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This paper analyses the establishment and evolution of a public oversight body (POB) – the Egyptian Audit Oversight Unit (AOU) – and its implications for local auditing firms and practices.

Primary data were gathered from 34 semi-structured interviews (including follow-up ones) between 2014 and 2020. Secondary data was obtained through publicly available documents and internal memos. Drawing on Debord's (1967) Society of the Spectacle, the insights focus on the POB's conception, materialisation and evolution in a context characterised by weak regulatory structures.

Through a series of acts, the findings reveal how the AOU first accepted the image of “international best practice” oversight (the “metaphorical”), followed by the construction of the local structure and décor replicating a United States (US) style POB archetype (the “transformational”) by primarily relying on visible processes/procedures. Yet, these mechanisms emphasised the spectacular nature of oversight, with little improvement for practice and limiting itself to “cracking down” on smaller local firms. A final stage (the “performative”) reveals how the AOU seeks to expand its activities beyond its original mandate without challenging the image-driven nature of its oversight.

The paper offers two key contributions. First, it reveals how actors, through a combination of symbolic and tangible measures, create a new performative reality of public oversight. Second, it advocates Debord's “spectacle” to complement other theoretical lenses, with a view to illuminating the materialisation stages that bridge the gap between proclaimed oversight policies and actual practices (including conscious and unconscious omissions) within a given political economy context.

This study aims to understand the socioeconomic impact of flood events on households, especially household welfare in terms of changes in consumption and coping strategies to deal with flood risk. This study is based on Bihar, one of the most frequently flood-affected, most populous and economically backward states in India.

Primary data were collected from 700 households in the seven most frequently flood-affected districts in Bihar. A total of 100 individuals from each district were randomly selected from flood-affected villages. Based on a detailed literature review, an econometric (probit) model was developed to test the null hypothesis of the availability of consumption insurance, and the multivariate probability approach was used to analyze the various coping strategies of these households.

The results of this study suggest that flood-affected households maintain their consumption by overcoming various losses, including income, house damage and livestock loss. Households depend on financial transfers, borrowings and relief, and migrate to overcome losses. Borrowing could be an extra burden as the government compensates for house damage and crop loss late to the affected households. Again, there is no compensation to overcome livelihood loss and deal with occurrences of post-flood diseases, which further emphasizes the policy implications of strengthening the health infrastructure in the state and generating alternative livelihood opportunities.

This study discusses flood risk in terms of changes in household welfare, identifies the most effective risk-coping capabilities of rural communities and contributes to the shortcomings of the government insurance and relief model.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2023-0569

The devastating acute COVID-19 epidemic crippled the global economy in 2020. Within a month of the COVID-19 epidemic, every industry saw its stock prices plummet the most. Ending the COVID-19 pandemic will need equitable access to safe and effective vaccinations. This study aims to look at the link between COVID-19 vaccination and the stock markets for health and pharmaceutical sector.

The researchers used a mean-adjusted return model and event research approach to figure out how the first dose of the COVID-19 vaccine affects health and pharmaceutical sector stock market returns.

The evidence-based outcome indicates that immunisation announcement affects health and pharmaceutical company returns. Furthermore, the study concludes that the health and pharmaceutical industry is inefficient for a short period of time, but after 41 days, the sector absorbs the noisy information.

Since the outbreak, the development of COVID-19 vaccines has been a key focus of shareholders and investors. This study is unique in that it investigates the effect of the first dosage of SARS-CoV-2 vaccination on equity returns in the health and pharmaceutical industries, and it is likely to make a substantial contribution to the capital market literature on event methodology.

This paper explores international trade of the Chinese manufacturing industries through the lenses of network analysis (NA) to visualise the world trade network of the Chinese economy, describe its topology and better explain the international organisation of Chinese manufacturing industries.

The authors built a dataset of 40,550 Chinese companies and their 107,026 subsidiaries in 118 countries from Orbis-BVD and used a NA to investigate the connection between China and other countries. In particular, the authors studied the connections between Chinese companies and their subsidiaries in order to build a network of Chinese industries.

