Electronic Markets最新文献

Industries and energy markets around the world are facing mounting pressure to decarbonize, prompting them to transform processes and supply chains towards sustainability. However, a lack of credible sustainability data proves to be a considerable barrier for emerging markets for sustainable products: Against the background of complex and globalized supply chains, it is necessary to verify the sustainability claim of products in order to demand price premiums for sustainable products in the long run. To enable this, it is necessary that stakeholders in globalized supply chains are willing to share relevant data along the entire supply chain for increasing traceability and reducing information asymmetries. Using the example of international hydrogen supply chains, we study how data can be shared between different stakeholders using Digital Product Passports while addressing stakeholders’ concerns about data privacy and disclosure. In our work, we develop design principles that provide insight into how a Digital Product Passport should be designed to verify the hydrogen’s carbon footprint in a reliable way and to ensure the willingness of stakeholders to share their data. We follow a multi-step approach with a structured literature review followed by expert interviews and qualitative content analysis for a synthesis of design principles. Our research illustrates that a Digital Product Passport must collect data comprehensively and automatically, process it in a decentralized and tamper-proof manner, protect privacy and sovereignty of stakeholders, and ensure interoperability.

Background: Iron deficiency anemia (IDA) and b-thalassemia minor (BTM) are the two most common causes of microcytic anemia, and although these conditions do not share many symptoms, differential diagnosis by blood tests is a time-consuming and expensive process. CBC can be used to diagnose anemia, but without advanced techniques, it cannot differentiate between iron deficiency anemia and BTM. This makes the differential diagnosis of IDA and BTM costly, as it requires advanced techniques to differentiate between the two conditions. This study aims to develop a model to differentiate IDA from BTM using an automated machine-learning method using only CBC data.

Methods: This retrospective study included 396 individuals, consisting of 216 IDAs and 180 BTMs. The work was divided into three parts. The first section focused on the individual effects of hematological parameters on the differentiation of IDA and BTM. The second part discusses traditional methods and discriminant indices used in diagnosis. In the third section, models developed using artificial neural networks (ANN) and decision trees are analysed and compared with the methods used in the first two sections.

Based on a large real-world dataset comprising Instagram posts of popular influencers, this study empirically analyzes the impact of disclosed and undisclosed advertising on consumers’ engagement with (a) the advertisement and (b) future non-advertising posts of the same author. As extant research reports inconsistent effects of ad disclosures based on inferred motives, persuasion knowledge, and source credibility, this study develops a conceptual framework incorporating these theoretical concepts. To identify undisclosed advertisements, we use data from regions with proper disclosure culture to train a model to predict if posts are advertising. Based on the predictions for > 65,000 posts of 239 macro-influencers, we find that advertising posts gather less engagement than non-advertising posts. Regarding immediate ad engagement, we find that disclosed ads gather less engagement than undisclosed ads. Contrastingly, when analyzing future engagement, we identify positive persistent effects of disclosed advertising and negative persistent effects of undisclosed advertising on consumers’ engagement with future posts of the same author. We conclude that source credibility explains the effect of disclosures on future posts, while the Persuasion Knowledge Model can explain the effect of disclosures on the current advertisement. Thus, consumers’ coping strategies triggered by activated persuasion knowledge are mostly limited to the advertisement. Our findings can explain the opposing results of extant research. From a managerial perspective, we find that by not disclosing advertising posts, influencers and marketers increase an ad’s engagement levels at the expense of persistently lowered attitudes. Conversely, in the long run, they may benefit from transparent disclosures.

Technologies of self-sovereign identity (SSI) and Web3 tools that strongly protect individual autonomy, combined with the ethics of Asian altruism, can effectively guide the governance of the emerging cyber civilization. In contrast, governance in Western industrial civilization stresses the pursuit of individual self-interest and struggles to balance the benefits of big tech with the protection of individual dignity and the preservation of the common good. We demonstrate, with reference to a local community in Japan, that SSI is successful in encouraging communal collaboration and well-being while providing individuals with greater control over their personal data. We also show that Web3 tools provide incentives for altruistic behaviors while safeguarding SSI. Integration of SSI and social protection demonstrates the potential for building an information society grounded in altruistic values, honoring individual dignity, and recognizing the government’s role in protecting social welfare. Ultimately, this research unveils how altruistic values can be fostered through SSI and Web3.

