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Due diligence refers to a comprehensive process of investigating and evaluating business opportunities in mergers and acquisitions. While early-stage due diligence usually encompasses financial and strategic assessment, one of the most important things in due diligence is looking at organizational culture at an early stage. This chapter takes stock of the existing research and practice in the area of cultural due diligence and evaluates the strengths and limitations. Based on the review of literature, we developed a framework for cultural due diligence to address the limitations of existing approaches. The framework illustrates a process to screen the M&A targets, gain insight into the target firm’s culture, and identify integration challenges. The process starts with more unobtrusive, indirect, and informal assessments of the target firm’s culture and moves onto more obtrusive, direct, and formal assessments.

Cross-border acquisitions play an important role in corporate strategic development and international expansion. During the past decades, mergers and acquisitions have been intensively researched through the lenses of strategic management, corporate finance, behavioral finance, etc. Despite the intense effort, the progress made is still fragmented and lacks unifying theories that approach the entire acquisition process on the one hand, and in-depth research of critical factors on the other. The intent of the research paper is to establish a vital link between academic research and practice of mergers and acquisitions, especially regarding the pre-acquisition evaluation.

In detail, the research paper investigates critical factors – and their inclusion in the pre-acquisition due diligence, before decision about acquisition is made. Pre-acquisition due diligence theoretically conforms to organizational learning theory, which proposes the more the acquiring firm learns about the acquisition target, the higher the probability of a successful acquisition. The central hypothesis states that due diligence, including the critical factors, in the pre-acquisition phase is related to acquisition success.

Using a multidimensional measure of critical factors, the empirical evidence is based on 85 cross-border acquisitions that took place between 2007 and 2013 in the European automotive industry. The quantitative analysis finds positive association between the Choice of Strategic Partner, Business Capabilities and HR Knowledge, and Financial Factors and Acquisition Premium as critical factors of due diligence and acquisition success. The strongest relationship is between business capabilities and knowledge transfer as the main asset for realization of synergy values and successful acquisition. In this context, the valuation of the business capabilities of the acquisition targets is classified as the main challenge for reflecting suitability of the acquisition price and establishing value generation from the combined firms in the post-acquisition phase.

By studying acquisition risk and critical factors – both success and failure reasons – this research tested and proved theoretically sound framework for successful acquisition. From a practical standpoint, the research results provide acquisition management with a proven model for pre-evaluating acquisition candidates by means of comprehensive due diligence.

The authors provide a general framework of behavior under asymmetric information and develop indices of diligence, objectivity and quality by an analyst and analyst firm about a studied firm, and relate them to the accuracy of its forecasts. The authors test the associations of these indices with time.

The test of Public Information versus Non-Public Information Models provides the index of diligence, which equals one minus the p-value of the Hausman Specification Test of Ordinary Least Squares (OLS) versus Two Stage Least Squares (2SLS). The test of Objectivity versus Non-Objectivity Models provides the index of objectivity, which equals the p-value of the Wald Test of zero coefficients versus non-zero coefficients in 2SLS regression of the earnings forecast residual. The exponent of the negative of the standard deviation of the residuals of the analyst forecast regression equation provides the index of analytical quality. Each index asymptotically equals the Bayesian ex post probability, by the analyst and analyst firm about the studied firm, of the relevant behavior.

The authors find that ex post accuracy is a statistically and economically significant increasing function of the product of the indices of diligence, objectivity and quality by the analyst and analyst firm about the studied firm, which asymptotically equals the Bayesian ex post joint probability of diligence, objectivity and quality. The authors find that diligence, objectivity, quality and accuracy did not improve with time.

There has been no previous work done on the systematic and objective characterization and joint analysis of diligence, objectivity and quality of analyst forecasts by an analyst and analyst firm for a studied firm, and their relation with accuracy. This paper puts together the frontiers of various disciplines.

The paper aims to propose a mediation moderated model to examine the influence of academic reliance on students' intellectual engagement.

Four hundred and seventy-one respondents who completed a self-reported questionnaire were chosen to participate in the study using a convenient sampling technique. The hypotheses were tested using PLSc.

Findings from the study reveal academic resilience and academic diligence positively predicts students' intellectual engagement. Academic diligence positively predicts students' intellectual engagement and further mediates the effect of academic resilience on intellectual engagement. Finally, learning support positively predicts intellectual engagement and further moderates the effect of the association between academic resilience and academic diligence on intellectual engagement.

