Search Results (19)

Digital transformation (DT) has become an important engine for the development of the digital economy and an important means of reshaping corporate culture, business processes, management models, and so on. Different social communities at different levels have different needs and understandings of digital transformation. Therefore, this paper proposes to explore the communication themes of digital transformation on social media. This study’s main objective is to uncover underlying thematic structures and core ideas from large amounts of textual data in different social media communities to better understand the significance of the communication themes. This paper also aims to reveal the characteristics of diffusion patterns of DT themes by opinion-themed mining. This study uses text mining and social network analysis methods to mine DT themes, theme structure, and the statistical characteristics of hot words across various online communities. The main findings of this study are as follows. The Huawei forum discusses the technological drivers of the digital economy from a micro level. Sohu News explores business operation strategies at a macro level. The Zhihu forum discusses the elements of digital development at the micro level. Moreover, the hot words’ degree centrality and betweenness centrality across various online communities exhibited a power law distribution. In conclusion, this research paper studies and analyzes DT themes of different social media platforms to discover the opinions and attitudes of various social groups in the digital transformation era and deeply interprets social trends and public opinions in order to provide valuable decision-making theoretical support for managers, enterprises, and governments. Full article

Implementing ESG is crucial for China’s modernization journey and corporate sustainability. To deeply understand the current standing of ESG in China, this study leverages online data richness using text mining techniques, specifically Latent Dirichlet Allocation (LDA) and ego network analysis. LDA is utilized to identify prevalent discussion topics on ESG, while ego network analysis is applied to examine the relationships and influences among key stakeholders. The scientific aim of this research is to identify prevalent ESG discussion topics, examine the relationships and influences among stakeholders, and determine core ESG focus areas on Chinese society. The findings highlight popular discussion topics such as ESG investment, the ESG notion, green finance transformation, and ESG rating. These topics underscore China’s growing concern for environmental protection and social responsibility. The core discussion areas focus on sustainable development, company social responsibility, and eco-friendliness, framing harmonized progress across economic, social, and environmental realms. Interestingly, governance discourse is sparse; the reasons are analyzed. Through the analysis of online discussions on China’s ESG, this study aims to enhance policymakers’ and participants’ understanding of the true status of China’s ESG, being of practical significance for policy formulation and appropriate ESG strategies. Full article

The implementation of Enhanced Recovery After Surgery (ERAS) is a challenge for healthcare systems, especially in case of patients undergoing major surgery. Despite a proven significant reduction in postoperative complications and hospital lengths of stay, ERAS protocols are inconsistently used in real-world practice, and barriers have been poorly described in a cohort comprising medical and paramedical professionals. This study aims to assess the proportion of French healthcare providers who practiced ERAS and to identify barriers to its implementation amongst those surveyed. We conducted a prospective cross-sectional study to survey healthcare providers about their practice of ERAS using an online questionnaire. Healthcare providers were contacted through hospital requests, private hospital group requests, professional corporation requests, social networks, and personal contacts. The questionnaire was also designed to explore barriers to ERAS implementation. Identified barriers were allocated by two independent assessors to one of the fourteen domains of the Theoretical Domains Framework (TDF), which is an integrative framework based on behavior change theories that can be used to identify issues relating to evidence on the implementation of best practice in healthcare settings. One hundred and fifty-three French healthcare providers answered the online questionnaire (76% female, median age 35 years (IQR: 29 to 48)). Physiotherapists, nurses, and dieticians were the most represented professions (31.4%, 24.2%, and, 14.4%, respectively). Amongst those surveyed, thirty-one practiced ERAS (20.3%, 95%CI: 13.9 to 26.63). Major barriers to ERAS practice were related to the “Environmental context and resources” domain (57.6%, 95%CI: 49.5–65.4), e.g., lack of professionals, funding, and coordination, and the “Knowledge” domain (52.8%, 95%CI: 44.7–60.8), e.g., ERAS unawareness. ERAS in major surgery is seldom practiced in France due to the unfavorable environment (i.e., logistics issues, and lack of professionals and funding) and a low rate of procedure awareness. Future studies should focus on devising and assessing strategies (e.g., education and training, collaboration, institutional support, the development of healthcare networks, and leveraging telehealth and technology) to overcome these barriers, thereby promoting the wider implementation of ERAS. Full article

