Integration modes, global networks, and knowledge diffusion in overseas M&As by emerging market firms

Purpose This paper aims to examine how integration modes impact the acquirer knowledge diffusion capacity of overseas mergers and acquisitions (M&As) effected by emerging market firms and the role played by the global innovation network position of the acquiring firms in affecting this relationship. Design/methodology/approach Through the use of structural equation modelling and bootstrap testing, the hypotheses are tested by drawing upon a sample of 102 overseas M&As effected by listed Chinese manufacturing companies. Findings The results show that acquirers from emerging countries are unable to increase the knowledge diffusion capacity unless they choose the right post-merger integration mode. This paper also finds that the relationship between integration mode and knowledge diffusion is channelled through the centrality and structural holes of acquirers in the global innovation networks. When considering the combinations of different resource similarities and complementarities of the acquired firms, differences emerge in the integration model and network embedded path of acquirers in emerging countries. Practical implications Emerging market multinational enterprises should consider post-merger integration as a crucial facilitator to the crafting of global innovation network positions that promote knowledge diffusion. The choices of integration mode and brand management autonomy should be matched with the resource similarities and complementarities that exist between the acquirer and target firms. Originality/value Based on the resource orchestration theory and by focussing on network centrality and structural hole as the crucial links, this study provides a nuanced understanding of the relationship between post-merger integration and knowledge diffusion and sheds light on latecomer firms from emerging countries

Investors\u27 Reactions to Alliance-Engendered Acquisition Ambiguity: Evidence from US Technology Deals

We study how, when target firms are engaged in strategic alliances, the ambiguity surrounding an acquisition\u27s anticipated synergies influences investors\u27 reactions to announcements of acquisitions. Drawing on behavioural finance research and the resource redeployment literature, we predict that investors\u27 limited access to the information encoded in the target firms\u27 alliances and the uncertainty around the re-deployability of their embedded resources generate a negative relationship between the number of target alliances and investors\u27 reactions. We also hypothesize that this negative effect is exacerbated when the alliances involve foreign alliance partners but is attenuated when acquirers are experienced in acquiring targets with alliances. Analysis of a large sample of US technology acquisitions supports all our hypotheses. We contribute to management research by offering a viable explanation of investors\u27 reactions to the announcement of major corporate events, such as acquisitions, whose structural characteristics deny investors material information about these events\u27 potential to create value

Sensitivity analysis of agent-based models: a new protocol

Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such critiques, we propose a systematic approach to conducting sensitivity analyses of ABMs. Our approach deals with a feature that can complicate sensitivity analyses: most ABMs include important non-parametric elements, while most sensitivity analysis methods are designed for parametric elements only. The approach moves from charting out the elements of an ABM through identifying the goal of the sensitivity analysis to specifying a method for the analysis. We focus on four common goals of sensitivity analysis: determining whether results are robust, which elements have the greatest impact on outcomes, how elements interact to shape outcomes, and which direction outcomes move when elements change. For the first three goals, we suggest a combination of randomized finite change indices calculation through a factorial design. For direction of change, we propose a modification of individual conditional expectation (ICE) plots to account for the stochastic nature of the ABM response. We illustrate our approach using the Garbage Can Model, a classic ABM that examines how organizations make decisions

Sensitivity analysis of agent-based models: a new protocol

Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such critiques, we propose a systematic approach to conducting sensitivity analyses of ABMs. Our approach deals with a feature that can complicate sensitivity analyses: most ABMs include important non-parametric elements, while most sensitivity analysis methods are designed for parametric elements only. The approach moves from charting out the elements of an ABM through identifying the goal of the sensitivity analysis to specifying a method for the analysis. We focus on four common goals of sensitivity analysis: determining whether results are robust, which elements have the greatest impact on outcomes, how elements interact to shape outcomes, and which direction outcomes move when elements change. For the first three goals, we suggest a combination of randomized finite change indices calculation through a factorial design. For direction of change, we propose a modification of individual conditional expectation (ICE) plots to account for the stochastic nature of the ABM response. We illustrate our approach using the Garbage Can Model, a classic ABM that examines how organizations make decisions

Optimal structure patterns for resilient corporate networks

Corporate networks are sets of companies maintaining formal relations between them in the form of contracts (INSEE, 2016). This type of network is generally affected when unexpected events happen, such as financial crises or other disasters. The notion of corporate network resilience appears, and it is a field increasingly studied. This resilience is defined as the ability to adjust the activity of the system to retain its basic functionality when errors, failures, and environmental changes occur (Gao, Barzet & Barabási, 2016). It is critical for firms that are members of these corporate network to increase their resilience and get prepared for future unexpected events. Otherwise, being unprepared could lead to bankruptcy. We have seen in the past years the consequences of financial crashes on companies. The resilience of a firm in a corporate network is impacted by different elements such as the properties of the network, the size, and the structure. In this thesis, we focus on the impact of the structure of the network of a company on its resilience. We propose a way to analyze empirical data, in order to find the most resilient structure for different problems. We illustrate our methodology with a case study of a network of companies in the oil-gas industry and provide advices to obtain a resilient structure for a company to survive against downturns, economical or technological

Customer knowledge sharing in cross-border mergers and acquisitions: The role of customer motivation and promise management

Knowledge is a vital source of competitive advantage and renewal for contemporary organizations. However, to date, few studies have scrutinized how mergers and acquisitions (M&As)—processes dependent on knowledge sharing—offer a valuable inter-organizational context through which to understand the attainment of customer knowledge sharing following M&As. Applying an integrated theoretical perspective from customer relationship management and M&A performance research, we study a Chinese–Finnish acquisition and customer firms of the acquired party across four advanced Western countries. We find that customer knowledge sharing is an active relationship management process that relies on the factors of customer dedication-based motivation vs. customer concerns about M&As to maintain relationships after acquisitions. In addition, and more importantly, we find that the promise management mechanisms—making promises, enabling promises, and keeping promises—of the M&A parties reinforce the motivational factors to maintain customer knowledge sharing in cross-border M&As. We propose a conceptual framework of customer knowledge sharing in cross-border M&As.</p