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This study aims to systematically review strategy making in the seaport context during a period of hyper uncertainty.

A systematic review using the context, intervention, method and outcome (CIMO) framework is conducted in the domains of strategy making and the port sector taking account of hyper uncertainty caused by Brexit.

Strategy making (under conditions of hyper uncertainty) is shown to evolve from both stakeholder/supply chain embedded relationships and from chief executive officer and extra organisational inputs. Through an iterative process of internal resourcing, stakeholder engagement strategy development can be seen to impact five key outcomes of an emerging strategy making under hyper uncertainty: economic returns; societal and regional impacts; deeper improved market engagement; improved environmental sensing and potential for dynamic capability development.

The systematic review integrates the existing fragmented research landscape regarding strategy making under hyper uncertainty, provides future research trajectories and develops a framework emerging from the review.

The framework offers port management and policymakers a tool to improve their engagement with strategy making under hyper uncertainty and associated outcomes.

The systematic review consolidates the fragmented literature and presents future research trajectories. The framework of strategy making under hyper uncertainty developed from the CIMO framework develops existing knowledge and contributes to academic theory.

The purpose of this paper is to explore uncertainty-coping strategic actions in the internationalisation strategy of entrepreneurial ventures, encompassing born globals/international new ventures, enduring established internationalisers, old born globals, born-again globals and micro-multinationals.

The authors developed a qualitative exploratory study applying a grounded theory approach to ten entrepreneurial firms to investigate the strategies they adopted to cope with Knightian uncertainty in international markets.

The global niche strategy emerged as a successful path to deal with uncertainty in smaller firms’ internationalisation. The authors uncover the components of this strategy, namely the creation of markets, the focus on global clients and the control of technology.

The contribution of this paper consists in exploring how entrepreneurial firms cope with uncertainty through a global niche strategy and in outlining its main components. The authors develop a model of smaller entrepreneurial firms’ international strategising under this perspective. The research thus links together international marketing and strategy with (international) entrepreneurship studies.

The application of real options theory to international strategy has surged in recent years. However, it is still a relatively new and loosely defined field, and there are several constraints on practical applications of this powerful theory. To move forward this field, the paper first provides a systematic analysis of theoretical and empirical contributions of real options theory to three critical issues in international strategy: (1) valuing multinational networks, (2) assessing market entry modes, and (3) evaluating market entry timing. The paper further suggests that future studies can focus on a refined treatment of uncertainty and the development of a dynamic theory in international strategy. Five testable propositions are developed in these directions.

While uncertainty has always been a feature of the healthcare environment, its pace and scope are rapidly increasing, fueled by myriad factors such as technological advancements, the threat and frequency of disruptive events, global economic developments, and increasing complexity. Contemporary healthcare organizations thus persistently face what is known as “deep uncertainty,” which obscures their ability to predict outcomes of strategic action and decision-making, presenting them with novel challenges and threatening their survival. Persistent, deep uncertainty challenges us to revisit and reconsider how we think about uncertainty and the strategic actions needed by organizations to thrive under these circumstances. Simply put, how can healthcare organizations thrive in the face of deeply uncertain environments? We argue that healthcare organizations need to employ both adaptive and creative strategic approaches in order to effectively meet patients' needs and capture value in the long-term future. The chapter concludes by offering two ways organizations can build the dynamic capabilities needed to employ such approaches.

Multiple stages of procurement for a product in a supply chain (SC) altogether form a “multi-Tier” supply network. The purpose of this paper is to develop and verify a systematic solution approach to ascertain the realistic cost advantage of a coordinated centralized sourcing strategy as compared to an isolated decentralized sourcing strategy for a multi-tier supply network under demand uncertainty.

The proposed systematic solution approach consists of seven steps to compare and contrast the cost advantage of a centralized coordinated sourcing strategy over a decentralized stage-wise sourcing strategy for a multi-tier supply network. A real-life automotive industry case analysis of two distinct products provides sufficient empirical evidence on the expected cost advantage of centralized coordinated sourcing strategy under demand uncertainty.

The case analysis affirms the practicability of the proposed seven-step solution approach to determine the realistic cost advantage of coordinated sourcing.

The scope of this research is restricted to a single product and two-tier supply network analysis. This research work also considers a restrictive assumption of negligible coordination cost.

