resource combination
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2021 ◽  
Vol 40 ◽  
pp. 100899
Author(s):  
Mingli Zhang ◽  
Lu Zhao ◽  
Yan Zhang ◽  
Yafei Liu ◽  
Nuan Luo

2015 ◽  
Vol 32 (1) ◽  
pp. 2-28 ◽  
Author(s):  
Rudolf R. Sinkovics ◽  
Noemi Sinkovics ◽  
Yong Kyu Lew ◽  
Mohd Haniff Jedin ◽  
Stefan Zagelmeyer

Purpose – The purpose of this paper is to examine operational-level implementation issues regarding mergers and acquisitions (M&As) in general, and resource combination and integration at the functional marketing level in particular. Design/methodology/approach – The paper introduces four factors (i.e. collaboration, interaction, marketing synergy, and the realignment of marketing resources) that support successful M&A marketing integration and enhance overall M&A performance. Findings – The results indicate that marketing synergy and the realignment of marketing resources contribute significantly to the extent of integration. At the same time, the authors find a significant but negative relationship between the interaction dimension and the speed of integration. Originality/value – The cultural integration of firms that feature different management styles and organizational cultures has been recognized as a particularly challenging aspect of cross-border M&As. This study explains factors that contribute to effective marketing integration in M&As.


2013 ◽  
Vol 464 ◽  
pp. 345-351 ◽  
Author(s):  
Han Zhang ◽  
Rui Feng Guo ◽  
Cong Geng

In this paper, a new mathematical combined model and the corresponding solution algorithm were proposed by analyzing the characteristics of services resource combination in cloud manufacturing. Aiming at avoiding problems of uncertainty, coarse-grained, diversity and dynamic in the process of services resource combination, a hierarchical model based on the hierarchical manufacturing implementation processes was firstly proposed. Then, quality of service (QoS) has been chosen to evaluate effects of services combination. Finally, a annealing algorithm was developed to solve the proposed model. Simulation experiment results prove the validity of the model and algorithm.


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