Search results

Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental elements, gratifications and user pre-existing attitudes in VGS, this paper presents the development of an extended model of uses and gratification theory (EUGT) for predicting users' behavior in novel technological context.

The proposed model was empirically tested in VGS context due to its popularity, interactivity and relevance. Data collected from 308 VGS users and structural equation modeling (SEM) was employed to assess the hypotheses. Multi-model comparison technique was used to assess the explanatory power of EUGT.

The findings confirmed three significant types elements in determining VGS viewers' engagement, including gratifications (e.g. involvement), environmental cues (e.g. medium appeal) and user predispositions (e.g. pre-existing attitudes). The results revealed that emerging technologies provide potential opportunities for new motives and gratifications, and highlighted the significant of pre-existing attitudes as a mediator in the gratification-uses link.

This study is one of its kind in tackling the criticism on UGT of considering media users too rational or active. The study achieved this objective by considering environmental impacts on user behavior which is largely ignored in recent UGT studies. Also, by incorporating users pre-existing attitudes into UGT framework, this study conceptualized and empirically verified the higher explanatory power of EUGT through a novel multi-modal approach in VGS. Compared to other rival models, EUGS provides a more robust explanation of users' behavior. The findings contribute to the literature of UGT, VGS and users' engagement.

This article analyzes the impact of monetary policy on income inequality across 16 advanced economies. The author investigates three key points: (1) the relationship between domestic monetary policy and domestic income inequality, (2) the spillover effect of USA monetary policy (including quantitative easing) on international inequality and (3) the quantitative influence of the monetary policies of both the USA and the Eurozone on the formation of domestic income inequalities.

The author employed the Global Vector Autoregressive (GVAR) model, which uses Vector Autoregressive with Exogenous Variables (VARXs) models of each economy to build an integrated system that enables us to evaluate individual responses to global shocks.

The author's analysis reveals that (1) contractionary monetary policy exacerbates domestic inequality and (2) USA monetary policy, including quantitative easing, affects international inequality. Furthermore, the author's variance decomposition analysis highlights that USA monetary policy is especially influential on income inequality in Norway and Sweden. Additionally, the cointegrating analysis confirms that monetary policy's impact on inequality persists in the long term.

Most of the studies focused on investigating domestic economies as closed economies. However, the author's approach differs in that the author uses the GVAR, which treats all economies as open. This allows us to incorporate the world economy into the domestic dynamics and connect the economies using bilateral trade. Another advantage of the GVAR is that it captures spillover effects by modeling each economy and constructing the international economy.

Previous studies have shown that the application of information technology (IT) can help break through the innovation boundaries of firms and has undoubtedly become a key enabler of collaborative innovation. These studies, however, are mainly based on theoretical analysis and case studies, and little is empirically known about the relationship between IT investments and collaborative innovation. Therefore, the purpose of this study is to empirically explore how firms' IT investments affect the firms' collaborative innovation performance. The authors also examine the moderating roles of the top management team's (TMT's) educational background and absorptive capacity in this relationship.

The authors collected data on 2,097 listed Chinese manufacturing companies and used the ordinary least squares (OLS) method to perform regression analysis. In addition, the authors conducted robustness tests using the propensity score matching (PSM) method and the instrumental variable method.

The results show that the relationship between IT investments and collaborative innovation is inverted, U-shaped and curvilinear. In addition, the TMT's educational background and absorptive capacity positively moderate the inverted U-shaped relationship between IT investments and collaborative innovation.

The study's findings on the relationship between IT investments and collaborative innovation differ from previous mainstream findings that recognized a positive linear relationship. The authors' findings deepen the understanding of the dual role of IT investments. Moreover, this research helps expand the contingency perspective in IT investments and collaborative innovation research.

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

This study identifies factors affecting brand building for academic libraries affiliated with the Ministry of Science, Research and Technology (MSRT) in Iran.

This research applied the grounded theory method based on the three open, axial and selective coding steps (Strauss and Corbin, 1998). The research tool was interviews conducted with 20 experts in librarianship, marketing and branding.