This research paper unveils an all-encompassing literature exploration into “nudging” in digital platforms and its profound impact on the user experience. This study delved into various sources spanning academic research papers, corporate reports, books, and online publications, acquired through a thorough four-step approach. The methodology entailed unearthing pertinent sources via diverse academic databases and industry networks, and a diligent review process to estimate their relevance and calibre. Data extraction from each selected source focused on the employed nudge techniques, underlying behavioural principles, and their repercussions on the user experience. The findings were subsequently synthesised to unearth the existing literature’s prevalent themes, disparities, and prospective gaps. The paper underscores the importance of nudging as a potent driver of user actions while safeguarding their autonomy. We employed a comprehensive approach to explore nudging application and influences on digital platforms, including academic database searches, corporate reports, and web blogs. We thoroughly extracted data on platform types, nudging strategies, behavioural theories, and user experience influences and impacts. Our study deliberates on potential future research trajectories, encompassing ethical considerations and personalised nudging methodologies. Ultimately, this study underscores how applying nudge techniques in the architecture of digital platforms can elevate user experiences and confer value upon both users and providers. However, the findings acknowledge the inherent limitations that accompany any literature review and may not encapsulate every facet of the subject matter. Full article

Power lines are critical infrastructure components in power grid systems. Strand breakage is a kind of serious defect of power lines that can directly impact the reliability and safety of power supply. Due to the slender morphology of power lines and the difficulty in acquiring sufficient sample data, strand breakage detection remains a challenging task. Moreover, power grid corporations prefer to detect these defects on-site during power line inspection using unmanned aerial vehicles (UAVs), rather than transmitting all of the inspection data to the central server for offline processing which causes sluggish response and huge communication burden. According to the above challenges and requirements, this paper proposes a novel method for detecting broken strands on power lines in images captured by UAVs. The method features a multi-stage light-weight pipeline that includes power line segmentation, power line local image patch cropping, and patch classification. A power line segmentation network is designed to segment power lines from the background; thus, local image patches can be cropped along the power lines which preserve the detailed features of power lines. Subsequently, the patch classification network recognizes broken strands in the image patches. Both the power line segmentation network and the patch classification network are designed to be light-weight, enabling efficient online processing. Since the power line segmentation network can be trained with normal power line images that are easy to obtain and the compact patch classification network can be trained with relatively few positive samples using a multi-task learning strategy, the proposed method is relatively data efficient. Experimental results show that, trained on limited sample data, the proposed method can achieve an F1-score of 0.8, which is superior to current state-of-the-art object detectors. The average inference speed on an embedded computer is about 11.5 images per second. Therefore, the proposed method offers a promising solution for conducting real-time on-site power line defect detection with computing sources carried by UAVs. Full article

This paper delves into the intricate relationship between religious populism and the legitimization of digital authoritarianism in Turkey. Specifically, it investigates how the ruling party, AKP, has strategically linked Islamist values to state policies as a means of justifying its repressive control over digital technology. Through an examination of internet governance at multiple levels—full network-level governance, sub-network or website-level governance, proxy or corporation-level governance, and network–node or individual-level governance—the study reveals the instrumentalization of religious populism to consolidate support and validate the government’s autocratic agenda. Furthermore, it sheds light on the role of state-controlled religious institutions, traditional media, social media outlets, as well as religious leaders and organizations in shaping public opinion, enabling the government to exert greater control over the dissemination of information. By dissecting the religious populist justification of digital authoritarianism in Turkey, this research provides valuable insights into the complex dynamics at play in the realm of online governance. Full article

Improvements in communication and networking technologies have transformed people’s lives and organizations’ activities. Web 2.0 innovation has provided a variety of hybridized applications and tools that have changed enterprises’ functional and communication processes. People use numerous platforms to broaden their social contacts, select items, execute duties, and learn new things. Context: Crowdsourcing is an internet-enabled problem-solving strategy that utilizes human–computer interaction to leverage the expertise of people to achieve business goals. In crowdsourcing approaches, three main entities work in collaboration to solve various problems. These entities are requestors (job providers), platforms, and online users. Tasks are announced by requestors on crowdsourcing platforms, and online users, after passing initial screening, are allowed to work on these tasks. Crowds participate to achieve various rewards. Motivation: Crowdsourcing is gaining importance as an alternate outsourcing approach in the software engineering industry. Crowdsourcing application development involves complicated tasks that vary considerably from the micro-tasks available on platforms such as Amazon Mechanical Turk. To obtain the tangible opportunities of crowdsourcing in the realm of software development, corporations should first grasp how this technique works, what problems occur, and what factors might influence community involvement and co-creation. Online communities have become more popular recently with the rise in crowdsourcing platforms. These communities concentrate on specific problems and help people with solving and managing these problems. Objectives: We set three main goals to research crowd interaction: (1) find the appropriate characteristics of social crowd utilized for effective software crowdsourcing, (2) highlight the motivation of a crowd for virtual tasks, and (3) evaluate primary participation reasons by assessing various crowds using Fuzzy AHP and TOPSIS method. Conclusion: We developed a decision support system to examine the appropriate reasons of crowd participation in crowdsourcing. Rewards and employments were evaluated as the primary motives of crowds for accomplishing tasks on crowdsourcing platforms, knowledge sharing was evaluated as the third reason, ranking was the fourth, competency was the fifth, socialization was sixth, and source of inspiration was the seventh. Full article

