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This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years.

Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America.

Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors.

This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.

The study aims to investigate the persistence of seasonal anomalies during religious holidays in emerging markets.

The authors select the Bombay Stock Exchange and National Stock Exchange stock returns from January 1990 to December 2022. The GARCH family models were adopted to examine the mean-variance returns associated with symmetric and asymmetric effects. The ARIMAX model is used to investigate the exogenous order during the pre-mandated and post-mandated trading holidays.

The results show that the persistence of returns and volatility during religious holidays significantly when subjected to specific religious holidays. The authors also found that volatility during religious festivals dipped during the pre-holiday and gradually increased after the events. The findings suggest that religious holiday anomalies exhibit a trivial significant effect on stock market returns and this effect is waning.

The findings provide investors and market regulators with a better understanding of market anomalies related to religious practices. During these periods, investors may experience substantial fluctuations in their portfolios, potentially leading to significant losses or payoffs. Investors can sustain substantial losses or payoffs and market manipulation by adjusting their strategies around religious holidays to account for potential volatility, albeit temporarily.

This study contributes to behavioural finance literature that suggests that beliefs and cultural aspects determine a country’s stock market inefficiency. To the best of the authors’ knowledge, no previous study has comprehensively examined threshold religious holidays across diverse religions in Indian market using long-memory data.

This paper examines the impact of a blockchain platform on the role and importance of trust in established buyer-supplier relationships.

A literature review provides insight into trust development in supply chains. Research uses a case study of two wine supply chains: the producers, importers, logistics companies and UK Government agencies. Semi-structured interviews determine how trust and trustworthiness develop in buyer-supplier relationships and the impact of a blockchain-based technology proof of concept on supply chain trust.

A blockchain-based platform introduces common trusted data, reducing data duplication and improving supply chain visibility. The platform supports trust building between parties but does not replace the requirements for organisations to establish a position of trust. Contrary to literature claims for blockchain trustless disintermediation, new intermediaries are introduced who need to be trusted.

The case study presents challenges specific to UK customs borders, and research needs to be repeated in different contexts to establish if findings are generalisable.

A blockchain-based platform can improve supply chain efficiency and trust development but does not remove the need for trust and trust-building processes. Blockchain platform providers need to build a position of trust with all participants.

Case study research shows how blockchain facilitates but does not remove trust, trustworthiness and trust relationships in established supply chains. The reduction in information asymmetry and improved supply chain visibility provided by blockchain does not change the importance of trust in established buyer-supplier relationships or the trust-based policy of the UK Government at the customs border.

The extraction of natural resources has long been part of economic development in small islands. The damage to environment and health is extensive, even rendering once productive islands virtually uninhabitable. Rather than providing long-term benefits to the population or to the environment, the culture of “extractivism” – a nonreciprocal approach where resources are removed and used with little care or regard to consequences – has instead left many in far more fragile circumstances, increasingly dependent on external income. The purpose of this paper is to show how continued extractivism in small islands is contributing to global climate change and increasing climate risks to the local communities.

Through a series of case studies, this paper examines the history of extractivism in small islands in Oceania, its contribution to environmental degradation locally and its impacts on health.

It examines how extractivism continues today, with local impacts on environment, health and wellbeing and its much more far-reaching consequences for global climate change and human health. At the same time, these island countries have heightened sensitivity to climate change due to their isolation, poverty and already variable climate, whereas the damage to natural resources, the disruption, economic dependence and adverse health impacts caused by extractivism impart reduced resilience to the new climate hazards in those communities.

This paper proposes alternatives to resource extractivism with options for climate compatible development in small islands that are health-promoting and build community resilience in the face of increasing threats from climate change.

Extractivism is a new concept that has not previously been applied to understanding health implications of resource exploitation thorough the conduit of climate change. Small-island countries are simultaneously exposed to widespread extractivism, including of materials contributing to global climate change, and are among the most vulnerable to the hazards that climate change brings.

Social media platforms are highly visible platforms, so politicians try to maximize their benefits from their use, especially during election campaigns. On the other side, people express their views and sentiments toward politicians and political issues on social media, thus enabling them to observe their online political behavior. Therefore, this study aims to investigate user reactions on social media during the 2016 US presidential campaign to decide which candidate invoked stronger emotions on social media.