The authors found that the network of Chinese companies is ramified but not wide and it can be divided into two clusters. Moreover, the relations between China and other peripheral countries are strongly mediated by a few leading locations (e.g. Hong Kong and the USA).

This paper contributes to the literature in several ways. First, the authors provide empirical evidence on the magnitude and ramifications of Chinese enterprises in the world. The existing studies generally focus on applying NA to sectoral insights (Mao and Yang, 2012; Shaikh et al., 2016; Zheng et al., 2016; Wanzenbö ck, 2018; Krichene et al., 2019), whereas in this work the authors take a comprehensive view of the entire Chinese manufacturing system. Second, this paper complements the existing literature identifying the difference between cluster levels in Chinese manufacturing (Wu and Jiang, 2011) by proposing a cluster centralisation method to analyse the international network of Chinese firms rather than just the national network. Finally, the results also shed light on the international trade relationship between China, Hong Kong and the USA.

Most recent C-suite surveying suggests current applications of generative AI, although hyped, are fragmented and unlikely to yield major financial returns anticipated. Instead, business leaders expect major value from generative AI will be achieved through application of generative AI to innovation: operational innovation, product and service innovation, and most elusive of all, business model innovation.

Findings and analysis presented draws on data from several surveys of C-level executives conducted by IBM Institute for Business Value in collaboration with Oxford Economics during 2023. Each survey focused on the potential of generative AI in a particular business area. The n-count of each survey ranged from 100-3000.

1. Business leaders expect generative AI to build on returns achieved from investments in traditional AI, with 10 percent RoI expected on generative AI investments by 2025. 2. Executives anticipate that generative AI will have most impact when implemented to expand innovation. 3. Specific examples provided for operational innovation, product innovation, and business model innovation

We are still very early in the generative AI development cycle. We have made best efforts to project, but only time will tell for sure.

Business application of generative AI are extremely fragmented. Despite the desire to throw investments at the wall to see what sticks, it is important that leaders take a structured approach to generative AI, focusing on RoI from innovation investments.

To alleviate negative impacts of generative AI, focusing on innovation potential and value maximization is crucial.

This research is based on completely new surveying and data. This papers adds to the sum total of new knowledge in the generative AI domain.

Persons with disabilities (PwD) are generally less likely to be employed than the general population. The paper aims to investigate whether access to assistive technologies (AT) impacts labour force participation in the disabled population.

The study utilises the nationally representative survey on disability in India conducted in 2018 through multi-stage sampling by the Ministry of Statistics and Programme Implementation (MOSPI), Government of India. The instrumental variable (IV) approach has been employed to infer causality between AT and labour market participation.

The study found that the labour force participation rate (LFPR) in India amongst the disabled population was 29% in the age group of 15–65 years in 2017–2018, as compared to 52% in the general population. Around two-thirds of the PwD respondents who were advised to acquire aid appliances acquired them, implying limited access to AT. The probability of LFPR in disabled population increases by 26.6% with access to AT particularly in urban areas.

Persistent issues such as lack of adequate amenities, poor literacy and a lack of vocational skills need to be addressed to improve labour market outcomes for the disabled population in rural areas.

Despite its role in promoting distributive justice and inclusive development, research on equity gaps in access to AT and its impact on labour market outcomes is scant. This is the first paper that provides empirical evidence on the impact of access to AT on LFPR in the context of low- and middle-income countries.

As an emerging technology, Radio Frequency IDentification (RFID) and blockchain have the potential to disrupt many areas of business and social structure. However, it is loaded with significant technical, social, legal, financial and ethical complications that bring difficulty in its widespread use within the public distribution system (PDS). This research aims to analyze the barriers to integrated RFID and blockchain adoption in developing countries' PDS. Furthermore, this study also aims to validate the proposed framework against the Indian PDS.

The proposed framework consists of 10 potential barriers to integrated RFID and blockchain adoption. To identify the barriers, this study referred to the extant literature followed by consultations with domain experts. This study prepared the DEMATEL-based questionnaires, collected the data from four domain experts and analyzed them using an integrated Grey-DEMATEL approach.