In the realm of the digital economy, platform-based Internet companies leverage characteristics such as “cross-side effects” and “emerging technologies” to gain a competitive edge. However, simultaneously, they encounter challenges linked to inadequate risk management and insufficient focus on social responsibility. However, the discussions surrounding these matters have primarily been confined to case studies, lacking a comprehensive understanding of the underlying mechanisms that give rise to social responsibility risks. This research addresses this gap by establishing a database of corporate social responsibility risks for Internet platform companies and employs a qualitative comparative analysis method to dissect these social responsibility risks. The study unveils that Internet platform companies can navigate low social responsibility risks through three distinct pathways: the “resource-experience combining type,” the “long-term shareholder-orientation type,” and the “novel innovative advantage type.” It delves into the questions of what Internet platform companies should do and how they should approach corporate social responsibility in varying contexts. Furthermore, it identifies novel strategies within the domain of platform organizations and the platform economy, thus expanding the conceptual framework of corporate social responsibility driving mechanisms. This research offers valuable guidance for government policy development directed at fostering the sustainable growth of Internet platforms. Additionally, it provides platform companies with insights into optimizing their approaches to manage social responsibility risks in alignment with their unique characteristics. Ultimately, it serves as a robust theoretical guide and practical illustration for addressing these pivotal issues.

This paper recaps the issue of online mis- and disinformation as a societal problem, reviews why government roles in defining mis- and disinformation are constitutionally suspect under First Amendment jurisprudence, and builds on a content-neutral theory of disincentivizing the production of mis- and disinformation first proposed by Marshall Van Alstyne. The purpose of this paper is to develop some key implementation details that would be necessary to resolve if the theory is to be adopted operationally.

The interactions between developers and users are a vital driver of complementary innovation and further facilitate the emergence and evolution of digital innovation ecosystems. However, these interactions are somewhat overlooked in research on digital innovation ecosystems. To increase the understanding of their interrelationship, firstly, we explain the foundation of value co-creation between developers and users by introducing service-dominant logic (S-D logic). Then, we analyze the coordination mechanism of their value co-creation using an evolutionary game approach. There are three key findings obtained: First, the underlying logic behind their value co-creation is mutual benefit, and the coordination mechanism elaborates how they select participation strategies by carefully weighing benefits against costs. Second, their engagement behavior is influenced by each other, and their initial choices also determine the evolution outcome of the behavior under certain circumstance. Third, the involvement of developers and users is impacted by similar benefits and costs, such as additional benefits of adopting the active strategy unilaterally, free-riding benefits, additional costs of positive participation, and benefits of ecosystem synergy. However, factors related to platform owners, the loss caused by punishment due to passive participation and the benefits from being featured due to active participation, only affect developers’ strategy choices directly. Finally, we discuss managerial implications of our findings.

Recent developments in the field of artificial intelligence (AI) have enabled new paradigms of machine processing, shifting from data-driven, discriminative AI tasks toward sophisticated, creative tasks through generative AI. Leveraging deep generative models, generative AI is capable of producing novel and realistic content across a broad spectrum (e.g., texts, images, or programming code) for various domains based on basic user prompts. In this article, we offer a comprehensive overview of the fundamentals of generative AI with its underpinning concepts and prospects. We provide a conceptual introduction to relevant terms and techniques, outline the inherent properties that constitute generative AI, and elaborate on the potentials and challenges. We underline the necessity for researchers and practitioners to comprehend the distinctive characteristics of generative artificial intelligence in order to harness its potential while mitigating its risks and to contribute to a principal understanding.