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With gaining popularity, online communities are increasing. It is leading to the data and information overflow. So, there are some challenges like cyber frauds, cyberbullying, etc. while engaging with online communities. Not only this, anonymity of the participants, stress and racism are also big challenges in online communities' interaction. Online harassers' attack tactics have changed over time. In addition, there are challenges like quality of discussion, inequality in participation of the users, etc. may scale online communities towards incitement and activism. Therefore, this study will try to analyse these challenges for overall benefit of the society.

The underlying fuzzy set theory is employed to handle the fuzziness of users' perceptions since the attributes are expressed in linguistic preferences. Through exhaustive literature review, the authors have identified 15 challenges. These challenges are further categorised as cause and effect by using DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach.

Lack of strategic planning and uninspired discussions between users has emerged as a major challenge in cause category. This study further demonstrates how individual challenge can be managed and developed to navigate the online communities to maintain a healthy environment in society.

Results are based on limited dataset. Therefore, findings cannot be generalised for all online communities.

The research findings offer a suitable direction to policymakers to formulate and design policies, laws and regulations to increase user engagement in the online community. The study is beneficial to firms and researchers in understanding the factors influencing effective management of online communities.

The advancement of enterprise social networks (ESNs) facilitates information sharing but also presents the challenge of managing information boundaries. This study aims to explore the factors that influence the information-control behavior of ESN users when continuously sharing information.

This study specifies the information-control behaviors in the “wall posts” channel and applies communication privacy management (CPM) theory to analyze the effects of the individual-specific factor (disposition to value information), context-specific factors (work-relatedness and information richness) and risk-benefit ratio (public benefit and public risk). Data on actual information-control behaviors extracted from ESN logs are examined using multilevel mixed-effects logistic regression analysis.

The study's findings show the direct effects of the individual-specific factor, context-specific factors and risk-benefit ratio, highlighting interactions between the individual motivation factor and ESN context factors.

This study reshapes the relationship of CPM theory boundary rules in the ESN context, extending information-control research and providing insights into ESNs' information-control practices.

This research aims to examine how decision-makers’ demographic traits affect the integration of foreign workforce into Tirolean (Austria) companies. With continuous world migrations, Tirol experiences a great inflow of foreign workforce. While integrating into the workforce, the foreign workers interact with various decision-makers whose demographic traits (e.g., age, gender, nationality) potentially influence the success of the integration process. To gather data on the integration levels of a foreign workforce, the author conducted a questionnaire. Furthermore, several statistical analyses were run to determine if the relationship between demographic characteristics and integration success exists. The study reveals that demographic characteristics influence decision-makers’ acceptance of expatriates, as well as their recruitment, integration, and training and development outcomes. The empirical results indicate the strength of relationships identified through analyses. The study is limited to geographical, as well as the scope of the sample size, as the data are obtained from Tirol only. In addition, the results from the study serve as a basis for future discussions and research.

The purpose of this paper is to evaluate undergraduate student perceptions about the application of immersive technologies for enhancing the student learning experience. This study assesses the viewpoints of students from varying multidisciplinary backgrounds about whether immersive technologies can enhance their learning experience and increase their level of engagement in the context of higher educational delivery.

The research used a case study methodology adopting a questionnaire-based research mixed methods approach. In total, 83 participants completed the questionnaire. The purpose of the research was to evaluate and interpret students’ perspectives at higher educational level about the use of immersive technologies towards enhancing their learning experience. There was also a focus on remote educational delivery due to the legacy of COVID-19.

The findings suggest that there is still more empirical work to be undertaken regarding the application of immersive technologies in higher education. The study revealed that there are immersive benefits though preference for face-to-face teaching remains popular. The negative connotations associated with immersive technology use in higher education, (e.g. virtual reality), such as cost of equipment and motion sickness, substantiates the themes identified in the academic literature.

The study explores a diversity of immersive technologies and their application in higher education (HE) contexts. Findings indicate that although there are acknowledged pedagogical benefits of immersive technology use in HE prevalent barriers remain that require further empirical research if immersive technology use is to be universally used in the sector.

This study aimed to address the underexplored domain of organisational vulnerability, with a specific focus on understanding how vulnerability is understood in organisations and the underlying pathways leading to vulnerability.

This study utilised a narrative literature review methodology, using Google Scholar as the primary source, to analyse the concepts of organisational vulnerability in the context of disaster risk studies. The review focused on relevant documents published between the years 2000 and 2022.

The analysis highlights the multifaceted nature of organisational vulnerability, which arises from both inherent weaknesses within the organisation and external risks that expose it to potential hazards. The inherent weaknesses are rooted in internal vulnerability pathways such as organisational culture, managerial ignorance, human resources, and communication weaknesses that compromise the organisation’s resilience. The external dimension of vulnerability is found in cascading vulnerability pathways, e.g. critical infrastructure, supply chains, and customer relationships.

