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The purpose of this paper and its companion (Part I: single and two‐component supply chains) is to investigate methods to tackle complexities, constraints (including time‐varying constraints) and other challenges. In this part, attention is devoted to multi‐silo supply chain and the relationships between the components. The first part of the paper aims to consider two types of experimental supply chains: with one‐to‐many and many‐to‐one relationships. The second half of the paper aims to present two approaches on optimising the material flow in the real‐world supply chain network.

Cooperative coevolutionary and classical sequential approaches are taken to address the experimental multi‐silo supply chains. Due to the nature and the complexity of the supply chain presented in the second half of the paper, evolutionary algorithm was not sufficient to tackle the problem. A fuzzy‐evolutionary algorithm is proposed to address the problem.

The proposed systems produce solutions better than solutions proposed by human experts and in much shorter time.

The paper discusses various algorithms to provide the decision support for the real‐world problems. The system proposed for the real‐world supply chain is in the process of integration to the production environment.

This chapter addresses adaptation to dynamic, novel and uncertain military environments. These environments require a shift from a maneuver warfare paradigm to an asymmetric world where shifting alliances, questionable civilian loyalties, opaque cultures, and the requirement to maintain peace one day and combat the next makes for a particularly confusing situation. This new warfare paradigm requires adaptation to an uncertain, complex environment.

The initial section discusses a general cognitive model of visualization called RAVENS and its importance for adaptation developed specifically to address complex military environments. RAVENS posits that humans are inherently flexible decision makers and situation awareness depends on the ability of humans to create narrative visualizations that capture the overall context of complex military environments. Using the framework as a guideline, we will examine two important visualization research programs whose purpose is to allow military operators to rapidly adapt to volatile situations. The first program investigates cognitive effects such as the framing bias and their possible interactions with a variety of display concepts during a series of missile defense simulations. The experimenters presented risk as a spatial representation of uncertainty and target value that emphasized either expected population lost or expected population saved. The second program investigated the feasibility of using visualizations generated from Scheherazade (a coevolutionary algorithm) to aid MI analysts in predicting emergent tactics of terrorist groups during urban operations. Finally, we discuss the value of these approaches for providing coherent narrative understanding as called for in the RAVENS model.

In regarding to operational efficiency and safety improvements, multiple tower crane service scheduling problem is one of the main problems related to tower crane operation but receives limited attention. The current work presents an optimization model for scheduling multiple tower cranes' service with overlapping areas while achieving collision-free between cranes.

The cooperative coevolutionary genetic algorithm (CCGA) was proposed to solve this model. Considering the possible types of cross-tasks, through effectively allocating overlapping area tasks to each crane and then prioritizing the assigned tasks for each crane, the makespan of tower cranes was minimized and the crane collision avoidance was achieved by only allowing one crane entering the overlapping area at one time. A case study of the mega project Daxing International Airport has been investigated to evaluate the performance of the proposed algorithm.

The computational results showed that the CCGA algorithm outperforms two compared algorithms in terms of the optimal makespan and the CPU time. Also, the convergence of CCGA was discussed and compared, which was better than that of traditional genetic algorithm (TGA) for small-sized set (50 tasks) and was almost the same as TGA for large-sized sets.

This paper can provide new perspectives on multiple tower crane service sequencing problem. The proposed model and algorithm can be applied directly to enhance the operational efficiency of tower cranes on construction site.

The purpose of the paper is to examine the coevolutionary dynamics between multistage overseas mergers and acquisitions (M&A) integration and knowledge network reconfiguration and the impact of this coevolution on industrial technology innovation.

This paper builds a coevolution analysis framework in stages and constructs structural equation models for empirical tests using the Chinese technology-sourcing overseas M&A events that occurred from 2001 to 2012.

Overseas M&A integration and knowledge network reconfiguration are in a coevolutionary relationship, driving industrial technology innovation. The acquirer adopts initial integration degree that matches the resource relatedness between the acquiring and acquired parties, promoting initial industrial technology innovation through initial knowledge network reconfiguration. Initial knowledge network reconfiguration will feed back to the M&A integration decision in the mid-to-late stage through increasing knowledge similarity and narrowing network position difference. The higher the improvement of mid-to-late integration degree, the more it can drive mid-to-late industrial technology innovation through mid-to-late knowledge network reconfiguration.

Future research can accurately classify overseas M&A integration stages through case tracking and explore other network attributes.

Practical guidelines are provided for managers on how to implement a multistage overseas M&A integration strategy, optimize knowledge network reconfiguration and promote industrial technology innovation. Significant practical implications are presented, especially in academia, society and quality of life.

Different from the previous research considering M&A integration as a single-stage decision, this paper emphasizes the dynamics of the M&A integration process and explores the coevolution mechanism of multistage overseas M&A integration and knowledge network reconfiguration.

Post-merger integration (PMI) is driven by coevolving processes. This paper examines the coevolution of dynamic integration strategy and network reconstruction and explores how these processes systematically enable emerging market acquirers to upgrade innovation capabilities.

This paper conducts a multi-case study based on four Chinese overseas acquisitions of manufacturing firms. The data were collected from interviews and archival documentation.

