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Scholarly communications, particularly, questions and answers (Q&A) present on digital scholarly platforms provide a new avenue to gain knowledge. However, several studies have raised a concern about the content anomalies in these Q&A and suggested a proper validation before utilizing them in scholarly applications such as influence analysis and content-based recommendation systems. The content anomalies are referred as disinformation in this research. The purpose of this research is firstly, to assess scholarly communications in order to identify disinformation and secondly, to help scholarly platforms determine the scholars who probably disseminate such disinformation. These scholars are referred as the probable sources of disinformation.

To identify disinformation, the proposed model deduces (1) content redundancy and contextual redundancy in questions (2) contextual nonrelevance in answers with respect to the questions and (3) quality of answers with respect to the expertise of the answering scholars. Then, the model determines the probable sources of disinformation using the statistical analysis.

The model is evaluated on ResearchGate (RG) data. Results suggest that the model efficiently identifies disinformation from scholarly communications and accurately detects the probable sources of disinformation.

Different platforms with communication portals can use this model as a regulatory mechanism to restrict the prorogation of disinformation. Scholarly platforms can use this model to generate an accurate influence assessment mechanism and also relevant recommendations for their scholars.

The existing studies majorly deal with validating the answers using statistical measures. The proposed model focuses on questions as well as answers and performs a contextual analysis using an advanced word embedding technique.

The COVID19 crisis has thrown wide open the debate on Europe’s Economic and Monetary Union’s (EMU) future. Next Generation EU (NGEU) has broken the stalemate over a central fiscal capacity. The open question is whether NGEU is a one-off or a first step. The suspension of the Stability and Growth Pact has given new urgency to the debate on reforming EMU’s fiscal rules.

There is no debate as yet about how these two prospects relate to each other. This paper argues that a permanent fiscal capacity and revised rules should be seen as alternatives.

This study makes two claims: first, a fiscal capacity renders a reformed pact unnecessary and second, that is an optimal solution politically. A fiscal capacity would provide an efficient asymmetric shock absorber and therefore reduce the need for pre-emptive action against negative cross-border externalities. It would also provide an abundant supply of an EU-wide safe asset around which to structure the EU’s financial system, thus rendering unnecessary the backstopping of member states' debts.

This would restore democratic accountability while eliminating moral hazard and enforcement problems.

The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed at containing the pandemic. Isolation through social distancing played a key role in achieving this objective. This research study examines the factors affecting the intention of individuals toward social distancing in India.

A correlation study was conducted on residents from across Indian states (N = 499). Online questionnaires were floated, consisting of health belief model and theory of planned behavior model, with respect to social distancing behavior initially. Finally, structural equation modeling was used to test the hypotheses.

The results show that perceived susceptibility (PS), facilitating conditions (FC) and subjective norms are the major predictors of attitude toward social distancing, with the effect size of 0.277, 0.132 and 0.551, respectively. The result also confirms that the attitude toward social distancing, perceived usefulness of social distancing and subjective norms significantly predict the Intention of individuals to use social distancing with the effect size of 0.355, 0.197 and 0.385, respectively. The nonsignificant association of PS with social distancing intention (IN) (H1b) is rendering the fact that attitude (AT) mediates the relationship between PS and IN; similarly, the nonsignificant association of FC with IN (H5) renders the fact that AT mediates the relationship between FC and IN.

The results of the study are helpful to policymakers to handle operations management of nudges like social distancing.

The research is one of its kind that explores the behavioral aspects of handling social nudges through FC.

The purpose of this paper is to present the investigation on contemporary applications of game design in architectural visualization, urban environmental planning and the results to address the problems of traditional methods specifically in terms of interactivity and visualization. The authors present the prototype that incorporates information modeling and virtual reality (VR) into interactive architectural visualization.

The proposed system supports a virtual walkthrough process that allows users to navigate in an architectural space of their imagination and design. The immersion in the design of living space or environment has been made possible through the inclusion of VR through the use of WebVR technology to deploy the design to be experienced.

This study investigates and establishes a framework that explores the intricacies of 3 imensional (3D) Architectural Visualization in a real-time engine by designing a visual experience with a better level of user interaction and then deploying it through VR.

To the best of the authors’ knowledge, this is one of the few experimental frameworks which perfectly integrates VR for visualization in digital home design environments. The prospective applications of this framework are in several fields of construction innovation, architectural design, 3D modeling, virtual and augmented reality.

In keeping with global developments rendering online shopping as an emerging trend among consumers, the present study extends the unified theory of use and acceptance of technology (UTAUT2) comprising the digital payment mode (DPM) as a new driver of online shopping and with the mediation of attitudes toward technology (ATTs) to gauge a better and deeper understanding of behavioral intention (BI).

This study used a survey instrument with snowball sampling from 600 consumers in northern India. Partial least squares structural equation modeling was used to find the association between drivers using UTUAT2, along with DPM and ATTs. The data were divided into a test group (20%) and validated through a training group (80%).

DPM was shown to be directly associated with BI. The mediation of ATTs was also validated through the model. The predictability of the model was 67.5% for the test group (20%) and 69.6% for the training group (80%). The results also indicated that facilitating conditions is a critical driver of BI.

This study enhances the understanding of the roles that DPM and ATTs play in BI during online shopping, suggesting that Indian managers need to adopt DPM as a support service to make online shopping a worthwhile experience.

This paper aims to help higher education institutions (HEIs) develop a better understanding of student support and services needs, thereby enabling them to allocate limited resources for initiatives that effectively improve student experience.

