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The current scenario shows increased adoption of off-chain voting applications in decentralized autonomous organizations (DAOs) to avoid complexity and costs for user engagement in their governance. This paper aims to comprehend the trends and patterns within the DAO community with off-chain voting systems and blockchain usage.

This exploratory study uses a two-pronged quantitative approach, combining descriptive statistical analysis and fuzzy-set qualitative comparative analysis. Input data from different DAO proposals and votes were analyzed.

Results indicate that the 179 DAOs analyzed account for 26,538 proposals and 1,268,474 followers of the entire Snapshot base in January 2023, showing high concentration in engagement. The preferred social media communication channels are Twitter and GitHub, showing a decrease of Ethereum as a main chain, with Polygon and Binance Smart Chain already accounting for 22%. Basic voting can lead to greater user involvement in the voting process.

This study complements the traditional governance theory perspective and advances in the emerging literature on DAOs and blockchain with an empirical analysis.

As blockchain technology gains increasing adoption, comprehending trends and patterns within the DAO community becomes pivotal in identifying opportunities and challenges for innovation and improvement.

Findings can facilitate the development of improved governance models and decision-making processes for DAOs, leading to a more robust and sustainable ecosystem.

This study presents a broader IT-based governance foresight via blockchain while providing an understanding of the voting process, technology features and governance mechanisms for social community engagement and decision-making in DAOs.

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

In the presence of coronavirus disease 2019 (COVID-19), due to the social distance restriction, consumers' regular consumption behaviors and patterns have been changing fundamentally. Thereafter, an innovative group buying model has emerged and developed explosively with a specific focus on consumer's location, known as community-based group buying (CGB). The purpose of this paper is to investigate the transfer mechanism of user's trust in dyadic contexts of social and commercial role-playing in the CGB program.

This study adopts an empirical research method, with an online and offline questionnaire survey, a total of 382 responses have been obtained. Then, both descriptive analysis and hierarchical regression analysis are conducted to explore the dual roles of group leader and its corresponding effects on consumers' trust (i.e. emotional trust and behavioral trust) and engagement actions (i.e. purchase and share) in the CGB program.

Results indicate that resident's trust and their perception of group leader's friend role can positively enhance their engagement actions in the CGB programs. Meanwhile, for the purpose of profit maximization, the group leader is more willing to play a friend role in transactions no matter whether the role conflict exists.

Research findings provide some managerial insights for CGB platform on the selection and training of group leaders and the incentive mechanism design.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

Covid-19 pandemic, war, climate emergency and other recent challenges are inflicting tremendous stress to youth. However, death and tragedy are nowadays considered taboo, as there is generally no standardized nor naturalized discussion on the subject, especially with young people. The current multi-crisis scenario is intensifying the need to incorporate an education on tragedy and resilience in our learning systems. In this context, it is necessary to find suitable teaching resources for this educational challenge that are attractive, entertaining and suitable for children and youth. A resource that meets all these requirements are children’s folk songs (CFSs). Apart from the intrinsic educational potential of music, folk songs have a simplicity and musicality that make them an ideal teaching resource. Considering their oral historical transmission, their survival confirms the attraction that this type of composition causes on children. However, to consider CFSs as an adequate resource to carry out an education for death and tragedy, it is necessary to study whether they present a non-negligible proportion of tragic passages and with enough variety of themes. This paper aims to address the study of the presence of explicit tragic content in Spanish CFSs and thus could be considered a cultural resource with transformative educational potential to develop resilience capabilities on the face of tragedy.

An analysis of lyrics of 2,558 Spanish CFSs is presented, using a manual content analysis as well as a computerized content analysis with the aim of identifying the tragic component of these songs and, thereby, assessing their pedagogical potential as a transformative educational resource.

The results obtained show a considerable presence of death and tragedy (19.78%) and a variety of tragedy dimensions. CFSs have been transmitted orally not only as a ludic resource, but also to prepare children for life (and death). The results show the complementarity of both analyses to avoid subjectivity while considering the underlying meanings of the songs.

This task had previously not been approached in an automated manner in the literature, nor there had been a similar study with a sample of this magnitude. The outcomes obtained show the considerable presence of tragedy in Spanish CFSs and emphasize the interest of this currently undervalued didactic resource.

Against the background of the popularity of social media and heritage tourism, this study aims to focus on world heritage sites, proposing a method to examine and compare the digital spatial footprints left by tourists using geographic information systems.

By analyzing user-generated content from social media, this research explores how digital data shapes the destination image of WHS and the spatial relationships between the components of this destination image. Drawing on the cognitive-affective model (CAM), it investigates through an analysis of integrated data with more than 20,000 reviews and 2,000 photos.

The creativity of this research lies in the creation of a comprehensive method that combines text and image analytics with machine learning and GIS to examine spatial relationships within the CAM framework in a visual manner.

The results reveal tourists' perceptions, emotions, and attitudes towards George Town and Malacca in Malaysia, highlighting several key cognitive impressions, such as history, museums, churches, sea, and food, as well as the primary emotions expressed. Their distributions and relationships are also illustrated on maps.

