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M&A success and synergies are regularly discussed in the practical literature, but synergies are typically treated as a static concept (how do you get them?) with little discussion of financial bet acquirers create in paying an up-front premium. We describe the importance of investor reactions, the nature of the challenge, and discuss synergies as a process with five rules of the road covering M&A strategy, diligence, culture, leakage, and validation and reporting. Potential acquirers must be better prepared before they commit these major capital investments, involving multiple stakeholders throughout the process of creating the value they are promising with M&A.

We report the important results of our 24-year study on acquirer performance, the persistence of investor reactions, and the role of the acquisition premium to support our position that synergies must be trackable and defendable before and after deal announcement. From our collective author experience of advising on many hundreds of synergy programs over the years, we distilled our experience based on the common lack of understanding of what is required by executives, and when, and what we have seen greatly improve the odds of success in achieving sufficient M&A synergies.

Major findings include: 1. Initial market reactions are good predictors of the future, most deals persist, positive or negative, and there is a big spread of returns between winners and losers with losers paying the highest premiums; 2. Premiums additions to target’s growth value and may require larger performance increases than acquirers expect; 3. Synergies are a dynamic process involving multiple stakeholders from becoming a prepared acquirer in M&A strategy, building an early synergy roadmap during diligence, understanding that culture and change issues launch at announcement and preparation must begin long before, anticipating leakage, and validating and reporting post-close.

Our study is original covering three waves of mergers over 24 years; we formalize the synergy challenge created by paying a premium with respect to the already existing growth expectations for the target; we make clear that ultimately validating synergies begins with M&A strategy and diligence through to the workings of an Integration Management Office, anticipating synergy leakage, and preparing employees for change.

Selecting and scheduling optimal project portfolio simultaneously is a complex decision-making problem faced by organizations to realize the strategy. However, dynamic synergy relationships among projects complicate this problem. This study aims at constructing a project portfolio selection and scheduling (PPSS) model while quantifying the dynamic synergetic effects to provide decision support for managing PPSS problems.

This study develops a mathematical model for PPSS with the objective of maximal project portfolio benefits (PPBs). To make the results align with the strategy, comprehensive PPBs are divided into financial and non-financial aspects based on the balanced scorecard. Then, synergy benefits evolve dynamically in the time horizon, and system dynamics is employed to quantify them. Lastly, a case example is conducted to verify the applicability of the proposed model.

The proposed model is an applicable model for PPSS while incorporating dynamic synergy. It can help project managers obtain the results that which project should be selected and when it should start while achieving optimal PPBs.

This study complements prior PPSS research in two aspects. First, financial and non-financial PPBs are designed as new criteria for PPSS, making the results follow the strategy. Second, this study illuminates the dynamic characteristic of synergy and quantifies the synergetic effect. The proposed model provides insights into managing a PPSS effectively.

While previous operations management literature acknowledges the positive influence of Lean and Industry (I4.0) on performance, recent studies examining the synergy between these two factors have produced inconsistent and contradictory results. Therefore, this study aims to provide a comprehensive understanding of the effect of Lean and I4.0 synergy on firm performance.

This study utilised a meta-analysis approach, examining 23 empirical studies exploring multiple effects of the Lean and I4.0 synergy on firm performance. Multiple subgroup analyses were conducted to assess the contradictory outcomes and identify in what conditions such synergy may achieve performance.

The results affirm the prevailing positivist perspective among most scholars regarding the positive influence of the Lean and I4.0 synergy on firm performance. However, the overall effect size derived from the studies indicates a weak relationship, suggesting that this synergy alone is not the sole determinant factor of firm performance. In addition, the subgroup analyses reveal the presence of contingent conditions that may affect the performance outcomes when integrating Lean and I4.0, as most effects exhibit a weak relationship.

This study represents the first meta-analysis investigating the relationship between the Lean and I4.0 synergy on firm performance. By shedding light on the contradictory effects often depicted in the operations management literature, this study provides a critical reflection for researchers who tend to adopt an overly optimistic view of such synergy.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

This paper aims to address the question: What is the distribution of value (in pounds) created in a sample of domestic takeovers in the United Kingdom from 2013 to 2020 among acquirer and target stockholders?

The author employs a traditional event study methodology to calculate the percentage excess returns of companies on the announcement date. These returns are then converted into pound-denominated excess returns using the companies' market capitalizations. This allows the author to estimate the synergies of the mergers and acquisitions (M&As) and how they are allocated between acquirers and targets. This innovative transformation from percentage to pound excess returns establishes a new ratio methodology for addressing the paper's objective.

