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THE GLOBAL MERGERS AND ACQUISITIONS MARKET: STATUS AND FEATURES OF TRANSFORMATION

2023· article· en· W4394610397 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTRADE AND MARKET OF UKRAINE · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Development and Digital Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsMergers and acquisitionsTransformation (genetics)BusinessIndustrial organizationFinanceChemistry

Abstract

fetched live from OpenAlex

Objective. The objective of the present study is to analyse the state and peculiarities of the transformation of the global M&A market in 2013-2022. Methods. The following methods and techniques of cognition were used: analysis and synthesis, induction and deduction (to substantiate the importance and role of the study of the status and features of the global M&A market), generalisation and systematisation (to identify the main indicators of the global M&A market), analysis of time series (to identify trends and patterns of development, features of transformation of the global M&A market in 2013-2022), graphical (for a visual representation of the peculiarities of the global M&A market development). Results. Based on the analysis of the data of the United Nations Conference on Trade and Development (UNCTAD), the author found that in 2013-2022 the global M&A market was characterised by dynamic development, in particular, an increase in the aggregate value and number of M&A transactions concluded globally; significant structural imbalances in development; significant variability and growth in the average value of M&A transactions observed in different groups of countries and different sectors of the economy. Thus, it is established that in 2013-2022 there was an increase in the total value of M&A transactions concluded in the world - the total value of M&A transactions concluded in the world increased by more than USD 444 billion and amounted to USD 706.6 billion as of 2022. Increase in the number of M&A transactions - the number of M&A transactions in the world increased by 2827 transactions to 7763 transactions as of 2022. The article establishes that the most dynamically growing structural element of the global M&A market is the relevant market of developed countries. Developed countries are significantly ahead of developing countries both in terms of value and quantity of M&A transactions. In macro-regional terms, the highest aggregate value and number of M&A transactions were characteristic of Europe (on average, 43.2% of the aggregate value of M&A transactions in the world, 50.1% of the total number of M&A transactions in the world), in particular the European Union (on average, 23.9% and 33.9%, respectively); Americas, in particular North America (on average 33.4% and 22.8%, respectively); Asia (on average 11.3% and 11.5%, respectively), in particular East and South-East Asia (on average 6.98% and 6.7%, respectively).In terms of countries, the United Kingdom, the United States, Australia, Sweden, France, Canada, Switzerland, Saudi Arabia, the Netherlands, China, Spain, Germany and Denmark accounted for the largest aggregate value and number of M&A deals. These countries accounted for more than 50% of the total value and number of M&A transactions. In terms of sector, the tertiary sector of the economy accounted for the largest total value and number of M&A transactions. On average, the tertiary sector accounted for 51.1% of the total value and 70.4% of the total number of M&A deals concluded globally. In terms of industry sectors, the largest aggregate value and number of M&A transactions were in the following industries: information and communications; mining; finance and insurance; transportation and storage; pharmaceuticals, electronics and electrical equipment; trade; professional services; food, beverages and tobacco; and real estate. On average, these industries accounted for more than 70% of the total value and number of M&A transactions. It was determined that the average value of M&A transactions in the world increased by an average of USD 37.8 million and amounted to USD 91 million in 2022. The average value of M&A deals in emerging markets was higher than the average value of the corresponding deals both globally and in developed countries. The average value of M&A transactions in the primary sector of the economy is significantly higher than the value of M&A transactions in other sectors of the economy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.873
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.209
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it