The consolidation of telerehabilitation for the treatment of many diseases over the last decades is a consequence of its cost-effective results and its ability to offer access to rehabilitation in remote areas. Telerehabilitation operates over a distance, so vulnerable patients are never exposed to unnecessary risks. Despite its low cost, the need for a professional to assess therapeutic exercises and proper corporal movements online should also be mentioned. The focus of this paper is on a telerehabilitation system for patients suffering from Parkinson’s disease in remote villages and other less accessible locations. A full-stack is presented using big data frameworks that facilitate communication between the patient and the occupational therapist, the recording of each session, and real-time skeleton identification using artificial intelligence techniques. Big data technologies are used to process the numerous videos that are generated during the course of treating simultaneous patients. Moreover, the skeleton of each patient can be estimated using deep neural networks for automated evaluation of corporal exercises, which is of immense help to the therapists in charge of the treatment programs. Full article

The many success stories of reinforcement learning (RL) and deep learning (DL) techniques have raised interest in their use for detecting patterns and generating constant profits from financial markets. In this paper, we combine deep reinforcement learning (DRL) with a transformer network to develop a decision transformer architecture for online trading. We use data from the Saudi Stock Exchange (Tadawul), one of the largest liquid stock exchanges globally. Specifically, we use the indices of four firms: Saudi Telecom Company, Al-Rajihi Banking and Investment, Saudi Electricity Company, and Saudi Basic Industries Corporation. To ensure the robustness and risk management of the proposed model, we consider seven reward functions: the Sortino ratio, cumulative returns, annual volatility, omega, the Calmar ratio, max drawdown, and normal reward without any risk adjustments. Our proposed DRL-based model provided the highest average increase in the net worth of Saudi Telecom Company, Saudi Electricity Company, Saudi Basic Industries Corporation, and Al-Rajihi Banking and Investment at 21.54%, 18.54%, 17%, and 19.36%, respectively. The Sortino ratio, cumulative returns, and annual volatility were found to be the best-performing reward functions. This work makes significant contributions to trading regarding long-term investment and profit goals. Full article

In the context of the rapid development of new media such as network citizen journalism, it is of great theoretical and practical significance to use the online public opinion to supervise sewage discharge enterprises’ emission governance behaviors and improve the social opinion supervision mechanism. This paper considers the dynamic characteristics of the spread process of public opinion and the game process of social supervision on corporate pollution control; constructs a tripartite evolutionary game model of the local government, sewage discharge enterprises, and the public by coupling the susceptible–exposed–infected–removed (SEIR) model and the evolutionary game model; and discusses the influence laws of public opinion spread on the tripartite evolutionary game. The results show that (1) the public with higher influence or authority has a more significant restraint effect to restrain the pollution control behavior of the local government and pollutant companies by using online public opinion supervision. (2) Increasing the probability of transforming a latent person into a supervisor and the topic derivative rate or reducing the probability of a supervisor’s self-healing can increase the peak value of supervisors, expand the scope of social public opinion, and improve the effectiveness of public opinion supervision. (3) The relatively high authenticity of public opinion supervision makes public opinion supervision a substitute for local government supervision, but it has a relatively strong inhibitory effect on the over-standard pollutant discharge behavior of sewage discharge enterprises. These conclusions can provide a reference for improving the social supervision mechanism of pollution control in the era of network citizen journalism. Full article

A key parameter in the strategy of news organizations remains the exploitation of factors (such as post time and post type) that enhance the engagement level within online communities on social media. The purpose of this paper is to examine the relationship between post time and post type in correlation with audience response in the Twitter digital platform. Specifically, the study aims to ascertain how the two specific variables affect user engagement with its Twitter posts and how they shape the effectiveness of communication on social networks. The analysis includes 7.122 tweets of the Greek National Broadcasting Corporation (ERT) over four months. Moreover, the study analyzes the tone of user comments on the Twitter posts of the specific public media organizations to understand in-depth how the users communicate their views publicly. The collection of comments lasted seven weeks and they numbered 265 in 2639 tweets. Regarding the post time variable, the study came to important findings on user behavior during the 24 h, as the number of Retweets appears to increase in the morning compared to the afternoon. It was also found that as time goes on, the user is interested in leaving his personal opinion. Regarding the correlation of post type with user engagement, it was found that the accompaniment of a tweet with audiovisual material has a tempting effect on users. Full article