Library building architecture, library information resources and services, librarians' branding, marketing activities and library management are the causal conditions affecting brand building. The national economic situation, the digital publishing situation in the country and different characteristics of the new library community are the intervening conditions affecting brand building. The role of other libraries in society in the scientific education of the new generation provides contextual conditions for brand building. The higher education system and the library parent organization play a part in the operative actions/interactions for brand building. The consequences of brand building are brand image development, brand excellence and brand behavioral loyalty for libraries. Library brand identity is also a core category in brand building.

Facing steep challenges by emergent services, academic libraries are ill-prepared to meet the needs of the new information society solely with traditional services and functions. Academic libraries are required to rebrand themselves to be more successful at delivering a strong performance within a changing information environment by enhancing their brand image and establishing a more effective relationship with users.

With the increased demand for the application of technology in property activities, there is a growing need for property professionals adept in using digital technology. Hence, it is important to assess the competence of academia in equipping property professionals with digital technology skills. This study, therefore, assesses property academics in Australian universities to identify their level of knowledge and use of digital technology applicable to the property industry.

Online questionnaire surveys were administered to 22 out of 110 property academics contacted through the Australia Property Institute (API) database to achieve this aim. The collected data were analysed using mean score ranking and ANOVA.

The study found that apart from databases and analytics platforms such as Corelogic RP data, price finder and industry-based software such as the Microsoft Office suite and ARGUS software, the academics were not knowledgeable in most identified and sampled proptech tools. Similarly, most proptech tools were not used or taught to the students. It was also found that early career academics (below five years in academia) were the most knowledgeable group about the proptech tools.

Relying on the API database to contact property academics potentially excludes the position of property academics who may not be affiliated or have contacts with API, hence, the findings of this study should be generalised with caution.

The study bears huge implications for the property education sector and industry in Australia; a low knowledge and use of nascent tools such as artificial intelligence, machine learning, blockchain, drones, fintech, which have received intense interest, reveals some level of skill gap of students who pass through that system and may need to be upskilled by employers to meet the current day demand.

In response to the clamour for technology-inclined property professionals, this paper presents itself as the first to assess the knowledge levels and application of digital technology by property academics.

The purpose of this study is to provide information that reflects the true state of affairs and to develop a conceptual model that examines the moderating effect of uncertainty on relative brand trust–love.

Extant empirical studies, conceptual literature and related theories were identified and integrated to develop the conceptual model.

Findings of the study suggest that relative brand trust–love arises because of different components of uncertainty. Relative brand trust–love exhibited by the customer is moderated by uncertainty at the individual level, brand level and technology level. These uncertainties represent the situation that considers if relative brand trust–love can be enhanced. A few propositions have been suggested for such situations to enhance relative brand trust–love.

This paper proposes a conceptual model and also makes research propositions that need to be validated and confirmed empirically. It adds value to theoretical advancements in strengthening the customer–brand relationship. Furthermore, results suggest that relative brand trust–love can be improved over time if these components can be supported by increasing information at different levels. The conclusions will be informative to practitioners and brand managers in strengthening a brand into the market more effectively. Moreover, it can transform the brand into a global brand and help build sustainable long-term relationships. Findings can be useful and interesting information for the researchers who are interested in finding strategic ways for effective decision-making related to brand trust and brand love.

The conceptual model, and the propositions related to different levels of uncertainty, and its effect on relative brand trust–love, is a new approach in enhancing relative brand trust–love and hence helpful in strengthening the quality of customer–brand relationships.

It has been argued in the literature that structural changes in the financial markets, such as integration, have the potential to cause herding behavior or correlated behavioral patterns in traders. The purpose of this study is to investigate whether there is any financial herding behavior in the Latin American Integrated Market (MILA), a transnational stock market composed of Chile, Peru, Colombia and Mexico stock exchanges and whether there is any ARCH or GARCH effect in the herding behavior models.

This study uses the modified return dispersion approach on daily index return data. The sample period is from January 03, 2002 to May 07, 2019. The data are obtained from the MILA database. To count time-varying volatilities in herding models, the authors run ARCH family regression with GARCH (1,1) settings. Hwang and Salmon (2004) model is used as a robustness test.