For testing the proposed hypotheses regarding emotional reactions to social media content during the 2016 presidential campaign, regression analysis was used to analyze a data set that consists of Trump’s 996 posts and Clinton’s 1,253 posts on Facebook. The proposed regression models are based on viral (likes, shares, comments) and emotional Facebook reactions (Angry, Haha, Sad, Surprise, Wow) as well as Russell’s valence, arousal, dominance (VAD) circumplex model for valence, arousal and dominance.

The results of regression analysis indicate how Facebook users felt about both presidential candidates. For Clinton’s page, both positive and negative content are equally liked, while Trump’s followers prefer funny and positive emotions. For both candidates, positive and negative content influences the number of comments. Trump’s followers mostly share positive content and the content that makes them angry, while Clinton’s followers share any content that does not make them angry. Based on VAD analysis, less dominant content, with high arousal and more positive emotions, is more liked on Trump’s page, where valence is a significant predictor for commenting and sharing. More positive content is more liked on Clinton’s page, where both positive and negative emotions with low arousal are correlated to commenting and sharing of posts.

Building on an empirical data set from Facebook, this study shows how differently the presidential candidates communicated on social media during the 2016 election campaign. According to the findings, Trump used a hard campaign strategy, while Clinton used a soft strategy.

In response, the purpose of this paper is to provide theoretical frameworks about the organizational uncertainty behind what and when to adopt blockchain technology and their implications on transaction costs. The immature nature and the absence of standards in blockchain technology lead to uncertainty in government organizations concerning the adoption (“what to adopt”) and the identification of the right time (“when to start”).

Using transaction cost theory and path dependency theory, this paper proposes two frameworks: to assess transaction cost risks and opportunities costs; and to depict four different types of transaction costs outcomes regarding blockchain adoption.

This paper identifies various theoretical concepts that influence blockchain adoption and combine the two critical constructs of “bounded rationality” and the “lock-in effect” to categorize the multiple transaction costs outcomes for blockchain adoption.

Although existing research in blockchain highlights mainly the potential benefits of blockchain applications, only a little attention has been given to frameworks that categorize potential transaction costs outcomes under uncertainty, in particular from organizational theorists.

Both frameworks advance the understanding of the decision-making behind blockchain adoption and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the uncertainty regarding transactions costs stemming from blockchain technology.

This study investigates the relationship between the Chief Executive Officer's (CEO) overconfidence and financial reporting complexity in Iran, a context characterized by weak corporate governance and heightened managerial discretion.

The sample consists of 1,445 firm-year observations from 2010 to 2021. CEO overconfidence (CEOOC) is evaluated using an investment-based index, specifically capital expenditures. Financial reporting complexity (Complexity) is measured through textual features, particularly three readability measures (Fog, SMOG and ARI) extracted from annual financial statements. The ordinary least squares (OLS) regression is employed to test the research hypothesis.

Results suggest that CEOOC is positively related to Complexity, leading to reduced readability. Additionally, robustness analyses demonstrate that the relationship between CEOOC and Complexity is more distinct and significant for firms with lower profitability than those with higher profitability. This implies that overconfident CEOs in underperforming firms tend to increase complexity. Also, firms with better financial performance present a more positive tone in their annual financial statements, reflecting their superior performance. The findings remain robust to alternative measures of CEOOC and Complexity and are consistent after accounting for endogeneity issues using firm fixed-effects, propensity score matching (PSM), entropy balancing approach and instrumental variables method.

This study adds to the literature by delving into the effect of CEOs' overconfidence on financial reporting complexity, a facet not thoroughly investigated in prior studies. The paper pioneers the use of textual analysis techniques on Persian texts, marking a unique approach in financial reporting and a first for the Persian language. However, due to the inherent challenges of text mining and feature extraction, the results should be approached with caution.

The insights from this study can guide investors in understanding the potential repercussions of CEOOC on financial reporting complexity. This will assist them in making informed investment decisions and monitoring the financial reporting practices of their invested companies. Policymakers and regulators can also reference this research when formulating policies to enhance financial reporting quality and ensure capital market transparency. The innovative application of textual analysis in this study might spur further research in other languages and contexts.