The suitability of the proposed solution approach is verified using real-life case examples. This research provides theoretical insights and factual evidence to SC practitioners, so as to adopt a centralized sourcing strategy in a varied manufacturing environment.

There is no evidence of a systematic step-by-step solution approach to determine the cost advantage of a coordinated sourcing strategy over an isolated decentralized sourcing strategy for a multi-tier supply network under demand uncertainty.

The effectiveness of alternative buffering strategies in complex multilevel assembly manufacturing systems using the Material Requirement Planning (MRP) methodology is explored and assessed. The safety stock, safety lead time, “hard” safety capacity, and forecast inflation buffering strategies are tested under uncertainties of end‐item demand, resource supply, and task control. The MRP methodology is applied for scheduling along with a complex, realistic simulation model for execution of operations. Average inventory levels for end and component items, capacity utilisation, end‐item backorders and customer undersupport are used as performance measures. Experimental results establish safety stock and “hard” safety capacity as dominant buffering strategies under all uncertainty conditions, and task control is shown as the most disruptive uncertainty source.

The objective of this paper is to illustrate and examine the different flexibility strategies adopted by supply chain participants as a result of different environmental uncertainties.

An exploratory multi‐case study, involving five Chinese companies in the textile and apparel industry, was conducted.

The analysis, based on the supply chain literature, reveals that the unpredictable dynamics of the supply chain can arise from a variety of internal and external sources, including suppliers, operating systems, customers, and competitors. In response to the various environmental uncertainties and risks in the supply chain, four types of flexibility strategy are identified in our case analysis: laggard, conservative, agile, and aggressive. The results also suggest that the adoption of flexibility strategies should match a firm's business environment and that better supply chain responsiveness can be achieved in two ways: by reducing uncertainties and by improving supply chain flexibility.

The key limitation of the study is that it focuses solely on the textiles and clothing industry, which makes it difficult to generalize the results to other industries. Another difficulty arises from the subjective criteria employed in some constructs, such as the perceived aggressiveness of competition, the predictability of customer demand, and the designations of companies in the proposed strategy categories.

The proposed theoretical framework can assist managers in properly diagnosing and deploying supply chain flexibility strategies. The actions identified for promoting supply chain flexibility can also be used to assess the various options for exploiting or acquiring flexibility strategies.

Expanding on the previous research approach of examining flexibility strategies from the perspective of a single firm, this study draws on the multi‐case approach to posit a series of propositions that link the adoption of specific supply chain flexibility strategies to various environmental conditions in a supply chain context and proposes a conceptual framework to illustrate how supply chain responsiveness can be improved in today's volatile market environment.

The purpose of this paper is to explain why the high quality cassava flour (HQCF) value chain in Nigeria has not performed as well as expected. The specific objectives are to: analyse important sources of uncertainty influencing HQCF value chains; explore stakeholders’ strategies to respond to uncertainty; and highlight the implications of different adaptation strategies for equity and the environment in the development of the value chain.

The authors used a conceptual framework based on complex adaptive systems to analyse the slow development of the value chain for HQCF in Nigeria, with a specific focus on how key stakeholders have adapted to uncertainty. The paper is based on information from secondary sources and grey literature. In particular, the authors have drawn heavily on project documents of the Cassava: Adding Value for Africa project (2008 to present), which is funded by the Bill & Melinda Gates Foundation, and on the authors’ experience with this project.

Policy changes; demand and supply of HQCF; availability and price of cassava roots; supply and cost of energy are major sources of uncertainty in the chain. Researchers and government have shaped the chain through technology development and policy initiatives. Farmers adapted by selling cassava to rival chains, while processors adapted by switching to rival cassava products, reducing energy costs and vertical integration. However, with uncertainties in HQCF supply, the milling industry has reserved the right to play. Vertical integration offers millers a potential solution to uncertainty in HQCF supply, but raises questions about social and environmental outcomes in the chain.

The use of the framework of complex adaptive systems helped to explain the development of the HQCF value chain in Nigeria. The authors identified sources of uncertainty that have been pivotal in restricting value chain development, including changes in policy environment, the demand for and supply of HQCF, the availability and price of cassava roots, and the availability and cost of energy for flour processing. Value chain actors have responded to these uncertainties in different ways. Analysing these responses in terms of adaptation provides useful insights into why the value chain for HQCF in Nigeria has been so slow to develop.