The authors found strong herding behavior under the general market conditions and moderate and partial herding behavior under some specified markets circumstances, such as bull and bear markets and high-low volatility states. Moreover, the pre-MILA period exhibits more herding behavior than the post-MILA period. The empirical results show that most of the ARCH and GARCH effects are statistically significant, implying that the past information of stock returns and market volatility significantly affect the volatility of following periods, which can also explain the formation of herding tendency among investors. Finally, the results of the robustness tests (Hwang and Salmon, 2004) confirm herding in all periods, except full sample period for Mexico and post-MILA period for Mexico and Colombia.

This study investigates the herding behavior in the MILA market in terms of market return, volatility and timing. A limitation of the paper is that the authors have not included other factors on the formation of herding behavior, such as macroeconomic factors, effects of regional or international markets and policy influences. The authors will explore the issue in the extension of the paper.

As MILA is the first virtual integration of stock exchanges without merging, the study provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are useful for academics, investors and policymakers in their investment and decision makings.

The paper provides useful findings and draws good inferences of herding behavior in the MILA market in terms of market return, volatility and timing which are not only useful in practical implications, but also in social implications.

This study contributes to the herding literature by examining four different hypotheses in respect of the unique case of transnational stock exchange without fusions or corporate mergers, where each market maintains its independence and regulatory autonomy. The authors also contribute to the literature by including both ARCH and GARCH effects in the herding behavioral models along the Hwang and Salmon (2004) approach.

The construction industry is widely recognized as one of the most hazardous sectors in the world. Despite extensive research on safety management, a critical issue remains that insufficient attention is devoted to safety practices in rural areas. Notably, accidents frequently occur during the construction of rural self-built houses (RSH) in China. Safety management tends to be overlooked due to the perceived simplicity of the construction process. Furthermore, it is essential to acknowledge that China currently lacks comprehensive laws and regulations governing safety management in RSH construction. This paper aims to analyze the behavior of key stakeholders (including households, workmen, rural village committee and the government) and propose recommendations to mitigate safety risks associated with RSH construction.

This paper applies evolutionary game theory to analyze the symbiotic evolution among households, workmen and rural village committee, in situations with or without government participation. Additionally, numerical simulation is utilized to examine the outcomes of various strategies implemented by the government.

Without government participation, households, workmen, and rural village committee tend to prioritize maximizing apparent benefits, often overlooking the potential safety risks. Numerical simulations reveal that while government involvement can guide these parties towards safer decisions, achieving the desired outcomes necessitates the adoption of reasonable and effective strategies. Thus, the government needs to offer targeted subsidies to these stakeholders.

Considering that during the construction phase, stakeholders are the main administrators accountable for safety management. However, there exists insufficient research examining the impact of stakeholder behavior on RSH construction safety. This study aims to analyze the behavior of stakeholders about how to reduce the safety risks in building RSH. Thus, the authors intend to contribute to knowledge in this area by establishing evolutionary game model. Firstly, this study carried out a theoretical by using tripartite evolutionary game to reveal the reasons for the high safety risk during building RSH. Practically, this research points out the important role of households, workmen and rural village committee in improving safety management in rural areas. Besides, some suggestions are proposed to the government about how to reduce construction safety risks in rural areas.

Construction workers’ safety compliance is attracting considerable critical attention as it plays a decisive role in improving safety on construction sites. This study applied the concept of differentiating safety compliance into deep compliance (DC) and surface compliance (SC) and relied on trait activation theory to investigate the effects of situational awareness (SA) and emotional intelligence (EI) on safety compliance.

Cross-sectional survey data were collected from 239 construction workers in Australia, and these responses were statistically analyzed using the partial least squares structural equation modeling (PLS-SEM) to validate the proposed model.

Results revealed that both EI and SA positively impacted DC and negatively impacted SC. Moreover, SA partially mediated the link between EI and two types of safety compliance (DC and SC). The outcomes showed that construction workers’ ability in regulating their emotions could influence their perception of environmental cues and the effectiveness of safety compliance behavior.

This study sheds light on investigating the antecedents of DC and SC from the perspective of trait activation theory. The findings also have practical implications, stating that construction site managers or safety professionals should consider providing training on construction workers’ EI and SA to enhance their willingness to expend conscious efforts in complying with safety rules and procedures, which can lead to improved safety outcomes.