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Both investors and the stock markets are believed to behave in a perfectly rational manner, where investors focus on utility maximization and are not subjected to cognitive biases or any information processing errors. However, it has been discovered that the sentiment of the social mood has a significant impact on the stock market. This study aims to analyze how did the protest event of Tesla happened in April 2021 have a significant effect on the company's stock performance as well as its competitors, Nio, under the competitive effect.

The research is based on time series data collected from Tesla and Nio by employing 10 days, 15 days and 20 days anticipation and adjustment period for the event study. This study employed a text sentiment analysis to identify the polarity of the sentiment of the protest event using the Microsoft Azure machine learning tool which utilizes MPQA subjective lexicon.

The findings provide further evidence to show that a company-specific negative event has deteriorating effects on its stock performance, while having an opposite effect on its competitors.

The paper argues that negative sentiments through social media word of mouth (SWOM) affect the stock market not just in the short run but potentially in the longer run. Such negative sentiments might create a snowball effect which causes the market to further scrutinize a company's operations and possibly lose confidence in the company.

This study explores how the Tesla's protest event at Shanghai Auto Show 2021 has a significant impact on Tesla's stock performance and prolonged negative impact although Tesla implemented immediate remedial actions. The remedial actions were not accepted positively and induced a wave of negative news which had a more persistent effect.

The purpose of this polyphonic paper is to report on interdisciplinary discussions on the state-of-the-art and future of public sector accounting research (PSAR). The authors hope to enliven the debates of the past and future developments in terms of context, themes, theories, methods and impacts in the field of PSAR by the exchanges they include here.

This polyphonic paper adopts an interdisciplinary approach. It brings into conversation ideas, views and approaches of several scholars on the actual and future developments of PSAR in various contexts, and explores potential implications.

This paper has brought together scholars from a plurality of disciplines, research methods and geographical areas, showing at the same time several points of convergence on important future themes (such as accounting as a mean for public, accounting, hybridity and value pluralism) and enabling conditions (accounting capabilities, profession and digitalisation) for PSA scholarship and practice, and the richness of looking at them from a plurality of perspectives.

Exploring these past and future developments opens up the potential for interesting theoretical insights. A much greater theoretical and practical reconsideration of PSAR will be fostered by the exchanges included here.

In setting out a future research agenda, this paper fosters theoretical and methodological pluralism in the interdisciplinary research community interested in PSAR in various contexts. The discussion perspectives presented in this paper constitute not only a basis for further research in this relevant accounting area on the role, status and developments of PSAR but also creative potential for practitioners to be more reflective on their practices and also intended and united outcomes of such practices.

This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.

In this study a two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n = 16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.

Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.

The volunteer basis of this study meant that the sample was not representative or generalisable.

Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.

This work aims at proposing a novel Internet of Things (IoT)-based and cloud-assisted monitoring architecture for smart manufacturing systems able to evaluate their overall status and detect eventual anomalies occurring into the production. A novel artificial intelligence (AI) based technique, able to identify the specific anomalous event and the related risk classification for possible intervention, is hence proposed.

The proposed solution is a five-layer scalable and modular platform in Industry 5.0 perspective, where the crucial layer is the Cloud Cyber one. This embeds a novel anomaly detection solution, designed by leveraging control charts, autoencoders (AE) long short-term memory (LSTM) and Fuzzy Inference System (FIS). The proper combination of these methods allows, not only detecting the products defects, but also recognizing their causalities.

The proposed architecture, experimentally validated on a manufacturing system involved into the production of a solar thermal high-vacuum flat panel, provides to human operators information about anomalous events, where they occur, and crucial information about their risk levels.

Thanks to the abnormal risk panel; human operators and business managers are able, not only of remotely visualizing the real-time status of each production parameter, but also to properly face with the eventual anomalous events, only when necessary. This is especially relevant in an emergency situation, such as the COVID-19 pandemic.

The monitoring platform is one of the first attempts in leading modern manufacturing systems toward the Industry 5.0 concept. Indeed, it combines human strengths, IoT technology on machines, cloud-based solutions with AI and zero detect manufacturing strategies in a unified framework so to detect causalities in complex dynamic systems by enabling the possibility of products’ waste avoidance.

Information Systems research on emotions in relation to using technology largely holds essentialist assumptions about emotions, focuses on negative emotions and treats technology as a token or as a black box, which hinders an in-depth understanding of distinctions in the emotional experience of using artificial intelligence (AI) technology in context. This research focuses on understanding employees' emotional experiences of using an AI chatbot as a specific type of AI system that learns from how it is used and is conversational, displaying a social presence to users. The research questions how and why employees experience emotions when using an AI chatbot, and how these emotions impact its use.

An interpretive case study approach and an inductive analysis were adopted for this study. Data were collected through interviews, documents review and observation of use.

The study found that employee appraisals of chatbots were influenced by the form and functional design of the AI chatbot technology and its organisational and social context, resulting in a wider repertoire of appraisals and multiple emotions. In addition to positive and negative emotions, users experienced connection emotions. The findings show that the existence of multiple emotions can encourage continued use of an AI chatbot.

This research extends information systems literature on emotions by focusing on the lived experiences of employees in their actual use of an AI chatbot, while considering its characteristics and its organisational and social context. The findings inform the emerging literature on AI.

