Acqui-hiring or Acqui-quitting: Post-M&A Turnover Prediction via a Dual-fit Model

Gaining highly skilled human capital is one of the primary reasons for corporate mergers and acquisitions (M&A), especially for knowledge-intensive industries. However, the inevitable tensions brought by the divergent cultures and organizational misalignment during the M&A process result in high talent turnover rate and ultimately the integration failure. Hence, it is imperative to understand and prepare for the potential effects of M&A process on employee turnover. To this end, we propose a novel dual-fit model induced heterogeneous Graph Neural Network (GNN) model to predict the talent turnover trend in the post-M&A process, by taking into account the complex relationship among the acquirer firm, the acquiree firm, and the acquired employees. Specifically, we creatively design a dual-fit model comprised of both the firm-level compatibility and employee-firm fit. Extensive evaluations on large-scale real-world data clearly demonstrate the effectiveness of our approach

Evolution of Supply Chain Collaboration: Implications for the Role of Knowledge

Increasingly, research across many disciplines has recognized the shortcomings of the traditional “integration prescription” for inter-organizational knowledge management. This research conducts several simulation experiments to study the effects of different rates of product change, different demand environments, and different economies of scale on the level of integration between firms at different levels in the supply chain. The underlying paradigm shifts from a static, steady state view to a dynamic, complex adaptive systems and knowledge-based view of supply chain networks. Several research propositions are presented that use the role of knowledge in the supply chain to provide predictive power for how supply chain collaborations or integration should evolve. Suggestions and implications are suggested for managerial and research purposes

Comparative social capital: Networks of entrepreneurs and investors in China and Russia

Most studies on entrepreneurs’ networks incorporate social capital and networks as independent variables that affect entrepreneurs’ actions and its outcomes. By contrast, this article examines social capital of the Chinese and Russian entrepreneurs and venture capitalists as dependent variables, and it examines entrepreneurs’ social capital from the perspectives of institutional theory and cultural theory. The empirical data are composed of structured telephone interviews with 159 software entrepreneurs, and the data of 124 venture capital decisions in Beijing and Moscow. The study found that social networks of the Chinese entrepreneurs are smaller in size, denser in structure, and more homogeneous in composition compared to networks of the Russian entrepreneurs due to the institutional and cultural differences between the two countries. Furthermore, the study revealed that dyadic (two-person) ties are stronger and interpersonal trust is greater in China than in Russia. The research and practical implications are discussed.http://deepblue.lib.umich.edu/bitstream/2027.42/40169/3/wp783.pd

Initiating organizational memories using ontology network analysis

One of the important problems in organizational memories is their initial set-up. It is difficult to choose the right information to include in an organizational memory, and the right information is also a prerequisite for maximizing the uptake and relevance of the memory content. To tackle this problem, most developers adopt heavy-weight solutions and rely on a faithful continuous interaction with users to create and improve its content. In this paper, we explore the use of an automatic, light-weight solution, drawn from the underlying ingredients of an organizational memory: ontologies. We have developed an ontology-based network analysis method which we applied to tackle the problem of identifying communities of practice in an organization. We use ontology-based network analysis as a means to provide content automatically for the initial set up of an organizational memory

Is sexism a gender issue? A motivated social cognition perspective on men’s and women’s sexist attitudes toward own and other gender

The present research investigated the antecedents of ambivalent sexism (i.e., hostile and benevolent forms) in both men and women toward own and other gender. In two heterogeneous adult samples (Study 1: N = 179 and Study 2: N = 222), it as revealed that gender itself was only a minor predictor of sexist attitudes compared to the substantial impact of individual differences in general motivated cognition (i.e., Need for closure). Analyses further showed that the relationship between Need for closure and sexism was mediated by social attitudes (i.e., right-wing authoritarianism and social dominance orientation), which were differently related to benevolent and hostile forms of sexism. In the discussion it is argued that sexism primarily stems from individual differences in motivated cognitive style, which relates to peoples? perspective on the social world, rather than from group differences between men and women

Degeneracy: a link between evolvability, robustness and complexity in biological systems

A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology. This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability

A model for digital preservation repository risk relationships

The paper introduces the Preserved Object and Repository Risk Ontology (PORRO), a model that relates preservation functionality with associated risks and opportunities for their mitigation. Building on work undertaken in a range of EU and UK funded research projects (including the Digital Curation Centre , DigitalPreservationEurope and DELOS ), this ontology illustrates relationships between fundamental digital library goals and their parameters; associated rights and responsibilities; practical activities and resources involved in their accomplishment; and risks facing digital libraries and their collections. Its purpose is to facilitate a comprehensive understanding of risk causality and to illustrate opportunities for mitigation and avoidance. The ontology reflects evidence accumulated from a series of institutional audits and evaluations, including a specific subset of digital libraries in the DELOS project which led to the definition of a digital library preservation risk profile. Its applicability is intended to be widespread, and its coverage expected to evolve to reflect developments within the community. Attendees will gain an understanding of the model and learn how they can utilize this online resource to inform their own risk management activities