Search results

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 study predicts the growth of Africa's international trade from 2011 to 2040 by accounting for the uncertainties in the continent.

This study applies a scenario planning method (SPM) to develop multiple future scenarios considering uncertainties inherent in African socio-economies related to the success or failure of economic and industrial policies (EIPs) and economic corridor development policies (ECDPs). Subsequently, based on these future scenarios, the growth of African international trade from 2011 to 2040 is predicted using the Global Trade Analysis Project (GTAP) model.

The predictions reveal that if the EIPs and the ECDPs are successfully implemented, Africa, as a whole, will experience a significant increase in trade, estimated at US$ 1,905 billion and US$ 1,599 billion for exports and imports, respectively, compared to the scenario in which they fail. However, the effects vary greatly by country or region and industrial sector. The results also show that African intra-regional trade is rapidly expanding and is the second-largest after trade with Europe followed by other continents.

SPM, which allows us to reflect the uncertainties affecting African international trade prediction, is applied to build the future scenarios. The study comprehensively predicts African future international trade by setting a wide range of exogenous variables and parameters (input conditions for the GTAP model) related to EIPs and ECDPs.

In this paper, the authors suggest that Central Americans can use entrepreneurship to solve economic uncertainty in their home country and that entrepreneurship can contribute to reducing the number of undocumented migrants to the USA.

The authors first illustrate the context of Central American illegal migration to the USA from a transitional entrepreneurship perspective, the authors address the economic drivers of illegal migration from Central America, which results in marginalization in the USA. Second, the authors build a theoretical model that suggests that Central Americans can improve their entrepreneurial abilities through the entrepreneurial cognitive adjustment mechanism.

Central Americans at risk of illegally migrating to the USA have high entrepreneurial aptitudes. Entrepreneurship can help them avoid the economic uncertainty that drives Central Americans to illegally migrate to the USA and become part of a marginalized community of undocumented immigrants. This conceptual paper introduces an entrepreneurial cognitive adjustment mechanism as a tool for Central Americans to reshape their personalities and increase their entrepreneurial abilities in their home countries. In particular, entrepreneurial intentions reshape the personality characteristics of individuals (in terms of high agreeableness and openness to experiences, as well as low neuroticism) through the entrepreneurial cognitive adjustment mechanism, which consists of reflective action in sensemaking, cognitive frameworks in pattern recognition and coping in positive affect.

This paper studies Central Americans at risk of illegal migration using the lens of transitional entrepreneurship, which advances the understanding of the antecedents to marginalized immigrant communities in the USA and suggests a possible solution for this phenomenon. Besides, the authors build a cognitive mechanism to facilitate the transitional process starting from entrepreneurial intention to reshaping individuals' personality, which further opens individuals' minds to entrepreneurial opportunities. Since entrepreneurial intention applies the same way to all entrepreneurs, the authors' aim of constructing the entrepreneurial intention unfolding process will go beyond transitional entrepreneurship and contribute to intention-action knowledge generation (Donaldson et al., 2021). Moreover, the conceptual study contributes to public policy such that international and local agencies can better utilize resources and implement long-term solutions to the drivers of illegal migration from Central America to the USA.

This investigation aims to determine the effect of trade uncertainty on domestic investment (DI) and foreign direct investment (FDI) for the Turkish economy from the first quarter of 2005 to the first quarter of 2020.

The authors adopt the vector autoregression (VAR) model augmented with Fourier terms. Using this methodology, the authors obtain the empirical results of the impulse-response functions and the variance decomposition analysis.

The empirical results demonstrate that a shock to trade uncertainty has a slight negative impact on DI for up to approximately 1.5 years, whereas its impact on FDI is negative but long-lasting. Moreover, the contribution of trade uncertainty to FDI is relatively higher than to DI in the error variance decomposition for the investigated period. These empirical results can be beneficial for shaping the Turkish authorities' trade policies in the following periods.