As the frequency and severity of disasters continue to increase, organisations of all sizes face heightened vulnerability to unforeseen disruptions and potential destruction. Acknowledging and comprehending organisational vulnerability is a crucial initial step towards enhancing risk management effectiveness, fostering resilience, and promoting sustainable success in an interconnected global environment and an evolving disaster landscape.

The boom in live streaming has intensified competition among streamers for viewers' gifts, which makes it meaningful to study the factors that affect the viewers’ gifting behavior. Given the emotional attachment between streamers and viewers, the authors set out to elucidate a new driver on viewer gifting: expressions of the streamer. This research aims to explore the impact of streamer emotions on the viewer gifting behaviors, including free and paid gifting. The loyalty level of the viewers is also introduced as a moderating factor to investigate the heterogeneous effect of streamer emotions on gifting behavior.

The dataset the authors collected consists of two parts, including 1809.69 h of live streaming videos and 358,002 gift giving records. Combined with deep learning methods and regression analysis, the authors performed empirical tests on the 81,110 valid samples. Several robustness checks were also conducted to ensure the reliability of main results.

The empirical results show that streamer emotions do have effects on viewers' free and paid gifting behavior. The authors’ findings show that positive streamer expressions, such as happiness and surprise, have a positive influence on viewer gifting behavior. However, some negative expressions, like sadness, can also have a positive impact. Moreover, the authors discovered that higher viewer loyalty amplifies the positive effect of streamer emotions and reduces the negative effect.

This research contributes to the study about streamer emotions and viewers' consumption behavior, which extends the application of emotion as social information model (EASI model) in the live streaming setting. The authors carefully divide the gifting behavior into two types: free and paid, and study how these two types are affected by streamer emotions. Besides, these effects are analyzed within viewers of different loyalty levels. This study offers practical emotion management strategies for streamers and live streaming platforms to gain more economic profits.

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

The purpose of this study is to determine what technological strategies were used within each of the phases of the ADDIE framework when developing content for professional training. The study also examined the affordances of those technologies in training.

A PRISMA systematic review methodology (Moher et al., 2015) was utilized to answer the four questions guiding this study. Specifically, the PRISMA extension Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Protocols (PRISMA-P, Moher et al., 2015) was used to direct each stage of the research, from the literature review to the conclusion. In addition, the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA principles; Liberati et al., 2009) are used to guide the article selection process.

The findings reveal that the majority of the studies were in healthcare (36%) and education (24%) and used an online format (65%). There was a wide distribution of ADDIE used with technology across the globe. The coding for the benefits of technology use in the development of the training solution revealed four trends: 1) usability, 2) learning approaches, 3) learner experience and 4) financial.

This systematic review only examined articles published in English, which may bias the findings to a Western understanding of how technology is used within the ADDIE framework. Furthermore, the study examined only peer-review academic articles from scholarly journals and conferences. While this provided a high level of assurance about the quality of the studies, it does not include other reports directly from training providers and other organizations.

These findings can be used as a springboard for training providers, scholars, funders and practitioners, providing rigorous insight into how technology has been used within the ADDIE framework, the types of technology, and the benefits of using technology. This insight can be used when designing future training solutions with a better understanding of how technology can support learning.

This study provides insight into the uses of technology in training. Many of these findings and uses of technology within ADDIE can also transfer to other aspects of society.

This study is unique in that it provides the scholarly community with the first systematic review to examine what technological strategies were used within each of the phases of the ADDIE structure and how these technologies provided benefits to developing a training solution.

The share of fast-moving consumer goods (FMCG) in e-commerce has increased, particularly after COVID-19, alongside the growing volume of e-commerce transactions. The increased number of orders necessitates the optimization of delivery operations. This situation has made using different technologies in last-mile delivery processes necessary. Currently, used electric vehicles (EVs) play a significant role in integrating these technologies into delivery operations. Adapting to new technologies emerges as a critical need for small enterprises to survive in the face of advancing technologies. In this context, the main purpose of this paper is to examine and identify attitudes of small businesses toward EVs’ usage in last-mile delivery for FMCG.

The theoretical frameworks commonly used in studies investigating new technologies, namely the theory of planned behavior (TPB) and technology acceptance model (TAM) have been employed. The analysis of the study was conducted using partial least squares-structural equation modeling (PLS-SEM) and the Smart PLS software package.

When examining the results of the study, a significant and positive relationship was found between compatibility and enjoyment with perceived usefulness. Furthermore, a significant and positive relationship was identified between attitude toward use, perceived behavioral control and perceived usefulness. Ultimately, a strong relationship was found between intention, which is a precursor to active usage and attitude. Based on the obtained data, it can be concluded that EVs can be actively used in last-mile delivery in the future.

In FMCG processes in Türkiye, EVs are limitedly used in last-mile delivery operations. However, there are very few studies on the use of EVs in FMCG. Therefore, it is expected that the current research will contribute to the literature by providing information on the factors that influence the acceptance of EV usage and their implications. The TAM and TPB models were used in the current study.