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Blockchain is an emerging technology that started in the cryptocurrency sphere with bitcoin but expanded to include numerous applications. This chapter provides an overview of the book. It begins by identifying the three main components of a blockchain. Next, it discusses the book's purpose, distinguishing features, and its intended audience. The chapter then outlines the book's structure, consisting of 22 chapters divided into four main parts. It offers a brief synopsis of each section and chapter. Finally, it ends with a summary and conclusions.

The purpose of this paper is to introduce a novel respiration pattern-based biometric prediction system (BPS) by using artificial neural network (ANN).

Respiration patterns were obtained using a knitted piezoresistive smart chest band. The ANN model was implemented by using four hidden layers to help achieve the best complexity to produce an adequate fit for the data. Not only did this study give a detailed distribution of an ANN model construction including the scheme of parameters and network layers, ablation of the architecture and the derivation of back-propagation during the iterations but also engaged a step-based decay to systematically drop the learning rate after specific epochs during training to minimize the loss and increase the model’s accuracy as well as to limit the risk of overfitting.

Findings establish the feasibility of using respiratory patterns for biometric identification. Experimental results show that, with a learning rate drop factor = 0.5, the network is able to continue to learn past epoch 40 until stagnation occurs which yielded a classification accuracy of 98 per cent. Out of 51,338 test set, the model achieved 51,557 correctly classified instances and 169 misclassified instances.

The findings provide an impetus for possible studies into the application of chest breathing sensors for human machine interfaces in the area of entertainment.

This is the first time respiratory patterns have been applied in biometric prediction system design.

The purpose of this paper is to identify if fraud theory models suggested over the years are applicable to match-fixing and if so, whether the Krambia-Kapardis’ (2016) holistic fraud and corruption prevention model can be used to reduce significantly match-fixing in football.

An online survey was developed by the authors and was administered to football stakeholders in Cyprus, namely, players, referees, coaches and team management.

The research questions, who are the initiators of match-fixing, why is match-fixing taking place and what is the best way to prevent or reduce match-fixing, have been answered, and these findings have enabled the authors to make policy recommendations.

The survey considered match-fixing in only one sport (football) while the number of respondent categories and the 335 usable questionnaires returned did not allow advanced statistical analysis of the data obtained.

The findings point to the need both for ethics and moral values to be installed in all the stakeholders through training and continuing education. It is also suggested that teams/clubs and related associations acting as regulators ought to implement governance principles and ethical programs, including whistleblowing lines and appoint integrity officers to minimize the match-fixing phenomenon. Furthermore, society, as well as government, sport regulators and sponsors, ought to encourage and demand fair play and integrity in sport through improved measures of governance and accountability and the implementation of ethical audits and public disclosure of audited financial statements of teams. Finally, sports integrity ought to be embedded in school curriculum from a very young age.

To the best of the authors’ knowledge, this is an original contribution to knowledge that has impact on the future of sporting fairness and social legitimacy.

The purpose of this paper is to investigate the impact of intellectual capital (IC) efficiency on the banks’ risk-taking and stability of Asian emerging markets.

This study uses a sample of 204 listed banks from 12 Asian emerging countries for the period 2010 to 2019. Data were analyzed using Ordinary Least Squares regression and checked for robustness using system generalized methods moment (GMM) estimation. The dependent variable of bank stability is measured using Z-score-based return on assets (ROA) and return on equity (ROE). The second dependent variable of bank risk is proxied by the standard deviation of ROA, ROE, non-performing loans and loan loss provision.

The results suggest the IC efficiency has no association with bank risk-taking and stability. The findings lend no support to the resource-based theory. The robustness of this result is confirmed by the system GMM estimation. However, support is found for the competition fragility view as high market power is associated with low risk-taking. The IC subcomponents, human capital efficiency (HCE) report a negative coefficient for bank risk-taking thereby having no support for the hypothesized relationships. Diversified banks with a higher deposit to total asset ratio resort to high risk-taking.

IC efficiency does not have an impact on the bank’s risk-taking behavior and stability for Asian banks. Managers can use these findings to improve their IC and boost investor confidence. Regulatory authorities should increase its monitoring function of banks when the GDP decreases as risk-taking behavior are galvanized during this period.

This research is one of the first to provide empirical evidence of IC efficiency’s relationship with bank stability and bank risk-taking. The implications are useful for policymakers, managers and governing bodies to enhance the banks’ IC efficiency.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.

Biometric authentication, which requires storage of biometric templates and/or encryption keys, raises a matter of serious concern, since the compromise of templates or keys necessarily compromises the information secured by those keys. To address such concerns, efforts based on dynamic key generation directly from the biometrics have recently emerged. However, previous methods often have quite unacceptable authentication performance and/or small key spaces and therefore are not viable in practice. The purpose of this paper is to propose a novel method which can reliably generate long keys while requires storage of neither biometric templates nor encryption keys.

This proposition is achieved by devising the use of fingerprint orientation fields for key generation. Additionally, the keys produced are not permanently linked to the orientation fields, hence, allowing them to be replaced in the event of key compromise.

The evaluation demonstrates that the proposed method for dynamic key generation can offer both good reliability and security in practice, and outperforms other related methods.

In this paper, the authors propose a novel method which can reliably generate long keys while requires storage of neither biometric templates nor encryption keys. This is achieved by devising the use of fingerprint orientation fields for key generation. Additionally, the keys produced are not permanently linked to the orientation fields, hence, allowing them to be replaced in the event of key compromise.

This study aims to explore how the application of digital technology and information technology can help firms improve their innovation performance and examines the mediating mechanisms of supply chain agility and supply chain integration.

This study conducted a questionnaire survey of 320 business managers in an automotive cluster in China and analyzed the collected data using structural equations.

Digital technology applications (DTA) have a positive impact on innovation performance, while supply chain agility and integration mediate this impact. In addition, information technology applications (ITA) also has a positive impact on innovation performance, while supply chain agility and integration mediate between the two. Supply chain agility (SCA) and supply chain integration (SCI) significantly enhance the positive impact of technology adoption on firms' innovation performance.

This study confirms the impact of digital technology and information technology applications on innovation performance and explores the mediating role played by supply chain agility and integration.