This research shows that higher education administrators must establish effective and efficient policies that integrate students' academic resilience, academic diligence and learning assistance.

This paper is amongst the first to have tested a model including resilience, academic diligence, intellectual engagement and learning support in a university setup from a developing country perspective.

Customer due diligence measures that are employed in the United Kingdom (UK) to detect and combat money laundering are discussed. The UK adopted a progressive regulatory and enforcement framework to combat money laundering which relies, inter alia, on the use of customer due diligence measures to regulate and curb the occurrence of money laundering activities in its financial institutions and financial markets. However, other regulatory measures that could have contributed to the effective combating money laundering in the UK will not be explored in detail since the article is focused on the reliance and use of customer due diligence measures to curb money laundering activities. Accordingly, the strength, flaws and weaknesses of the UK anti-money laundering regulatory and enforcement framework are examined. Lastly, possible recommendations to address such flaws and weaknesses are provided.

The paper discusses customer due diligence measures that are used in the UK to detect and combat money laundering.

It is hoped that policymakers and other relevant persons will use the recommendations provided in the paper to enhance the curbing of money laundering in the UK.

The paper does not provide empirical research.

The study is useful to all policymakers, lawyers, law students and regulatory bodies in the UK.

The study seeks to curb money laundering in the UK society globally.

The study is original research on the use of customer due diligence measures to detect and combat money laundering in the UK.

This paper explores the historical aspects of customer due diligence and related anti-money laundering measures in South Africa. Customer due diligence measures are usually employed to ensure that financial institutions know their customers well by assessing them against the possible risks they might pose such as fraud, money laundering, Ponzi schemes and terrorist financing. Accordingly, customer due diligence measures enable banks and other financial institutions to assess their customers before they conclude any transactions with them. Customer due diligence measures that are utilised in South Africa include identification and verification of customer identity, keeping records of transactions concluded between customers and financial institutions, ongoing monitoring of customer account activities, reporting unusual and suspicious transactions and risk assessment programmes. The Financial Intelligence Centre Act 38 of 2001 (FICA) as amended by the Financial Intelligence Centre Amendment Act 1 of 2017 (Amendment Act) is the primary statute that provides for the adoption and use of customer due diligence measures to detect and combat money laundering in South Africa. Prior to the enactment of the FICA, several other statutes were enacted in a bid to prohibit money laundering in South Africa. Against this background, the article provides a historical overview analysis of these statutes to, inter alia, explore their adequacy and examine whether they consistently complied with the Financial Action Task Force Recommendations on the regulation of money laundering.

The paper provides an overview analysis of the historical aspects of the regulation and use of customer due diligence to combat money laundering in South Africa. In this regard, a qualitative research method as well as the doctrinal research method are used.

It is hoped that policymakers and other relevant persons will adopt the recommendations provided in the paper to enhance the curbing of money laundering in South Africa.

The paper does not provide empirical research.

The paper is useful to all policymakers, lawyers, law students and regulatory bodies, especially, in South Africa.

The paper advocates for the use of customer due diligence measures to curb money laundering in the South African financial markets and financial institutions.

The paper is original research on the South African anti-money laundering regime and the use of customer due diligence measures to curb money laundering in South Africa.

The purpose of this of this paper is to show that judging by the number of mergers that still go sour, there is plenty of room to intensify the kind of operational due diligence that can uncover deal‐breaking factors before they destroy shareholder value. The paper focuses on specifically supply chain and IT as the two operations areas that deserve special attention because they still get short shrift.

The paper was written based on survey findings, publicly sourced information, case study work and Accenture's point of view based on work at over 400 M&A client engagements, three quarters with companies in the Global 1000. The two surveys cited are: 2006 Accenture study of supply chain managers; and Third Annual Due Diligence Symposium 2007 Survey.

The paper finds that when senior, experienced operations experts are involved in due diligence and pre‐merger planning, the major risks and potential deal breakers are exposed quickly – before deal momentum pushes things to the point where participants are reluctant to walk away. Also, with this input, deal makers can accurately assess the true investments needed as well as the “to be” operating costs of the joined companies. Those numbers can be used to adjust post‐merger cash flow projections, which are often extrapolated based on percentage estimates and projected top‐down rather than bottom‐up based on major projects under way or on operating model complexity. The operations experts allow new potential sources of value to be identified and considered as part of the valuation of the target company. The purchase price may then be adjusted up or down.