The purpose of this article is to clarify current and widespread misconceptions about the properties of blockchain technologies and to describe challenges and avenues for correct and trustworthy design and implementation of distributed ledger system (DLS) or Technology (DLT).

The authors contrast the properties of a blockchain with desired, however emergent, properties of a DLS, which is a complex and distributed system. They point out and justify, with facts and analysis, current misconceptions about the blockchain and DLSs. They describe challenges that these systems will need to address and possible solution avenues for achieving trustworthiness.

Many of the statements that have appeared on the internet, news and academic articles, such as immutable ledger and exact copies, may be misleading. These are desired emergent properties of a complex system, not assured properties. It is well-known within the distributed systems and critical software community that it is extremely hard to prove that a complex system correctly and completely implements emergent properties. Further research and development for trustworthy DLS design and implementation is needed, both practical and theoretical.

This is the first known published attempt at describing current misconceptions about blockchain technologies. Further collaborative work, discussions, potential solutions, evaluations, resulting publications and verified reference implementations are needed to ensure DLTs are safe, secure, and trustworthy.

Interdisciplinary teams with members from academia, business and industry, and from disciplines such as business, entrepreneurship, theoretical and practical computer science, cybersecurity, finance, mathematics and statistics, must be formed. Such teams must collaborate with the objective of developing strategies and techniques for ensuring the correctness and security of future DLSs in which our society may become dependent.

The value and originality of this article is twofold: the disproving, through fact collection and systematic analysis, of current misconceptions about the properties of the blockchain and DLSs, and the discussion of challenges to achieving adequate trustworthiness along with the proposal of general avenues for possible solutions.

Cognitive computing is part of AI and cognitive applications consists of cognitive services, which are building blocks of the cognitive systems. These applications mimic the human brain functions, for example, recognize the speaker, sense the tone of the text. On this paper, we present the similarities of these with human cognitive functions. We establish a framework which gathers cognitive functions into nine intentional processes from the substructures of the human brain. The framework, underpins human cognitive functions, and categorizes cognitive computing functions into the functional hierarchy, through which we present the functional similarities between cognitive service and human cognitive functions to illustrate what kind of functions are cognitive in the computing. The results from the comparison of the functional hierarchy of cognitive functions are consistent with cognitive computing literature. Thus, the functional hierarchy allows us to find the type of cognition and reach the comparability between the applications.

The purpose of this conceptual paper is to trigger a transcendental concern toward building the spiritual capital (SC) particularly focused on the highly relevant domain of work. In doing so, this conceptual framework focuses on potential antecedents and outcomes of the SC.

Such an endeavor is premised on the Christian's teaching that advocates the need for gathering spiritual treasures (i.e. capital). Secondly, the foray into Spiritism Doctrine (SD) literature is due to the fact that this doctrine considers the spiritual construct as the cornerstone of its principles and tenets. Thirdly, it also examines the related perceptions and approaches from the fields of positive psychology, positive organizational scholarship, workplace spirituality and psychology of religion.

The model invites the individual to capitalize on salient virtues and remarkable human qualities so as to build a SC, namely: humility, compassion, forgiveness, empathy, positive emotions, connections/relationships and sense of cooperation. Finally, it is envisaged that the attempt to create a SC may lead the individual to a feeling of well-being and more resilience at work.

At last, the implications to develop a SC in the context of work are sizeable. After all, it implies to add more concerns to one's career much beyond those strictly functional or professional ones. Rather, it means to regard the work domain through unusual lens.

By bringing the conceptual framework of SC to the forefront of management, spirituality and religion studies through an interdisciplinary approach showed that it is not an elusive or mythical topic. On the contrary, this analysis revealed that this is a serious and surprisingly neglected issue that deserves further attention in light of the benefits that it can potentially yield.

This study analyzes how tech firms can implement the modern wave of subscription-based business model (SBBM), including value proposition, value creation, value capture and performance. In fact, these elements push tech firms to move from traditional to SBBMs.

To achieve the objectives of this study, we initially construct a theoretical framework for applying SBBM. Subsequently, we employ qualitative research to examine the current implementation of the subscription-based economy within tech firms.

A successful SBBM necessitates capturing value through sustainable revenue transactions and revising aspects of the value proposition, creation and capture. Continuous improvement through business value analysis is imperative. Additionally, an agile operations system is vital to address revenue complexities, enable data collection and enhance value proposition, service innovation, churn rate and customer retention, which are essential for SBBM maintenance.

This study delves into how the subscription-based economy is reshaping the business models of tech firms. Beyond exploring the theoretical foundation of this transformative path, this study offers actionable insights on enhancing the value proposition, creation, capture and business value within subscription-based economy frameworks.

The study examines the impact of digital platforms and supply chain capability on operational performance and tests the mediation effect of supply chain capability. Further, the purpose is to examine the moderating effect of digital culture and sharpen our knowledge of how organizational culture as a contextual factor affects the firm's digitalization.

The data were harvested from 194 Finnish manufacturing companies, and structural equation modeling was used to test the hypotheses.

The findings show that digital platforms positively and significantly affect supply chain capability. Moreover, supply chain capability mediates the relation between digital platforms and operational performance. Further, this study confirms that digital culture is a contextual factor that explains the differences in the effects of digital platforms on firm performance.

This study is one of the first attempts to examine the effect of digital culture in the context of digital platforms, supply chain capabilities, and operational performance.