Tourism practitioners, government officials, and residents can gain valuable insights from this study. The proposed methodology provides a valuable reference for future tourism studies and help to achieve a sustainable competitive advantage for other heritage destinations.

Constant or decreasing returns and increasing returns to scale are two kinds of mechanism in economic growth. The goal of supply-side structural reform is to promote the establishment of the mechanism with increasing returns to scale. The paper aims to discuss this issue.

This paper argues that the overall economic structure of the developing economy has been divided into the sector of constant or decreasing returns to scale and the sector of increasing returns to scale due to the dual economic structure. Among them, the supply-side structural reform is mainly to reduce the sector of decreasing returns to scale and increase the sector of increasing returns to scale. Based on the hypothesis of such two-sector economic structure in the supply side of developing economies and on the industrial data, this paper empirically tests the returns to scale of China’s supply structure. The result suggests that so far the sector of constant or decreasing returns to scale dominates the supply structure of China’s economic growth, which results in the state of decreasing returns to scale in China’s overall economy.

Therefore, to realize the long-term sustained growth and transformation of the development pattern of China’s economy, the authors must carry out the supply-side structural reform, vigorously develop the modern industrial sectors characterized by modern knowledge and technology, and promote the development of an innovation-driven economy.

Besides, the authors must accelerate the transformation from traditional industrial sectors to modern industrial sectors, actively promote China’s industrial structure toward rationalization and high gradation, as well as build a modern industrial system so as to facilitate the formation of the mechanism of increasing returns to scale and accelerate the transformation of the driving force of China’s economic growth.

This research aims at analyzing the antecedents of absorptive capacity (ACAP) in the companies incubated in the State of Rio Grande do Norte, Brazil. In this context, 111 incubated companies took part in the research.

The methodology used the confirmatory factor analysis and the multiple linear regression to analyze the relationship of the dependent variables (ACAP) with the dependent variables (interaction with other companies, professionals' knowledge (PK), knowledge use (KU) and knowledge acquisition).

The results highlight that external KU was the construct that most influences the ACAP. Among the dependent variables suggested, only the construct concerning the incubators' PK presented no model significance, which shows that the PK is not an antecedent of ACAP in the incubated companies.

This study is relevant due to pointing out that the incubators may not be providing their professionals with knowledge properly, or that this knowledge is not being accessed by the incubated companies, which allows actions turned to encouraging businesses in this context.

The increased interest among academicians to explore more about tax management behavior is evident in the literature on corporate tax avoidance. This paper aims to illustrate the multiple aspects that influence the tax avoidance behavior of corporations and its impacts through the systematic review method.

This study used “Tax Avoidance” OR “Tax Aggressiveness” OR “Tax Planning” as search strings to extract the relevant literature from the Scopus database. This study is a comprehensive analysis of existing literature on corporate tax avoidance behavior. Further, the keyword network analysis has been used to find out the most explored and dry research areas related to corporate tax avoidance behavior using VOSviewer software.

The study finds that taxation decision is an important managerial decision. Managers adopt tax avoidance tactics to boost postax profits to meet the shareholders’ expectations, particularly of risk-averse shareholders, and sometimes for their benefit also. With this, this study also finds that firms’ characteristics, political connections and corporate social responsibility activities also impact taxation decisions. In addition, the study identifies that tax-avoiding behavior has a contradictory impact on firm value, market growth and corporate transparency disclosure decisions.

The study assists the researchers by providing a brief overview of tax avoidance behavior, for corporates in understanding the implications of tax avoidance, and for policymakers to fix the taxation loopholes and bring necessary tax reforms.

This study adds to the existing literature by providing a thorough overview of theories, determinants and outcomes of corporate tax avoidance behavior.

The main purpose of this research is to examine the impact of institutional quality and sectoral employment on environmental degradation in developing countries. This paper also re-examined the validity of the Environmental Kuznets Curve (EKC) hypothesis and estimated the long run impact of explanatory variables on CO₂ emissions.

In this paper, the balanced panel data for the period 2002–2016 was used based on data availability and applied two-step SYS-GMM estimators.

The results showed that institutional quality such as government effectiveness (GE) and the rule of law (RL) reduce CO₂ emissions and promote environmental quality in developing countries. Interestingly, the authors found new evidence that employment in agriculture and industry has a positive impact on pollution, while employment in the service sector was negatively associated with CO₂ emissions, and the validity of the EKC hypothesis was confirmed. In addition, the research suggests that strong institutional frameworks and their effective implementation are the most important panacea and should be treated as a top priority to counteract environmental degradation and achieve the UN Sustainable Development Goals.

This is the first study to examine the short run and long run effects of institutional quality and sectoral employment on environmental degradation using the balanced panel data for a large sample of developing countries. This paper also used a special technique of Driscoll and Kraay standard error approach to confirm the robustness results and showed the different roles of sectoral employment on environmental quality.