Dealmakers have significantly improved their understanding of, and skills in conducting, many elements of mergers and acquisitions, especially valuation and merger integration. Yet in example after example, due diligence processes have proven to be an Achilles heel. Dealmakers today must use every tool at their disposal to improve their odds of a successful deal while at the same time avoiding bad acquisitions. That means placing the same importance on operational due diligence as on valuation, traditional due diligence and merger integration. It also calls for using operational due diligence to pinpoint initiatives that protect and create value after an acquisition. The shift to this next level of due diligence will require enhancing rather than replacing traditional due diligence activities. The due diligence lists will be longer, yes, but importantly, they will be forward‐looking, gauging current observations against future operating needs.

This research provides fundamentals for generating (partially) automated standardized due diligence reports. Based on original digital building documents from (institutional) investors, the potential for automated information extraction through machine learning algorithms is demonstrated. Preferred sources for key information of technical due diligence reports are presented. The paper concludes with challenges towards an automated information extraction in due diligence processes.

The comprehensive building documentation including n = 8,339 digital documents of 14 properties and 21 technical due diligence reports serve as a basis for identifying key information. To structure documents for due diligence, 410 document classes are derived and documents principally checked for machine readability. General rules are developed for prioritized document classes according to relevance and machine readability of documents.

The analysis reveals that a substantial part of all relevant digital building documents is poorly suited for automated information extraction. The availability and content of documents vary greatly from owner to owner and between document classes. The prioritization of document classes according to machine readability reveals potentials for using artificial intelligence in due diligence processes.

The paper includes recommendations for improving the machine readability of documents and indicates the potential for (partially) automating due diligence processes. Therefore, document classes are derived, reviewed and prioritized. Transaction risks can be countered by an automated check for completeness of relevant documents.

This paper is the first published (empirical) research to specifically assess the automated digital processing of due diligence reports. The findings are helpful for improving due diligence processes and, more generally, promoting the use of machine learning in the property sector.

The purpose of this paper is to explore the role of independent directors’ diligence in restraining earnings management practices in the Indian context.

It employs a panel data analysis to test the association of earnings management with the diligence of independent directors.

The results suggest that the diligence of independent directors has a significant impact on earnings management. The findings support the agency theory and provide evidence of the role played by the board processes in restricting earnings management.

This study is important for the regulators as it highlights the significance of independent directors’ diligence in producing higher quality financial statements, thereby creating the real economic value of companies. This is the first article that explores the impact of independent directors’ diligence on earnings management practices particularly in the context of an emerging economy, like India in the light of new Companies Act 2013 and revised Clause 49 of the Listing Agreement, 2014 by Securities and Exchange Board of India.

The individual levels involved in real estate management are thoroughly discussed in the literature. This paper provides a structured meta-analysis of the different theoretical approaches in German-speaking countries. It also investigates the integration of transaction management and technical due diligence into the concepts of organisation theory. In this process, the interfaces are analysed and optimised models are developed for transferring the technical due diligence findings to the operational level.

Interviews with transaction management experts were conducted based on a narrative literature review. These interviews shed light on how the components of transaction management and due diligence are integrated into the transaction process, with a particular focus on technical due diligence. They also provide insights into how the related results are taken into account in relation to the transaction, and how they are transferred into the operational phase.

It becomes apparent that the role of transaction management is not clearly defined and delimited in the structural model of the real estate industry. Technical due diligence findings are usually transferred to the operation of the property via several, manual interfaces with corresponding losses of knowledge. The related models derived and developed for the purpose of operational optimisation define the role of transaction management against a technical background and identify the interfaces to be considered.

The significance of transaction management for subsequent operations is discussed and elaborated on. More specifically, transferring safety-relevant, high-priority findings from the technical due diligence exercise plays a crucial role for the modelling stage. On the implementation level, the derived models serve as a basis for customising the internal organisational structure.

In Germany, there has hardly been any research into the involvement of technical experts in the real estate transaction process to date. This paper provides initial approaches to optimising organisational structures and sustainably integrating technical due diligence findings into real estate operations.