An assessment framework following the Kano analysis is developed to categorize student service features based on customer satisfaction and need fulfillment. The framework is used at a local university, using 23 service features listed as minimum requirements by the national regulatory body for education. Analysis of the satisfaction survey results and prioritization are based on quality indices derived from a factor of importance and the satisfaction gap. A survey was conducted for two academic years to generate a comparison of results.

Of the list mandated as minimum requirements for HEIs, the study revealed that no features were regarded as “must-be,” eight as performing, 14 as attractive and one as indifferent by the students. As these results were disaggregated per year level, the natural decay of delight as in the Kano theory was exhibited as there were less attractive features for students who have been in the university longest. After a full-year academic cycle, results compared to the baseline figures seemed to reveal of impact of the achievement of performance targets by the units rendering specific activities on client satisfaction.

Further rounds of the study are needed to build up more data sets on the relationship between objective performance and satisfaction level for performing features, mindful that this categorization is also bound to change along the way.

As HEIs in the Philippines journey towards the establishment of their own respective internal quality assurance systems, this study provides a practical approach for institutions to transform a mere list of student services for compliance into a strategic tool to enhance the student experience.

In the context of continuous quality improvement, the study presents how the qualitative Kano model, along with simple quantitative tools in the methodology, can be utilized not only in the planning stage of service design but also in closing the planning, doing, checking and acting (PDCA) cycle and opening the quality improvement spiral.

This paper aims to examine the options available to arbitrators when they suspect money laundering during arbitration proceedings, considering their compatibility with fundamental principles and concepts of arbitration.

Using a doctrinal analysis approach, the paper draws on legal principles, antimoney laundering regulations and relevant literature to explore the topic. It considers relevant international treaties, standards set by the financial action task force on money laundering, cases and arguments from legal analysts and experts.

The paper identifies three options for arbitrators: disregarding suspicions, initiating an investigation or terminating the proceedings. Disregarding suspicions is deemed inappropriate, as it may facilitate the concealment of financial crimes. Initiating an investigation is seen as a preferable option, aligning with the arbitrator’s role and the public interest in nullifying contracts linked to criminal conduct. Terminating the proceedings is not recommended, as it contradicts the principle of natural justice. The paper emphasizes the importance of reasonable grounds for suspicions, notifying the parties, and allowing them to address the concerns.

This paper contributes to the existing literature by comprehensively analyzing the compatibility of these options with arbitration principles and concepts. It underscores the need for clear laws and directives to guide arbitrators in addressing financial crimes within the arbitration process, maintaining a balance between party autonomy and preventing the misuse of arbitration for illicit activities.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

Sustainability has become an integral part of the real estate industry, alongside advancing globalization and demographic development. Due to real estate's influence on greenhouse gas emissions throughout its life cycle, both the regulatory and legal requirements concerning the sustainability of real estate are growing and, as a result of social responsibility, the interest of tenants and investors in sustainable real estate. However, criteria for measuring the ecological sustainability of a real estate investment in the purchase process in order to reduce the risk of including “stranded assets” in the portfolio are missing. This paper aims to address the need to integrate the issue of carbon stranding into existing sustainability rating tools.

Existing tools are examined based on defined criteria to determine whether they are suitable for purchasing a property before suitable tools for purchase are compared. Strengths and weaknesses are identified, which are to be remedied with the scoring tool. Taxonomy regulation is integrated into the existing valuation basis as a legal regulation.

The result is a scoring tool that enables real estate companies to measure and evaluate the ecological sustainability performance of a property during the acquisition process, taking into account the three aspects of sustainability and considering them when determining an appropriate purchase price in line with market conditions. Moreover, the developed tool helps to minimize the risk of acquiring a stranding asset.

The environmental, social and governance (ESG) framework employed in this study does not incorporate governance considerations. While the analysis extensively evaluates the building's environmental and social aspects, it does not extend to examining the governance practices of the companies involved. Thus, the assessment is confined solely to the physical attributes of the property without accounting for broader corporate governance factors.

The developed scoring tool represents a valuable tool for the real estate industry, offering insights into sustainability performance during property acquisitions and providing a structured framework for decision-making. By addressing both certification and taxonomy regulation requirements, the tool contributes to the industry's evolution toward more sustainable and environmentally responsible real estate practices.

In response to the growing importance of sustainability in the real estate industry, this paper introduces a novel scoring tool for evaluating the sustainability of real estate investments during the acquisition process.

The rise of emerging economies in the innovation landscape has often been attributed to the positive spillovers of innovation capabilities from multinational corporations (MNCs). However, it is less certain that their innovative capabilities imported from the home country function effectively in the host country from the outset. This study examines the performance of the innovation capabilities of MNC subsidiaries in emerging economies over time by considering the gradual process of their learning about host countries.

We employed stochastic frontier analysis to measure innovation capabilities, our focal construct. For regression analysis, we applied the Mundlak estimator, a variant of the fixed-effects panel estimator, to a sample comprising subsidiaries of MNCs from technologically advanced nations operating in Korea between 2006 and 2016.

Our results indicate that the innovation capabilities of MNC subsidiaries initially underperform those of local firms but improve over time, eventually surpassing the capabilities of their local counterparts. Furthermore, our findings reveal that institutional distance amplifies the underperformance of the innovation capabilities of MNC subsidiaries.

This study contributes to the literature by extending both theoretical development and empirical measurement of innovation capabilities in cross-national settings. Additionally, it deepens our understanding of whether and how MNC subsidiaries adapt their innovation capabilities to the local market environment.