This study develops a coevolutionary framework of dynamic integration strategy and network reconstruction to explain processes and mechanisms of an acquirer’s innovation capability upgrading. This framework identifies three network motivations, namely, network access, network connection and network synergy. Under different network motivations, dynamic transitions of the acquirer’s integration strategy coevolve with multi-level reconstruction of its networks. Collectively, they are important mechanisms driving innovation capability moves from imitation innovation to asportation and reimitation innovation and then to independent innovation.

This paper responds to a recent call for more insights into the dynamics of PMI and contributes to the research on emerging market multinational corporations’ post-acquisition integration. By integrating the M&A and networks literature, the paper provides evidence of unexplored mechanism of network changes during PMI. It reveals that how acquirers manage the dynamics of PMI to gradually achieve multi-level reconstruction of their networks. Based on a coevolutionary framework, the paper provides a process perspective on how the coevolution of PMI and network reconstruction promotes the upgrading of innovation capabilities.

The purpose of this paper is to convey how the transition to market-based orientations by state-owned enterprises (SOEs), particularly the military sector, represents a coevolutionary process between business and regulatory institutions that has an impact on both the military and civilian markets.

The authors conducted a longitudinal case study of a military SOE, the Aosheng Group, between 1951 and 2012 to understand the dynamics between institutions and organizations. A comparative analysis between the main stages of evolution was completed, and conclusions about the main patterns of organizational and institutional change were reached.

The study reports evidence on the coevolutionary nature of change in big SOEs in China, demonstrating how institutional changes are bigger drivers in promoting reorientations than are market pressures. Within the framework of punctuated equilibrium theory, the determining role that managers may play in leading and implementing organizational reorientations is emphasized.

A triangulated methodology was employed to analyse a long period; however, its application to just a single case might be questioned in terms of generalizing any of the findings.

The longitudinal perspective applied in this case study contributes to critical questioning as to how Chinese agencies define forms of control and the goals for SOEs under their jurisdiction and the importance of allowing managerial discretion to the assigned managers.

Behavior in organizations is predominantly driven by expectations and routines derived from past experience rather than by envisioned scenarios reflecting future potentialities. The disproportionate weight placed on expectations derived from past experience has been blamed for a variety of problems associated with individual and organizational creativity and change. Drucker addressed this long‐standing problem by arguing that decision makers must address the degree of “futurity” they need to factor into their present thinking and action. Specifically, decision makers must consider the relative weight or ratio given to ideas derived from two temporally distinct sources of knowledge – expectations constructed from remembering past experiences, and visions derived from imagining the future. In this paper I seek to describe how varying the priority given to remembering and imagining during enactment (action‐perception‐sensemaking) episodes affects organizational creativity and change.

The chapter discusses the effects of climate change on tourism development in Estonia, Latvia, and Lithuania by combining these countries into a single Eastern Baltic Sea Region. The chapter explores the current situation and investigates the trends that will affect the economic development if the present climate conditions are situated in historical context. The first part discusses how destinations can be better managed if they are informed by the scholarship on ecological modernization and updated by a coevolutionary approach to climate change. This discussion proceeds with an analysis of the impact climate change has on tourism following different scenarios of current and future climate conditions. The development of tourism in the Baltic countries is then assessed with references to sustainable development. Overall the chapter demonstrates how destinations can cope with the changing preferences of tourists even in the face of highly unpredictable climatic developments.

The purpose of this study is to deepen understanding of the effects of using social media technologies to acquire technological knowledge and organizational learning competences, of technological knowledge competences on organizational learning and finally of organizational learning on organizational performance.

The study was performed by analyzing data from a sample of 197 technology firms located in Spain. The hypotheses were tested using a structural equations model with the program LISREL 8.80.

This study’s conceptual framework is grounded in complexity theory – along with dynamic capabilities theory, which complements the resource-based view. The study contributes to the literature by proposing a model that reflects empirically how business ecosystems that use social media technologies enable the development of interorganizational and social collaboration networks that encourage learning and development of technological knowledge competences.

It would be interesting for future studies to consider other elements to conceptualize and measure social media technologies, including (among others) significance of the various tools used and strategic integration. The model might also analyze other sectors and another combination of variables.

The results of this study have several managerial implications: developing social media technologies and interorganizational social collaboration networks not only enables the organizational learning process but also encourages technological knowledge competences. Through innovation processes, use of social media technologies also contributes to strengthening companies’ strategic positioning, which ultimately helps to improve firms’ organizational performance.

Since social media technologies drive information systems in contemporary society (because they enable interaction with numerous agents), the authors highlight the use of complexity theory to develop a conceptual framework.

The study also deepens understanding of the connections by which new experiential learning contributes to the generation of coevolutionary adaptive business ecosystems and digital strategies that enable development of interorganizational and social collaborative networks through technological knowledge competences. Only after examining the impact of social media technologies on organizational performance in prior literature, did the authors underscore that both quantity and frequency of social media technology use are positively related to improvement in knowledge processes that lead to employees’ creation and acquisition of new metaknowledge.