Recent developments suggest that the most effective strategy for the milling industry to reduce uncertainty in the HQCF value chain is through vertical integration, producing their own cassava roots and flour. This raises concerns about equity. Until now, it has been assumed that the development of the value chain for HQCF can combine both growth and equity objectives. The validity of this assumption now seems to be open to question. The extent to which these developments of HQCF value chains can combine economic growth, equity and environmental objectives, as set out in the sustainable development goals, is an open question.

The originality lies in the analysis of the development of HQCF value chains in Nigeria through the lens of complex adaptive systems, with a particular focus on uncertainty and adaptation. In order to explore adaptation, the authors employ Courtney et al.’s (1997) conceptualization of business strategy under conditions of uncertainty. They argue that organisations can assume three strategic postures in response to uncertainty and three types of actions to implement that strategy. This combination of frameworks provides a fresh means of understanding the importance of uncertainty and different actors’ strategies in the development of value chains in a developing country context.

A probabilistic non-dominated sorting genetic algorithm (P-NSGA) for multi-objective optimization under uncertainty is presented. The purpose of this algorithm is to create a tight coupling between the optimization and uncertainty procedures, use all of the possible probabilistic information to drive the optimizer, and leverage high-performance parallel computing.

This algorithm is a generalization of a classical genetic algorithm for multi-objective optimization (NSGA-II) by Deb et al. The proposed algorithm relies on the use of all possible information in the probabilistic domain summarized by the cumulative distribution functions (CDFs) of the objective functions. Several analytic test functions are used to benchmark this algorithm, but only the results of the Fonseca-Fleming test function are shown. An industrial application is presented to show that P-NSGA can be used for multi-objective shape optimization of a Formula 1 tire brake duct, taking into account the geometrical uncertainties associated with the rotating rubber tire and uncertain inflow conditions.

This algorithm is shown to have deterministic consistency (i.e. it turns back to the original NSGA-II) when the objective functions are deterministic. When the quality of the CDF is increased (either using more points or higher fidelity resolution), the convergence behavior improves. Since all the information regarding uncertainty quantification is preserved, all the different types of Pareto fronts that exist in the probabilistic framework (e.g. mean value Pareto, mean value penalty Pareto, etc.) are shown to be generated a posteriori. An adaptive sampling approach and parallel computing (in both the uncertainty and optimization algorithms) are shown to have several fold speed-up in selecting optimal solutions under uncertainty.

There are no existing algorithms that use the full probabilistic distribution to guide the optimizer. The method presented herein bases its sorting on real function evaluations, not merely measures (i.e. mean of the probabilistic distribution) that potentially do not exist.

Although there is a growing research stream on Performance Measurement and Management Systems (PMMS) in Ecosystems literature, current research offers limited theoretical insights into how PMMS deal with two types of strategies in uncertain ecosystems: ecosystem-based strategy – EBS (at the focal firm level) and ecosystem strategy – ES (at the ecosystem level). This study aims at identifying how PMMS are employed to deal with different types of strategies in uncertain ecosystems.

The authors employed an inductive, rich multiple case approach in five focal firms with platform ecosystems. Data collection involved multiple sources of information (primary and secondary data), combing retrospective and longitudinal perspectives. Data analysis combined replication and comparison logic with coding.

This study identifies four major distinctive dimensions of Ecosystem PMMS under uncertainty: (1) Integrative Performance (considering the different ecosystem actors’ performance), (2) Interdependence Performance (mutual, yet not necessarily convergent amongst ecosystem partners), (3) Regulative Performance (paradoxical in nature, having to cope with both flexibility and stability) and finally (4) Phased Learning Performance (non-linear).

Our primary contribution is a new framework for PMMS literature: a performance measurement and management system for dealing with strategies in ecosystems. This framework enables managing performance regarding both types of strategies (EBS and ES) and their interplay in uncertain ecosystems.

The ecosystem management requires focal firms to measure and manage the overall ecosystem’s performance, and it varies according to the type of strategy adopted in each case. Our framework provides dimensions that guide firms to build and implement PMMS for an ecosystem consistent with the ES. Therefore, it may improve performance, especially in uncertain business contexts.

The findings enrich PMMS literature in an ecosystem context related to the ES in uncertain environments.