Search results

This paper aims to explore the problem of power imbalance within decentralized autonomous organizations (DAOs) and propose potential solutions that could contribute to enhancing the democratic nature of DAOs.

In this paper, the authors apply a qualitative methodology. Using a thematic coding analysis, the authors process data collected from interviews with 11 experts.

Multiple factors contribute to the perceived lack of democracy within DAOs, such as token concentration and effective stakeholder communication. Next, quadratic voting has the potential to enhance democracy within DAOs, but this mechanism must be implemented mindfully. Finally, the results were nuanced when it comes to the effectiveness of liquid democracy in DAOs to enhance voter participation and representation.

To the best of the authors’ knowledge, this paper is one of the first research contributions to propose recommendations to address the power imbalance within DAOs and to contribute to the advancement of decentralized decision-making structures.

The purpose of this study is to provide a holistic view of the emergence of shareholder activism (SA) in India. However, specifically, this study aims at fulfilling the research gap by discussing the policy and legal advancement in the area of SA and investigating the chronological evolution of SA, manifestations of SA, motives of SA, outcome of SAs and impact of SA on the financial performance of the firm.

This study used a mixed methodology (both qualitative and quantitative) to draw inferences, including content analysis, descriptive statistics, independent sample t-test and paired sample t-test. The data has been collected from the annual reports of the sample companies and the Prowess database. Return on assets and return on equity have been used as measures of financial performance while investigating the difference in financial performance between firms subjected to SA and firms not subjected to SA.

The findings of this study suggest that there has been significant growth in the occurrence of SA incidents in India in the past decade, with shareholders prominently manifesting by opposing the proposals at annual general meetings/extraordinary general meetings, mostly involving governance-related demands. The findings from the independent sample t-tests revealed that there has been a significant difference in the financial performance of the sample subjected to SA and firms not subjected to SA. Furthermore, the results of the paired sample t-test provide strong evidence of significant improvement in the financial performance of firms’ post-SA.

The findings of this study have implications for various stakeholders. The findings of this study suggest that SA has been relatively more successful in the Indian context and may encourage minority shareholders to follow active participation through shareholder proposals and votes rather than a passive strategy to trade and exit. For firms, it can provide valuable inferences about the emergence of SA and how it has a positive impact on the financial performance of the firm, which can lead to a change in the perception of investors and promoters who perceive SA as a threat (Gillan and Starks 2000; Hartzell and Starks, 2003). For policymakers, it can act as a tool to investigate whether the regulatory changes have been able to bring the intended transparency, accountability and enhanced shareholder participation. This will encourage policymakers to be more agile, as their efforts are bearing fruit. This will also act as a guide to formulating future policies and regulations.

This study is an effort to provide a holistic view of SA scenarios in a developing economy setting like India, where SA is a very recent phenomenon. Although there are studies in the area of SA, there is a dearth of studies that have investigated the various dimensions of SA in the Indian context in a very systematic and extensive manner, investigating all the different dimensions of SA. Furthermore, this study also intends to investigate the impact of SA, which is normally perceived as a threat to financial performance and provide valuable contrasting evidence.

This study uses a bibliometric approach to analyze the overall status of e-government research by revealing patterns and trends that would help gain a broad understanding of global developments in the field and future directions.

All documents related to e-government published from 2000 to 2019 were extracted from the Scopus and the Digital Government Reference Library databases. Bibexcel, Biblioshiny, and VOSviewer were used to perform the analyses and visualize the science mapping.

The results showed that 21,320 documents related to e-government research were published and cited 263,179 times. The annual growth rate of e-government research has reached 21.50%. The regression analysis showed that the growth rate is expected to increase gradually over the coming years. Despite the significant role that conference papers play in the e-government literature, the impact of articles far exceeds conference papers. The University of Albany (SUNY) has played an important role in e-government research in terms of production and impact. Furthermore, the study revealed some countries that are expected to play a prominent role in e-government research, as well as several topics that may attract more attention soon.

The results presented in this study and the comprehensive picture obtained about the e-government field make it an effective supplement to the expert evaluation. Thus, researchers, research managers, policymakers, institutions, funding agencies, and governments can rely on it.

This study examines the effect of social media marketing on voting intention applying a combination of fuzzy logic methodology and a multidimensional panel data model.