The obtained results provide a precise list of barriers and the correlations among them. From the results, it is concluded that the unavailability of a skilled workforce at affordable cost, lack of knowledge about privacy level and unclear return on investment and benefits are the most critical blockchain adoption barriers in the context of Indian PDS.

This research proposes a framework consisting of 10 integrated RFID and blockchain adoption barriers in relation to Indian PDS. It also proposes a method for analyzing causal interrelationships between the barriers while allowing for data input from domain experts. Consequently, the framework is capable of coping with experts' biases and data scarcity.

The aim of this chapter is to describe the purpose of the introduction of the exchange rate commitment by the Czech National Bank (CNB) in the period from November 2013 to April 2017 and its effects on the real economy. The main reason for introducing the exchange rate commitment was concern about the possibility of a prolonged deflationary period in Czechia. Given that the standard monetary policy instruments had already been exhausted on easing the monetary policy conditions, the CNB Bank Board opted for an exchange rate commitment. The secondary objective of the exchange rate commitment was to boost the economy through the positive effect of a weaker koruna on exports. Next, we focus in more detail on the effect of the exchange rate commitment in the economy and the course of the foreign exchange interventions. Overall, we can summarize that the CNB's foreign exchange interventions were an extraordinary monetary policy instrument – in a market economy with inflation targeting and a flexible exchange rate – used in extraordinary times.

Since the last decade, debates regarding the efficiency and effectiveness of the forms of transfer, i.e. in the form of in-kind or cash transfers, have been gaining momentum. This paper aims to explore the preferences revealed by the beneficiaries, the role of contextual conditions in moulding these preferences, factors associated with the transfer scheme that defines the preferences and the rationale behind such responses.

The study conducted involves primary data collected from an Indian state, Odisha. 308 beneficiaries of the Targeted Public Distribution System (TPDS) were interviewed concerning specific objectives in a rural district (Mayurbhanj) and another highly urbanised district (Khordha).

The comparative results show that the strength of the contextual conditions significantly influences the preferences of the beneficiaries in the rural district as compared to the effect on the beneficiaries of the urban district. Education seems to have an insignificant impact in rural areas. However, income and standard of living have positive significant effects on shaping the preferences for cash or in-kind transfers.

Examining the strength of the contextual conditions and emphasising beneficiaries' perspectives would stimulate a better understanding of the implementation of the proposed quasi-Universal Basic Income. The study would hence, be instrumental in dealing with the transition towards cash transfers in the Indian context where the co-responsibility of both stakeholders, the government and the beneficiaries, should be given equal weightage.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0158

This paper provides a thorough examination of Socios.com, a blockchain platform that integrates token sales with the fan experience in the sports industry. The study focuses on three key aspects: the performance, bubble phenomenon and dynamics of fan tokens. The author aims to address important questions that may concern potential supporters and investors. Might sports fans incur financial losses due to their team loyalty? Is the fan token market just a passing trend? Are fan tokens driven by the behaviour of the cryptocurrency market?

This analysis aims to involve several methodologies. The author evaluates the short- and long-term performance of fan tokens by computing first-day and buy-and-hold (abnormal) returns. The author also employs the Phillips, Shi, and Yu's (PSY) real-time bubble detection method to investigate the presence of bubble phenomenon in the fan token market segment. Finally, the author examines the potential dependences between fan tokens, Chiliz and the cryptocurrency market (represented by the CCi30 index) using both Pearson/Kendall correlations and the wavelet coherence approach.

The study presents three notable contributions to the existing literature. First, the author demonstrates that investing in fan tokens to support one's favourite sports teams can lead to financial losses, whereas traders can potentially outperform the market by investing in Chiliz. Second, the author states that fan tokens were a short-lived trend, as evidenced by their decline in value after the bubble burst in 2021. Third, the findings indicate that the fan token market was influenced by the cryptocurrency market and Chiliz during periods of market downturns.

To the best of author’s knowledge, this is the first paper to conduct a comprehensive analysis of the performance, bubble phenomenon and dynamics of the token market fan segment, along with the exclusive on-platform currency, Chiliz.