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The purpose of this study is to develop an integrated model for the stochastic multiproject scheduling and material ordering problems, where some of the prominent features of offshore projects and their environmental-degrading effects have been embraced as well. The durations of activities are uncertain in this model. The developed formulation is tri-objective that seeks to minimize the expected time, total cost and CO₂ emission of all projects.

A new version of the multiobjective multiagent optimization (MOMAO) algorithm has been proposed to solve the amalgamated model. To empower the MOMAO, various procedures of this algorithm have been modified based on the multiattribute utility theory (MAUT) technique. Along with the MOMAO, this study has employed four other meta-heuristic methodologies to solve the model as well.

The outputs of the MOMAO have been put to test against four other optimizers in terms of convergence, diversity, uniformity and computation times. The results of the Mean Ideal Distance (MID) metric have revealed that the MOMAO has strongly prevailed its rival optimizers. In terms of diversity of the acquired solutions, the MOMAO has ranked the first among all employed optimizers since this algorithm has offered the best solutions in 56.66 and 63.33% of the test problems regarding the diversification metric and hyper-volume metrics. Regarding the uniformity of results, which is measured through the spacing metric (SP), the MOMAO has presented the best SP values in more than 96% of the test problems. The MOMAO has needed more computation times in comparison to its rivals.

A real case study comprising two concurrent offshore projects has been offered. The proposed formulation and the MOMAO have been implemented for this case study, and their effectiveness has been appraised.

Very few studies have focused on presenting an integrated formulation for the stochastic multiproject scheduling and material ordering problems. The model embraces some of the characteristics of the offshore projects which have not been adequately studied in the literature. Limited capacities of the offshore platforms and cargo vessels have been embedded in the proposed model. The offshore platforms have spatial limitations in storing the required materials. The vessels are also capacitated and they also have limited shipment capacities. Some of the required materials need to be transported from the base to the offshore platform via a fleet of cargo vessels. The workforces and equipment can become idle on the offshore platform due to material shortage. Various offshore-related costs have been integrated as a minimization objective function in the model. The cargo vessels release CO₂ detrimental emissions to the environment which are sought to be minimized in the developed formulation. To the best of the authors' knowledge, the MOMAO has not been sufficiently employed as a solution methodology for the stochastic multiproject scheduling and material ordering problems.

This study aims to develop a model for coordination and communication overhead in distributed software development through case study analysis in the Indian outsourcing software industry. The model is based on business knowledge, which can be classified as domain, regulatory, strategic, business process and operation process knowledge as per existing literature.

Double case study method was used to verify an existing knowledge–management framework of software development from the literature. The stakeholders of both the cases were interviewed, and project documents were verified to reach conclusions.

The findings supported the business knowledge classification from the literature. The concept can be used to analyze the software project in a distributed environment.

The research work findings are based only on two case studies. The study findings cannot be generalized and should be used as a learning tool. There can be large variations of project characteristics with differences in business knowledge requirements. The research shows the importance of business knowledge transfer in global software development.

Projects managers in the distributed software development environment can use the findings in project planning and work allocation for better control over cost and schedule, etc.

There is little research works attempted to study the business knowledge classification in the global software industry making the research novel.

This study empirically explores the intraday price discovery mechanism and volatility transmission effect between the dual-listed Indian Nifty index futures traded simultaneously on the onshore Indian exchange, National Stock Exchange (NSE) and offshore Singapore Exchange (SGX) and its spot market by using high-frequency data.

This study applies the vector error correction model to analyze the lead-lag relationship in price discovery among three markets. The contributions of individual markets in assimilating new information into prices are measured using various measures, Hasbrouck's (1995) information share, Lien and Shrestha's (2009) modified information share and Gonzalo and Granger's (1995) component share. Additionally, the Granger causality test is conducted to determine the causal relationship. Lastly, the BEKK-GARCH specification is employed to analyze the volatility transmission.

This study provides robust evidence that Nifty futures lead the spot in price discovery. The offshore SGX Nifty futures consistently ranked first in contributing to price discovery, followed by onshore NSE Nifty futures and finally by the spot. Empirical results also show unidirectional causality and volatility transmission from Nifty futures to spot, as well as bidirectional causal relationship and volatility spillovers between NSE and SGX Nifty futures. These novel findings provide fresh insights into the informational efficiency of the dual-listed Indian Nifty futures, which is distinct from previous literature.

These findings can potentially help market participants, policymakers, stock exchanges and regulators.

Unlike previous studies in this area, this is the first study that empirically examines the intraday price discovery mechanism and volatility spillover between the dual-listed futures markets and its spot market using 5-min overlapping price data and trivariate econometric models.

To address the absence of Lean in transportation logistics in the digital era, this study aims to investigate the application of Lean transportation (LT) tools to reduce waste and facilitate the digital transformation of dedicated road transportation in the offshore industry.

The study adopts action research with a multimethod approach, including a scoping review, focus groups (FG) and participant observation. The research is conducted within the offshore supply chain of a major oil and gas company.