This paper reveals that in UK takeovers, 40 percent of the synergies in pounds are allocated to the stockholders of acquiring companies, while 60 percent go to the stockholders of target companies. In other words, acquirers retain a significant portion—more than half—of the synergies generated in these domestic deals. This original finding is statistically significant at the one percent level and strongly contradicts the hypothesis that acquirers, at best, merely break even.

The evidence that UK takeovers distribute value gains nearly equally between domestic deal parties challenges the enduring conventional insight in the M&A literature. This conventional wisdom suggests that the value created by business combinations is entirely distributed to target company stockholders. Consequently, this reexamination may have broader implications, offering an alternative perspective on the motives behind business combinations. This perspective differs from the “managerial hubris hypothesis,” which aligns with the prevailing conventional insight but receives limited support in the original finding reported here.

Promoting technological innovation is important to address the complexity of major engineering challenges. Technological innovations include short-term innovations at the project level and long-term innovations that can enhance competitive advantages. The purpose of this study is to develop an incentive mechanism for the public sector that considers short-term and long-term efforts from the private sector, aiming to promote technological innovation in major engineering projects.

This study constructs an incentive model considering the differences in short-term and long-term innovation efforts from the private sector. This model emphasizes the spillover effect of long-term efforts on current projects and the cost synergy effect between short-term and long-term efforts. It also explores the factors influencing the optimal incentive strategies for the public sector and innovation strategies for the private sector.

The results indicate that increasing the output coefficient of short-term and long-term efforts and reducing the cost coefficient not only enhance the innovation efforts of the private sector but also prompt the public sector to increase the incentive coefficient. The spillover effect of long-term innovation efforts and the synergy effect of the two efforts are positively related to the incentive coefficient for the public sector.

This research addresses the existing gap in understanding how the public sector should devise incentive mechanisms for technological innovation when contractors acting as the private sector are responsible for construction within a public-private partnership (PPP) model. In constructing the incentive mechanism model, this study incorporates the private sector's short-term efforts at the project level and their long-term efforts for sustained corporate development, thus adding considerable practical significance.

Research on strategic alliances is concerned with two issues: continuation and reconfiguration. Building on prior research that examines the two issues separately, the paper studies them simultaneously. This paper aims to investigate how strategic alliances may exert the synergetic effect between dynamics and stability as well as to discuss the dynamic evolution process and influence factors of strategic alliances.

This paper describes the construction of a two-party evolutionary game model of alliance and partners. The model is used to analyze the evolution process of synergetic mechanism to determine when to terminate and when to continue with a partnership. Further, numerical simulation is used to quantify the results and to gain insight into the effects of various factors on the dynamic evolution of the synergetic mechanism.

This paper reveals several synergetic states of dynamics and stability in the alliances. The results show that synergy states are positively affected by the collaborative innovation benefits, alliance management capability, the intensity of intellectual property protection, liquidated damages and reputation losses, and negatively affected by the absorptive capacity of partners.

The study helps the alliance to achieve long-term development as well as to balance the paradoxical relationship. The results suggest that managers of strategic alliances should focus on building strong and long-term relationships in order to achieve high performance innovations. Managers should also pay close attention to their partners’ behaviors in previous alliances.

This paper provides new insights into the paradoxical relationship in alliance by revealing the evolution of synergetic mechanism between dynamics and stability. The results remind alliances to understand the relationship between dynamics and stability and to notice the influence factors of synergistic effects when they are making decisions.

The manufacturing industry and the producer service industry have a high degree of industrial correlation, and their integration will cause changes in the complex industrial network topology, which is an important reason for the synergistic effect. This paper describes the topology of industrial systems using complex network theory; further, it discusses how to identify the criticality and importance of industrial nodes, and whether node characteristics cause synergistic effects.

Based on the input-output data of China in 2007, 2012 and 2017, this paper constructs the industrial complex network of 30 Chinese provinces and cities, and measures the regional network characteristics of the manufacturing industry. The fixed-effect panel regression model is adopted to test the influence of agglomeration degree and centrality on synergies, and its adjustment mechanism is explored.

