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This paper aims to investigate the pass-through (PT) effect in Turkey by using quarterly data for the period 1998: Q1-2019: Q2 to understand the dynamic potential effects of exchange rates on domestic prices.

The paper launches several nonlinear models in which the basic determinants of domestic prices in Turkey are determined through Markov regime-switching models (MSMs). Hence, this research follows the variables of the consumer price index (CPI), USD exchange rate, gross domestic product (GDP; demand side of the economy), industrial production index (production side of the economy), economic uncertainty and geopolitical risk index for Turkey.

This work explores that the exchange rate and demand side of the economy (GDP) follow a positive nonlinear relationship with CPI at both regimes. The production side of the economy (IP) affects negatively the CPI during regime 0. Economic uncertainty influences the CPI positively at Regime 1, while geopolitical risk has a negative association with CPI at Regime 0. Eventually, the paper provides some policy proposals associated with the impacts of GDP, IP, economic uncertainty and geopolitical risk on CPI in Turkey.

One may claim that any PT model, which does not observe the possible structural or regime shifts in estimated parameters, might fail to estimate the coefficients unbiasedly and efficiently. Hence, this work differs from available relevant works in the literature since this paper considers linearity or nonlinearity important and reveals that the relevant PT model follows a nonlinear path rather than a linear path, this nonlinear path is converged strongly by MSMs and estimates the significant regime shifts in the constant term and, in parameters of independent variables of PT by MSMs.

Container shipping is a crucial component of the global supply chain that is affected by a large range of operational risks with high uncertainty, threatening the stability of service, manufacture, distribution and profitability of involved parties. However, quantitative risk analysis (QRA) of container shipping operational risk (CSOR) is being obstructed by the lack of a well-established theoretical structure to guide deeper research efforts. This paper proposes a methodological framework to strengthen the quality and reliability of CSOR analysis (CSORA).

Focusing on addressing uncertainties, the framework establishes a solid, overarching and updated basis for quantitative CSORA. The framework consists of clearly defined elements and processes, including knowledge establishing, information gathering, aggregating multiple sources of data (social/deliberative and mathematical/statistical), calculating risk and uncertainty level and presenting and interpreting quantified results. The framework is applied in a case study of three container shipping companies in Vietnam.

Various methodological contributions were rendered regarding CSOR characteristics, settings of analysis models, handling of uncertainties and result interpretation. The empirical study also generated valuable managerial implications regarding CSOR management policies.

This paper fills the gap of an updated framework for CSORA considering the recent advancements of container shipping operations and risk management. The framework can be used by both practitioners as a tool for CSORA and scholars as a test bench to facilitate the comparison and development of QRA models.

This book on uncertainty comprises the initial volume in a series titled “New Horizons in Managerial and Organizational Cognition”. We asked Frances Milliken and Gerard P. Hodgkinson, two well-known scholars who have made important contributions to our understanding of uncertainty to join us in this opening chapter to introduce this project. The brief bios found at the end of this volume cannot do justice to the broad range of their contributions, but our conversation gives a flavor of the kind of insights they have brought to managerial and organizational cognition (MOC). The editors thank them for helping launch the series with a decisive exploration of what defining uncertainty involves, how that might be done, why it is important, and how the task is changing. We were interested to discover that all five of us are currently involved in research that considers the nature and impact of uncertainty, and we hope that readers similarly find that paying attention to uncertainty contributes to their current projects. Working together, we can advance understanding of organizational settings and effective action, both for researchers and practitioners.

This article revisits some theories and concepts of public administration, including those related to public value, transaction costs and social equity, to analyze the advantages and disadvantages of using artificial intelligence (AI) algorithms in public service delivery. The author seeks to mobilize theory to guide AI-era public management practitioners and researchers.

The author uses an existing task classification model to mobilize and juxtapose public management theories against artificial intelligence potential impacts in public service delivery. Theories of social equity and transaction costs as well as some concepts such as red tape, efficiency and economy are used to argue that the discipline of public administration provides a foundation to ensure algorithms are used in a way that improves service delivery.

After presenting literature on the challenges and promises of using AI in public service, the study shows that while the adoption of algorithms in public service has benefits, some serious challenges still exist when looked at under the lenses of theory. Additionally, the author mobilizes the public administration concepts of agenda setting and coproduction and finds that designing AI-enabled public services should be centered on citizens who are not mere customers. As an implication for public management practice, this study shows that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

As a fast-growing subject, artificial intelligence research in public management is yet to empirically test some of the theories that the study presented.

The paper vulgarizes some theories of public administration which practitioners can consider in the design and implementation of AI-enabled public services. Additionally, the study shows practitioners that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

The paper informs a broad audience who might not be familiar with public administration theories and how those theories can be taken into consideration when adopting AI systems in service delivery.

This research is original, as, to the best of the author’s knowledge, no prior work has combined these concepts in analyzing AI in the public sector.

