The impact of mergers and acquisitions on shareholders' wealth in the logistics service industry

Kiesel, Florian; Ries, J. M.; Tielmann, Artur

doi:10.1016/j.ijpe.2017.09.006

Cited by 22 publications

(25 citation statements)

References 86 publications

(101 reference statements)

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“…Second, the long term stock returns performance is measured with the help of Buy-and-Hold Abnormal Returns (BHAR). In the financial researches, this approach is used (26) , Further, this technique is also used in M&As so that short term and long term impact of M&As can be analyzed and these synergies impact on the firm performance in terms of stock returns could be assessed (27) . The market model has been employed to estimate abnormal returns in the event window of 91 days.…”

Section: Methodsmentioning

confidence: 99%

Impact of mergers and acquisitions on shareholders' wealth: a study of Telecom sector of Pakistan

Hussain¹

2020

IJST

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Objectives: This study aims to investigate the impact of mergers and acquisitions related events on the shareholders' wealth in Telecom sector of Pakistan. Statistical analysis: Event study methodology has been used to achieve this objective, in which, the short term and long term performance of firms are measured. For short term performance, Abnormal Returns (AR) and Cumulative Abnormal Returns (CAR) are measured while to determine long term performance, Buy-and-Hold Abnormal Returns (BHAR) are measured. Findings: The results revealed that the occurrence of these events has negatively affected the shareholders' wealth and the financial market did not respond to these events in the telecom sector of Pakistan. Application: The study suggests that the telecom sector should choose different strategies to gain market share, to increase revenues, to gain a competitive edge and to diversify risk.

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Section: Methodsmentioning

confidence: 99%

Impact of mergers and acquisitions on shareholders' wealth: a study of Telecom sector of Pakistan

Hussain¹

2020

IJST

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“…Assumption 4. Successful CBM&A can increase the revenue of MNCs through mechanisms such as cost savings, increased profits, upscaling, and abundant resources as has been demonstrated in different economic sectors [67][68][69].…”

Section: Assumptionmentioning

confidence: 99%

Reverse Knowledge Transfer in Cross‐Border Mergers and Acquisitions in the Chinese High‐Tech Industry under Government Intervention

Guo

Yang

2021

Complexity

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The high-tech industry is the main force promoting the development of China’s national economy. As its industrial economic strength grows, China’s high-tech industry is increasingly using cross-border mergers and acquisitions (CBM&A) as an important way to “go out.” To explore the rules governing the process and operation mechanism of reverse knowledge transfer (RKT) through the CBM&A of China’s high-tech industry under government intervention, a tripartite evolutionary game model of the government, the parent company, and the subsidiary as the main subjects is constructed in this paper. The strategies adopted by the three subjects in the RKT game process are analysed, and the factors influencing RKT through CBM&A under government intervention are simulated and analysed using Python 3.7 software. The results show that, under government intervention, the parent company and subsidiary have different degrees of influence on each other. Subsidiaries are highly sensitive to the compensation rate of RKT. Positive intervention by the government tends to foster stable cooperation between the parent company and the subsidiary. However, over time, the government gradually relaxes its intervention in the RKT and innovation of multinational companies.

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“…Kiesel et al [17] examined the features of goods transport and storage of Qinghai Railway, and optimized RLP structure in terms of good diversity, marketing strategy, and intermodal transport, based on the production situation of railway goods and the design principles of RLP. From the perspectives of logistics safety, greenness, and social benefits, Binder et al [18] identified the factors affecting RLP's operational benefits, constructed a reasonable evaluation index system (EIS), and provided the intelligent park management center with the top and bottom design techniques for operation management platform.…”

Section: Introductionmentioning

confidence: 99%

Inventory Management of Railway Logistics Park Based on Artificial Neural Network

Gao¹,

Dou²

2020

JESA

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In recent years, China has stepped up its support to the optimization and development of railways. Meanwhile, the development of modern information technology (IT) has enhanced the economic advantages of railway logistics. To intelligently manage the inventory of railway logistics park (RLP), this paper integrates artificial neural network (ANN) into RLP inventory management. Firstly, the functional demand of RLP inventory management was analyzed comprehensively, and the main factors affecting the inventory demand were divided into different categories. Then, the authors formulated the framework of intelligent inventory management for RLP, and put forward the strategy of continuous periodic inventory monitoring. Finally, a RLP inventory prediction model was constructed based on optimized genetic algorithm (GA) and backpropagation neutral network (BPNN), and proved effective through experiments. The research results provide reference for the application of ANN in inventory management and prediction in other logistics fields.

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The impact of mergers and acquisitions on shareholders' wealth in the logistics service industry

Abstract: This is the other version of the paper.This version of the publication may differ from the final published version. Permanent repository link:

Cited by 22 publications

References 86 publications

Impact of mergers and acquisitions on shareholders' wealth: a study of Telecom sector of Pakistan

Impact of mergers and acquisitions on shareholders' wealth: a study of Telecom sector of Pakistan

Reverse Knowledge Transfer in Cross‐Border Mergers and Acquisitions in the Chinese High‐Tech Industry under Government Intervention

Inventory Management of Railway Logistics Park Based on Artificial Neural Network

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