The degree of network agglomeration in the manufacturing industry exerts a negative impact on the synergistic effect, while the centrality of the network exerts a significant promoting effect on the synergistic effect. The results of adjustment mechanism test show that enhancing the autonomous controllable ability of the regional industrial chain in the manufacturing industry can effectively reduce the effect of network characteristics on the synergistic effect.

Based on input-output technology, this paper constructs a complex industrial network model, however, only basic flow data are used. Considerable in-depth and detailed research on the economic and technological connections within the industry should be conducted in the future. The selection of the evaluation index of the importance of industrial nodes also needs to be further considered. For historical reasons, it is also difficult to obtain and process data when carrying out quantitative analysis; therefore, it is necessary to make further attempts from the data source and the expression form of evaluation indicators.

In a practical sense this has certain reference value for the formulation of manufacturing industrial policies the optimization of regional industrial layout and the improvement of the industrial development level. It is necessary to formulate targeted and specialized industrial development strategies according to the characteristics of the manufacturing industry appropriately regulate the autonomous controllable ability of the industrial chain and avoid to limit the development of industries which is in turn limited by regional resources. Industry competition and market congestion need to be reduced industry exchanges outside the region encouraged the industrial layout optimized and the construction of a modern industrial system accelerated.

The above research results hold certain reference importance for policy formulation related to the manufacturing industry, regional industrial layout optimization and industrial development level improvement. Targeted specialized industrial development strategies need to be formulated according to the characteristics of the manufacturing industry; the autonomous controllability of the industrial chain needs to be appropriately regulated; limitation of regional resources needs to be avoided as this restricts industrial development; and industry competition and market congestion need to be reduced. Agglomeration of production factors and optimization of resource allocation is an important part of a beneficial regional economic development strategy, and it is also an inevitable choice for industrialization to develop to a certain stage under the condition of a market economy. In alignment with the research conclusions, effective suggestions can be put forward for the current major industrial policies. In the process of promoting the development of the manufacturing industry, it is necessary for regional governments to carry out unified planning and guidance on the spatial layout of each manufacturing subsector. Regional governments need to effectively allocate inter-industry resources, better share economies of scale, constantly enhance the competitive advantages and competitiveness of development zones and new districts and promote the coordinated agglomeration and development of related industries with input industries. Industrial exchanges outside the region should be encouraged, the industrial layout should be optimized and the construction of a modern industrial system should be accelerated.

Complex network theory is introduced to study the industrial synergy effect. A complex industrial network of China's 30 regions is built and key network nodes are measured. Based on the dimensionality of the “industrial node – industrial chain – industrial complex network”, the research path of industrial complex networks is improved.

The construction industry sector is developing rapidly, especially with the increasing pace of the Fourth Industrial Revolution in this sector. Construction projects can benefit from greater integration and collaboration between their technologies and processes to reap the advantages and keep pace with the recent significant technological and managerial techniques developments. Therefore, this study aims to delve into and investigate building information modeling (BIM) and Lean Construction (L.C.) with a concentration on the potential BIM–lean interactions synergy and integration in the Jordanian construction industry.

This study takes exploratory nature, followed by the deductive research approach, and is designed to be a mono-quantitative research methodology. Moreover, the sampling technique is non-probability convenience sampling, and the research strategy is implemented through a questionnaire used and analyzed by using Statistical Package for Social Science to conduct descriptive and inferential statistical analysis and verify the reliability and validity through proper tests.

The BIM–lean interactions synergy and integration findings revealed that eliminating waste (time, cost, resources), promoting continuous improvement (Kaizen) and standardizing as lean construction principles are the most significant and agreeable toward achieving BIM–lean interactions synergy. On the other hand, “High 3D Visualization Modelling” was the most significant BIM function, followed by “Rapid and Auto-Generation of Documents and Multiple Design Alternatives” and “Maintenance of Information and Design Model Integrity.” Moreover, based on the relative importance index (RII) values, “Lack of Technical Expertise in BIM-LEAN” is the most significant challenge with a 0.89 value of RII, followed by “Lack of Government Direction and Standard Guidelines” with a 0.88 value of RII and “Financial considerations” with a 0.83 value of RII.

This study will help provide a new detailed overview that investigates the effects and expected benefits of integrating BIM processes and technological functionalities with lean construction principles within a synergetic environment. Moreover, the study will increase the awareness of using new technologies and management approaches in the architectural, engineering and construction industry, seeking to achieve integration between these technologies to reach ideal results in terms of the outputs of construction operations.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.