The purpose of the paper is 1) to address the importance of contingency at the right level when defining project control baseline, including cost reserves / “room to manoeuvre” and 2) present proactive uncertainty management as a regime to ensure cost effective management of project reserves and contribute to project success.

The paper is a combination of literature study and quantitative research on how contingency develops during the lifetime of a case project. The investigation into the case project includes document study into quantitative material from the case project. The combination of empirical material and theory makes the discussion robust.

Unrealistic low cost uncertainty will lead to unrealistic low contingency. The case study from a Norwegian mega project shows a contingency of 15 per cent in addition to expected costs. The case study shows that by continuous opportunity management and risk reduction, the needs for management reserves are systematically reduced and the contingency is controlled.

This research is limited to one case study. A higher number of cases are necessary to generalise the findings. However, the authors would claim that the systematic mapping of need for management reserve towards the project contingency, and a continuous uncertainty management system will help to obtain cost effective management. The findings from the case study could be applied on similar cases.

The case study shows a way of setting contingencies and managing contingencies through systematic uncertainty management.

Improved management of project provisions will increase the value of future projects.

This study aims to analyze the contagious effects of economic policy uncertainties in the USA on the economies of its important trading partners, such as Japan, Canada, Mexico and the Eurozone.

In the study using the uncertainty index created by Baker et al. (2016), the interaction between variables was analyzed with structural VAR (SVAR) models.

According to the results obtained from the analysis, economic policy uncertainties in the USA had significant effects on the economies of its high-volume trading partners. The internal debt crisis experienced in the Eurozone after the 2008 crisis caused the European Central Bank to respond to the economic policy uncertainties in the USA with contractionary monetary policies, unlike other countries. In addition to these results, Mexico, which has a more fragile economic structure than other countries in the analysis, was more impacted by increasing uncertainties, as expected.

The present study aimed to bring a new perspective to the literature by evaluating the contagiousness of local uncertainty in the globalizing world and the monetary policies implemented as a precaution against this situation on an empirical plane.

In a rapidly changing world, organisations are constantly presented with threats and opportunities and the need to be responsive and resilient. This necessitates developing risk and uncertainty management capabilities within organisations. This article aims to consider risk and uncertainty competence, knowledge, skills, attitudes and the behaviours required by contemporary managers to protect their organisations from threat and harm, whilst seizing opportunity and reward.

This article presents answers to three fundamental questions: (1) Do all managers (those not specialising in risk management) need to be competent in risk and uncertainty management? (2) What does risk competence mean? and (3) How can managers develop the capabilities to become risk competent? The content can be used by practicing managers or educators to develop individual and ultimately organisational risk competence.

All contemporary managers should have some degree of risk competence. Risk competence behavioural indicators and requisite risk knowledge and skills are identified and discussed.

This article provides a contemporary view on risk and uncertainty management competence, drawing on relevant competence frameworks and the existing risk literature.

This paper aims to determine the status of the socialist market economy through a logical analysis of the evolution of economic systems in human society.

This paper presents an analysis of uncertainty and the functions performed by different economic systems in managing and resolving it, thereby explaining the evolutionary rationale behind economic system evolution.

Firstly, the socialist market economy empowers the market to play a decisive role in resource allocation, which serves as the foundation for activating individuals' motivation to engage in economic activities. Secondly, the socialist market economy adheres to the basic socialist economic system, which is the basis for the socialist market economy to stabilize the economy and society or to address the risk of economic uncertainty that may trigger macro-level inconsistencies in economic operations. Thirdly, the advantages of a socialist market economy in adapting to economic uncertainties do not arise spontaneously and must be exerted through continuous improvement of the socialist market economy.

The innovation of this paper lies in introducing uncertainty to clarify the logic behind the evolution of economic systems in human society and explaining the typical significance of the socialist market economy and its advantages in accommodating and resolving uncertainty.

Due to increasing supply chain complexity, the supply chain uncertainty has become an imperative issue, which hinders the development of modern logistics and supply chain management. The paper attempts to conceptualize reverse logistics uncertainty from supply chain uncertainty literature and present the types of reverse logistics uncertainty in a triadic model.

The concept of reverse logistics uncertainty is developed based on a triadic model of logistics uncertainty and supply chain uncertainty literature. A desk research is conducted to develop a taxonomy of reverse logistics uncertainty. To better depict the reverse logistics uncertainty, we use case studies to discuss the types of reverse logistics uncertainty in the triadic model.

The study reveals four types of supply chain uncertainties in the reverse logistics. We call them reverse logistics uncertainty. Type-A and Type-B uncertainty are new types of supply chain uncertainty in the reverse logistics.

The types of reverse logistics uncertainty have not been empirically validated in industries. Especially, the two new types including Type-A and Type-B reverse uncertainty need further exploration.

Although reverse logistics has been discussed in the past decades, very few studies have been conducted on the supply chain uncertainty in returns management arena. The paper offers valuable insights to better understand the supply chain uncertainty in the reverse logistics. This also provides suggestions for both managers and researchers to reflect on the reverse logistics uncertainty management and business sustainability.