Digital technologies have been integrated into all aspects of public life, including politics, law, finance, business, education, science, and society. As a result of the use of digital technologies by various subjects, a transformation has occurred of the economic relations existing in society, including corporate relations. This study analyzes the impact of digitalization on individual institutions of corporate law. The authors investigate the following aspects of the digitalization of corporate law: (1) digital legal personality of the corporation (online registration (e-residency) of corporations and the digital footprint that companies leave in public registers); (2) digital corporate governance; and (3) digital (network or decentralized) autonomous organizations. The purpose of this research is to identify trends and directions of transformation of individual institutions of corporate law in a digital society. The authors conclude that the digitalization of institutions of corporate law will result in: (1) the reinterpretation of certain concepts of corporate law, such as corporation and corporate governance; (2) the improvement of the legal mechanisms of corporate governance following the introduction of AI into the collegial executive bodies of corporations; (3) the digitalization of corporate assets; and (4) the emergence of new subjects of corporate and other relevant relations. Full article

Online community marketing and social media influencer marketing have aroused the interest of many researchers and practitioners around the world. Companies building online content communities to implement community marketing and influencer marketing has become a new corporate strategy, especially in the tourism and hotel industries in which experiential products are sold. However, based on the content community, maintaining the sustainable development of a consumer advice network composed of opinion leaders and consumers is a major challenge. This paper selects the travel content community of Qunar.com as the research object to study the role of opinion leaders in the sustainable development of corporate-led consumer advice networks (CANs). Empirical evidence based on network evolution data from 1356 “Hotel Sleep Testers” across 11 years shows that: (1) the creation and provision of information can obviously increase the probability of the relationship construction and increase the number of relationships, thus facilitating the formation of opinion leadership (OL); (2) active participation in interactions and withhigh-quality information brings greater effects; (3) the network structure variables, such as preferential attachment, structural equivalence, and similarity, can also better predict the probability of a potential relationship; and (4) reciprocity in consumer advice networks has no significant impact on the establishment of network relationships. Full article

The COVID-19 pandemic has brought significant changes in education worldwide throughout 2020. In Ukraine, the preparedness for this process was different. There were various technical problems such as the absence of Internet connection, computers, or educational materials on the network, and most importantly, the unpreparedness of teachers to perform distance learning. From 28 April to 8 May 2020 at the Oles Honchar Dnipro National University (Dnipro, Ukraine), students were surveyed on the quality of distance learning organized during the quarantine period. A total of 1224 students from almost all faculties and centers took part in the survey and answered 19 questions in an online form developed in Office 365 (Microsoft Corporation, Redmond, WA, USA). The survey algorithm is based on the principle of cross-validation. According to the survey, the most important opportunities of distance (digital) learning are as follows: the opportunity to study in a convenient place, in a comfortable and familiar environment—28.57%; the opportunity to combine work with study—16.97%; the development of self-control skills and motivation to self-educate—16.43%; and the technical level of the learning process (use of information technologies)—13.83%. The aspects that negatively affect the organization of full-scale distance learning are as follows: the large volume of tasks—16.80%; the rapid fatigue due to prolonged work in front of a computer—16.35%; the absence of necessary equipment and/or constant (stable) access to the Internet—15.33%. In conclusion, ways to overcome the difficulties of distance learning, both by universities and by the government, are suggested. Full article

Even though many small and medium-sized enterprises (SMEs) realize the importance of the Sustainable Development Goals (SDGs) for their sustainable business development, they face difficulties when individually pursuing this target. This paper aims to provide cluster-based SMEs with a framework to facilitate the uptake of the SDGs through a cluster network model. By focusing on the case study of a furniture production Cluster Management Organization (CMO Habic a network-based approach to sustainability management is analyzed in order to integrate the SDGs framework into SMEs’ everyday language and day-to-day operations. Through a cluster model approach, industry-specific sustainability material issues are tackled jointly and with the aim of applying a common solution to a similar challenge, Lehi-ODS, an online sustainability management tool for SME self-evaluation, has been developed wherein the participating SMEs can gain an overarching knowledge about the UN 2030 Agenda, assess their own alignment with the SDGs and with respect to that of their peers, and prioritize initiatives to correctly deliver them. The main conclusion derived from the paper is that a CMO is deemed to be a valuable driver in identifying common sector-specific challenges of corporate sustainability and in addressing collectively the question of contributing to the SDGs. Full article