a different sample that validated the instrument.

This work developed and validated a six-factor measure of SMA. The total numbers of items in the final instrument are 22. Salience, Tolerance, Mood Modification, Relapse, Withdrawal and Conflict are the six factors of the final scale.

The current designed instrument can be exceptionally functional for evaluating the occurrence and level of the SMA. This can also serve to assist in the handling and management of such online addictive behavior. A lot of productivity is lost due to the unwarranted time spent on the social media. By better understanding the dimensions of SMA, one can limit one's time on such networks.

This work can provide valuable insight into this domain and help in understanding and treatment of this malaise. It can also help parents and other stakeholders at large to comprehend the danger linked with the excessive social media use and therefore, contribute towards the society. These dimensions can also help counsellors and psychologists to better understand the addiction behavior and accordingly counsel the concerned individual.

Although many instruments have been developed in the past by researchers to measure SMA,still some aspects of the concept remain under-researched. Moreover, most of such research has been confined to the developed world regions.

The increase in mobile telephone penetration has offered new opportunities for technology to improve payment operations all over the world. Little research has examined the issues related to the decision-making (DM) of mobile payment systems usage in the Jordanian context. The purpose of this study is to examine the factors that may have an influence on the adoption of mobile payment systems. This study has empirically tested the expanded unified theory of acceptance and use of technology (UTAUT2) together with awareness (AW), trust (TR), security (SE) and privacy (PR) as independent variables to explain the mobile payment system adoption in Jordan.

In total, 270 employees participated in a field survey questionnaire from the public sector in Amman city, the capital city of Jordan. Data were analyzed through a quantitative approach of partial least squares–structural equation modeling.

The results mainly showed that the determinants of DM to use mobile payment system are price value, social influence, performance expectancy, AW and TR. All of these determinants explained 60.2% of the variation of DM. In total, 72.2% has been explained as the TR to use m-payment system by SE and PR. Furthermore, the results revealed that TR mediates the association between SE as well as PR and the DM to use mobile payment system.

Interestingly, these new variables were found to be important and contribute to the UTAUT2 model. Consequently, the decision-makers in the Central Bank of Jordan should consider all these factors when re-upgrading a Jordan Mobile Payment system in the near future.

Research shows that postsecondary students are largely unaware of the impact of algorithms on their everyday lives. Also, most noncomputer science students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aims to explore subject-matter experts’ insights and perceptions of the knowledge components, coping behaviors and pedagogical considerations to aid faculty in teaching algorithmic literacy to postsecondary students.

Eleven semistructured interviews and one focus group were conducted with scholars and teachers of critical algorithm studies and related fields. A content analysis was manually performed on the transcripts using a mixture of deductive and inductive coding. Data analysis was aided by the coding software program Dedoose (2021) to determine frequency totals for occurrences of a code across all participants along with how many times specific participants mentioned a code. Then, findings were organized around the three themes of knowledge components, coping behaviors and pedagogy.

The findings suggested a set of 10 knowledge components that would contribute to students’ algorithmic literacy along with seven behaviors that students could use to help them better cope with algorithmic systems. A set of five teaching strategies also surfaced to help improve students’ algorithmic literacy.

This study contributes to improved pedagogy surrounding algorithmic literacy and validates existing multi-faceted conceptualizations and measurements of algorithmic literacy.

Promoting the adoption of digital payments by the elderly plays an important role in the development of the digital economy. The purpose of this study is to build an extended theory of planned behavior (TPB) model to predict the elderly's intention to pay for digital services under COVID-19 epidemic constraints.

Based on the extended TPB model, 320 qualified participants were recruited on the network. The structural equation model was tested using the SmartPLS3.3 tool, and the moderation effects were tested through SPSS26 and the Process macro.

The results showed that the three dimensions of TPB theory, the basic elements (perceived value and perceived risk), and the external environment (COVID-19 pandemic) were important factors that influence the elderly users' intention to adopt digital payments. Further research found that motivation factors (personal innovativeness, intergenerational support, and social support) can positively moderate these effects.

The results of the study provide a further explanation for understanding the willingness of elderly people to adopt digital payments during the COVID-19 pandemic and bring inspiration to system developers and social managers to reduce the risk of COVID-19 pandemic and increase the share of digital payments for this category.

This paper used the extended TPB theory to construct a fundamental environmental motivation (FEM) framework for understanding the main influencing factors of elderly users' intention to adopt digital payments during the COVID-19 pandemic.