Implementing LT’s continuous improvement tools, particularly value stream mapping (VSM), reduces offshore transportation waste and provides empirical evidence about the intersection of Lean and digital technologies. Applying techniques drawn from organisational learning theory (OLT), stakeholders involved in VSM mapping and FGs engage in problem-solving and develop action plans, driving digital transformation. Waste reduction in loading and unloading stages leads to control actions, automation and process improvements, significantly reducing downtime. This results in an annual monetary gain of US$1.3m. The study also identifies waste related to human effort and underutilised digital resources.

This study contributes to theory and practice by using action research and LT techniques in a real intervention case. From the lens of OLT, it highlights the potential of LT tools for digital transformation and demonstrates the convergence of waste reduction through Lean and Industry 4.0 technologies in the offshore supply chain. Practical outputs, including a benchmarking questionnaire and a plan-do-check-act cycle, are provided for other companies in the same industry segment.

The purpose of this paper is to understand the impending relationship between the impact of the US–China trade war on Taiwanese firms' spending on R&D and their offshore investment in technologically advanced countries (TAC), the authors examined if changes in these firms' R&D ratios and the growing presence of skilled workers in Taiwan's labour market during the trade war have affected their offshore investments in TAC.

Using a model built on pooled cross-sectional time-series data from 2012–2019, the authors examined whether a change in R&D ratios of domestic firms in Taiwan and the growing presence of skilled workers in Taiwan's labour market have affected the offshore investment by these firms during the trade war. Using data from the Manpower Utilisation Survey, the authors applied differences–in–differences–in–differences and differences–in–differences–in–differences–in–differences estimation methods and found that the trade war indeed gave a boost to Taiwan's job market, particularly for skilled workers.

From the estimation results, the authors noticed a rise in employment opportunities alongside a decline in the earnings of skilled workers in industries where more firms have spent on R&D as well as invested in offshore operations. However, firms in Taiwan that had not heavily spent on R&D from industries where investment in foreign operations was otherwise high have also attracted skilled workers during the trade war.

An in-depth analysis of the impact of the trade war on domestic firms' spending on R&D and their investment in offshore operations in TAC should be helpful to policymakers interested in understanding the effects of the trade war and subsequent changes in firms' spending on R&D on labour market outcomes. If changes in the R&D ratios and a steady supply of skilled workers influenced the outflow of Foreign Direct Investment (FDI) to TAC, this insight could be helpful for those devising policies and measures to curb the impact of the trade war on domestic spending on R&D.

The study findings not only provide broad lessons to policymakers in Taiwan, but the country case study can guide growing economies that are equally careful while perceiving trade war as a significant deterrent to domestic R&D spending and the outflow of FDI.

This study aims to examine how external and internal conditions drive the impact of circular economy mechanism by decomposing into three policy networks in terms of reduce, reuse and recycle, to better understand the contingency model of climate change and effect of firm size on subsequent performance.

Drawing on circular economy network and resource-based view (RBV)-network-resilience strategy framework, a pooled longitudinal cross-sectional data model is developed using a sample of 4,050 Taiwanese manufacturing multinational corporations (MNCs) making foreign direct investment between 2013 and 2018. Structural equation modeling analysis is used to comprehensively examine and investigate each circular economy policy network in the context of climate change and firm size. Post hoc multigroup analysis (MGA) is also conducted.

MGA shows that the reduce policy network is positively and negatively related to manufacturing know-how and production size, respectively. The impact of reuse policy network can enhance the competence of large firms. The recycle policy network is more prominent in terms of competence enhancement of climate change.

MNCs are seeking to build circular economy policy networks to a greater extent, given climate change pressure and guidelines.

This study adds to the circular economy and RBV-network-related literature on climate change and interactions to enhance performance, echoing the recent call on the sustainability of the circular economy of MNCs.

This paper aims to examine the history of data leaks and investigative journalism, the techniques and technology that enable them and their influence in Australia and abroad. It explores the ethical and professional considerations of investigative journalists, how they approach privacy and information-sharing and how this differs from intelligence practice in government and industry. The paper assesses the strengths and limitations of Collaborative Investigative Reporting based on Information Leaks (CIRIL) as a kind of public-facing intelligence practice.

This study draws on academic literature, source material from investigations by the International Consortium of Investigative Journalists and the Organised Crime and Corruption Reporting Project, and a survey of financial crime compliance professionals conducted in 2022.

The paper identifies three key causal factors that have enabled the rise of CIRIL even as traditional journalism has declined: the digital storage of information; increasing public interest in offshore finance and tax evasion; and “virtual newsrooms” enabled by internet communications. It concludes that the primary strength of CIRIL is its creation of complex global narratives to inform the public about corruption and tax evasion, while its key weakness is that the scale and breadth of the data released makes it difficult to focus on likely criminal activity. Results of a survey of industry and government professionals indicate that CIRIL is generally more effective as public information than as an investigative resource, owing to the volume, age and quality of information released. However, the trends enabling CIRIL are likely to continue, and this means that governments and financial institutions need to become more effective at using leaked information.