The study adopts a multidimensional panel data method that includes several fixed effects. The dependent variable is a multifaceted construct that measures the participants’ intention to vote. The independent variables are electronic word of mouth (eWOM), customisation (CUS), entertainment (ENT), interaction (INT), trendiness (TRD), candidate’s perceived image (CPI), religious beliefs (RB), gender and age. The grouping variables that signify fixed effects are employment status, level of education, mostly used social media and religion. First, the significance of said fixed effects was tested through an ANOVA process. Then, the main model was estimated, including the significant grouping variables as fixed effects.

Employment status and level of education were significant fixed effects. Also, eWOM, ENT, INT, CPI, RB and gender significantly affected participants’ voting intention.

Being based on a questionnaire that asked participants about how they perceive different aspects of social media, the present study is limited to their perceptions. Therefore, further studies covering the voters’ behaviour in action could be efficient complements to the present study.

The findings could guide the political parties into prioritizing the aspects of social media in forming an effective campaign resulting in being elected.

The findings have the potential to help the public in making better informed decisions when voting. Furthermore, the results of this study indicate applications for social media which are beyond leisure time fillers.

Fuzzy logic and multidimensional panel data estimates are this study’s novelty and originality. Structural equation modelling and crisp linguistic values have been used in previous studies on social media’s effect on voting intent. The former refines the data gathered from a questionnaire, and the latter considers the possibility of including different grouping factors to achieve a more efficient and less biased estimation.

We investigate the joint impacts of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of reviews and attitude toward the product/service reviewed.

We performed three studies to test our research model, presenting participants with scenarios involving product reviews and prior users' helpful and unhelpful votes across experimental settings.

A high helpfulness ratio boosts users’ trust and influences behaviors in both positive and negative reviews. This effect is more pronounced in attribute-based reviews than emotion-based ones. Unlike the ratio effect, helpfulness magnitude significantly impacts only negative attribute-based reviews.

Future research should investigate voting systems in various online contexts, such as Facebook post likes, Twitter microblog thumb-ups and up-votes for article comments on platforms like The New York Times.

Our findings have significant implications for voting system-providers implementing information techniques on third-party review platforms, participatory sites emphasizing user-generated content and online retailers prioritizing product awareness and reputation.

This study addresses an identified need; that is, the helpfulness votes as an additional trust cue and the joint effects of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of customers in reviews and their consequential attitude toward the product/service reviewed.

Histopathology biopsy imaging is currently the gold standard for the diagnosis of breast cancer in clinical practice. Pathologists examine the images at various magnifications to identify the type of tumor because if only one magnification is taken into account, the decision may not be accurate. This study explores the performance of transfer learning and late fusion to construct multi-scale ensembles that fuse different magnification-specific deep learning models for the binary classification of breast tumor slides.

Three pretrained deep learning techniques (DenseNet 201, MobileNet v2 and Inception v3) were used to classify breast tumor images over the four magnification factors of the Breast Cancer Histopathological Image Classification dataset (40×, 100×, 200× and 400×). To fuse the predictions of the models trained on different magnification factors, different aggregators were used, including weighted voting and seven meta-classifiers trained on slide predictions using class labels and the probabilities assigned to each class. The best cluster of the outperforming models was chosen using the Scott–Knott statistical test, and the top models were ranked using the Borda count voting system.

This study recommends the use of transfer learning and late fusion for histopathological breast cancer image classification by constructing multi-magnification ensembles because they perform better than models trained on each magnification separately.

The best multi-scale ensembles outperformed state-of-the-art integrated models and achieved an accuracy mean value of 98.82 per cent, precision of 98.46 per cent, recall of 100 per cent and F1-score of 99.20 per cent.

While the world grappled with the COVID-19 pandemic and its externalities, scientists have recommended that the global community brace against potential future pandemics. The need to build resilient systems has never been this urgent. The world, especially emerging economies, faces acute food insecurity, high food prices, failing health infrastructure and rampant misinformation spread, among others. Since blockchain technology (BCT) has been discussed in the supply chain resilience context, and it offers the potential to develop resilient systems, we aim to outline the potential of BCT to help build resilience against ongoing and future pandemics. Mainly, we focus on BCT for healthcare management, disruption management of food supply chains, human resource management, modern education and certification and governance and administration.

The widespread family businesses play an important role in the national economy of developed countries in Europe and North America, or of developing countries in East Asia. However, family business succession is a worldwide difficult problem. The innovative family business succession practices of Robert Bosch GmbH, the German family company which has a history of 130 years (1886-2016), basically follow the trend of evolving from family businesses to social enterprises after further socialization. However, it has its own innovation and uniqueness which is worthy of reference by Chinese family businesses.