This research stands as the inaugural study to explore the relationship between CEOs' overconfidence and financial reporting complexity in both developed and developing capital markets. It thereby broadens the extant literature to include diverse capital market environments.

Surprisingly little is known of the various methods of security analysis used by financial analysts with industry-specific knowledge. Financial analysts’ industry knowledge is a favored and appreciated attribute by fund managers and institutional investors. Understanding analysts’ use of industry-specific valuation models, which are the main value drivers within different industries, will enhance our understanding of important aspects of value creation in these industries. This paper contributes to the broader understanding of how financial analysts in various industries approach valuation, offering insights that can be beneficial to a wide range of stakeholders in the financial market.

This paper systematically reviews existing research to consolidate the current understanding of analysts’ use of valuation models and factors. It aims to demystify what can often be seen as a “black box”, shedding light on the valuation tools employed by financial analysts across diverse industries.

The use of industry-specific valuation models and factors by analysts is a subject of considerable interest to both academics and investors. The predominant model in several industries is P/E, with some exceptions. Notably, EV/EBITDA is favored in the telecom, energy and materials sectors, while the capital goods industry primarily relies on P/CF. In the REITs sector, P/AFFO is the most commonly employed model. In specific sectors like pharmaceuticals, energy and telecom, DCF is utilized. However, theoretical models like RIM and AEG find limited use among analysts.

This is the first paper systematically reviewing the research on analyst’s use of industry-specific stock valuation methods. It serves as a foundation for future research in this field and is likely to be of interest to academics, analysts, fund managers and investors.

This study aims to determine how the applications of blockchain technology (BT) can play a crucial role in managing financial flows in the humanitarian supply chain (HSC) and what benefits and challenges are associated with BT in a humanitarian setting.

The present study used a qualitative research approach, incorporating a systematic literature review and conducting semi-structured interviews with 12 experts in the fields of humanitarian operations, supply chain management, fintech and information technology.

The findings show that the humanitarian sector has the potential to reap significant benefits from BT, including secure data exchange, efficient SCM, streamlined donor financing, cost-effective financial transactions, smooth digital cash flow management and the facilitation of cash programs and crowdfunding. Despite the promising prospects, this study also illuminated various challenges associated with the application of BT in the HSC. Key challenges identified include scalability issues, high cost and resource requirements, lack of network reliability, data privacy, supply chain integration, knowledge and training gaps, regulatory frameworks and ethical considerations. Moreover, the study highlighted the importance of implementing mitigation strategies to address the challenges effectively.

The present study is confined to exploring the benefits, challenges and corresponding mitigation strategies. The research uses a semi-structured interview method as the primary research approach.

This study adds to the existing body of knowledge concerning BT and HSC by explaining the pivotal role of BT in improving the financial flow within HSC. Moreover, it addresses a notable research gap, as there is a scarcity of studies that holistically cover the expert perspectives on benefits, challenges and strategies related to blockchain applications for effective financial flows within humanitarian settings. Consequently, this study seeks to bridge this knowledge gap and provide valuable insights into this critical area.

The purpose of this paper is to contribute to the debate on blockchain (BC) adoption for preventing counterfeiting by investigating BC systems where different options for BC feeding and reading complement the use of BC technology. By grounding on the situational crime prevention, this study analyses how BC systems can be designed to effectively prevent counterfeiting.

This is a multiple-case study of five Italian wine companies using BC to prevent counterfeiting.

This study finds that the desired level of upstream/downstream counterfeiting protection that a brand owner intends to guarantee to customers through BC is the key driver to consider in the design of BC systems. The study identifies which variables are relevant to the design of feeding and reading processes and explains how such variables can be modulated in accordance with the desired level of counterfeiting protection.

The cases investigated are Italian companies within the wine sector, and the BC projects analysed are in the pilot phase.

The study provides practical suggestions to address the design of BC systems by identifying a set of key variables and explaining how to properly modulate them to face upstream/downstream counterfeiting.

This research applies a new perspective based on the situational crime prevention approach in studying how companies can design BC systems to effectively prevent counterfeiting. It explains how feeding and reading process options can be configured in BC systems to assure different degrees of counterfeiting protection.