Over the past decade, large-scale, data-driven investigative journalism projects such as the Pandora Papers and the Russian Laundromat have had a significant public impact by exposing money laundering, financial crime and corruption. These projects share certain hallmarks: the use of human intelligence, often sourced from anonymous leaks; inventive fusion of this intelligence with data from open sources; and collaboration among a global collective of investigative journalists to build a narrative. These projects prioritise informing the public. They are also an important information source for government and private sector organisations working to investigate and disrupt financial crime.

The purpose of this study is to extend the Fraud Diamond Theory to celebrity Special Purpose Acquisition Companies (SPACs) and investigate their post-Initial Public Offering (IPO) stock market performance.

After obtaining a sample of celebrity SPACs from the Spacresearch.com database, fraud risk characteristics were obtained from Lexis Nexus searches. Buy and hold abnormal returns were calculated for celebrity SPACs versus a small-cap equity benchmark for time intervals after IPO, and multiple regression analysis was performed to examine the relationship between fraud risk features and post-IPO returns.

Celebrity SPACs exhibit Fraud Diamond characteristics and significantly underperform a small-cap stock portfolio on a risk-adjusted basis after IPO.

This study only examines celebrity SPACs that conducted IPOs on the NYSE and NASDAQ/AMEX and does not include those that are traded on the Over the Counter Bulletin Board (OTCBB).

Celebrity endorsement of SPAC vehicles attracts investors who may not be properly informed regarding the risk characteristics of SPACs. Accordingly, investors should be warned that celebrity SPACs underperform a small-cap equity portfolio and exhibit significant elements of fraud risk.

The use of celebrity endorsement as a marketing device to attract investment in SPACs has regulatory implications.

To the best of the authors’ knowledge, this paper is the first to examine the fraud risk characteristics and post-IPO performance of celebrity SPACs.

This study aims to empirically examine the influence of Islamic corporate social responsibility (ICSR) on social welfare moderated by financial fraud.

The method used was the mix method. The number of respondents was 410. They combined the moderate regression analysis with PROCESS Andrew F Hayes to test the research hypothesis. After conducting the survey, it was continued by conducting interviews with the village community and the head of the village.

The first finding of this study is that ICSR has a significant positive effect on social welfare. The second finding is that financial fraud weakens the influence of ICSR on social welfare. The results of the interviews also confirmed the two findings of this study.

The high level of bias in answering the questions is due to the low public knowledge of ICSR. In addition, the interviews still needed to involve the oil and gas companies and government.

The main implication is improving social welfare, especially for those affected by offshore oil drilling. Furthermore, stakeholders are more sensitive to the adverse effects of financial fraud. Finally, to make drilling companies more transparent and on target in implementing ICSR.

The main novelty in this research is using of the mixed method. In addition, applying financial fraud as a moderating variable is rarely studied empirically.

The purpose here is to show how the “shadow” economy has grown in scale and impetus in recent years, though even before modern times it has been present (e.g. the City of London, Shaxson, 2011) since at least the middle ages. The reasons for this have become complicated, but we can identify some “deep structures” that are common. Firstly, “globalisation” made it easier for multinationals to escape national regulatory regimes. Secondly, one of the ways neoliberal trading regulations allowed such actors to augment their assets was by means of what they initially called “transfer-pricing” but which now is officially known as “profit shifting” through tax havens. Thirdly, the growth in international trade in legal and illegal ways caused money laundering – even by otherwise respectable banks – to grow across borders. Conversely, from the supply-side, tax haven status was increasingly accessed by jurisdictions that sought to achieve economic growth by supplying tax haven services, both Delaware and Ireland as exemplars of a “developmental” fiscal policy.

This paper adopts a “pattern recognition” design, an approach that is abductive, meaning interpretive, as shown in the observation that explanation can be valid or reliable without direct observation. This is shown in the indirect observation that “rain fell because the terrace has puddles” or “ancient glaciers once carved this valley”.

Reviewing the European Union’s (EU) list of non-co-operating jurisdictions in support of the OECD’s review of base erosion and profit-shifting activity, Collin concluded the EU’s listing “moved the needle” somewhat but was only a modest success. This is because of its reluctance to sanction its own members or large economies like the USA. Data on foreign direct investment and offshore banking assets suggest listed jurisdictions did not suffer notably from being named and shamed. In all cases studied, this contribution found legally damaging, fraudulent, conflict of interest and corrupt practice activities everywhere.

The originality is found in three spheres. Firstly, the pattern recognition method was vindicated in yielding hard to research results. Secondly, the “assemblage-thirdspace” theory was found advantageous in demonstrating the uneven geography of tax haven clusters and their common history in turbocharging economic development. Finally, the empirics showed the ruses executed by cluster members in tax havens to circumvent the law from global management consultancies to micro-firms consisting of tax lawyers and other experts interacting in knowledge supply chains of dubious morality.