These findings have implications within the macroeconomic setting. Government authorities can provide tax exemptions for specified sectors and debureaucratize investment processes for both domestic and foreign entrepreneurs. Additionally, institutional quality and property rights should be protected strictly and developed gradually.

This study is the first to examine the impact of world trade uncertainty on Türkiye’s DI and FDI. Because trade uncertainty might act as fixed costs, this creates the option value of waiting and seeing the market, and firms hesitate to incur investment.

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.

From the standpoint of a policy maker who has access to a number of expert forecasts, the uncertainty of a combined or ensemble forecast should be interpreted as that of a typical forecaster randomly drawn from the pool. This uncertainty formula should incorporate forecaster discord, as justified by (i) disagreement as a component of combined forecast uncertainty, (ii) the model averaging literature, and (iii) central banks’ communication of uncertainty via fan charts. Using new statistics to test for the homogeneity of idiosyncratic errors under the joint limits with both T and n approaching infinity simultaneously, the authors find that some previously used measures can significantly underestimate the conceptually correct benchmark forecast uncertainty.

The purpose of this paper is to present an integrated model to measure the operational efficiency of the top 40 container ports in the world for a five-year continuous period using a two-stage uncertainty data envelopment analysis (UDEA) combined with fuzzy C-means clustering method (FCM).

UDEA model is adopted for measuring the efficiency of container ports to overcome the limitation of the basic model, which is unable to handle uncertain data that are easy to meet in practice. FCM algorithm is implemented to find similar distribution efficiency scores of two stages and the cluster similar efficiency scores of container ports into various groups.

The combination of the two-stage UDEA model and the FCM algorithm provided a more comprehensive view when evaluating the performance of container ports. The UDEA results show that most of the container ports have reduced their profitability level in the second stage and most of the efficient container ports have turned into inefficient ones because of their small scale.

This paper proposes using the two-stage UDEA model to evaluate port efficiency based on two main aspects of productivity and profitability. Moreover, it combines DEA and FCM algorithms to offer a more comprehensive view when measuring the performance of container ports.

A significant body of literature suggests that shipping companies operate in an extremely volatile and risky environment, relying on the effective use of information to remain competitive. However, decision-making in this market is demanding because of the high uncertainty, market competition and significant capital investments. Moreover, the rapid spread of COVID-19 renders information uncertainty a daunting challenge for companies engaged in global trade. Hence, this study aims to explore the information behavior of managers in a time of crisis seems compelling.

This study provides novel insights into the information behavior of senior managers by adopting a qualitative approach. Forty-nine semi-structured face-to-face interviews with individuals from Hellenic shipping companies were conducted. Moreover, this study explores the extant theory qualitatively, using the grounded theory methodology and shows that an unprecedented event (pandemic crisis) can redefine the information behavior of managers.

This study highlights the importance of information in decision-making. Moreover, the results show that, during a pandemic, managers resort to alternative information sources, adopt collaborative information behaviors and take advantage of digital technology.

There is limited research in exploring the information behavior of managers in times of pandemics. This research underscores the fact that during a crisis, managers seek information from digital information resources and decision-making assumes a more decentralized form. This study concludes with a discussion of the theoretical and practical implications of these findings.

The article investigates factors associated with the relative success in adopting two specific alternative marine energies (liquefied natural gas [LNG] and electric batteries) in the Norwegian ferry market. This specific market segment is an interesting case study as its national-flagged fleet boasting the largest number of ships using alternative marine energies in comparison with the other countries of the region and the world.

A database tracking the yearly deployment of ships using a different combination of LNG and electric batteries was built from shipping lines’ online information and grey literature. The technological adoption approach was used to categorize different groups of users at each step of the adoption process and identify which factors separate the early adopters from the other groups of end-users. The compiled data allow tracing the changing distribution of Norwegian ferry operators along the conceptualized technology adoption curve.

Results indicated that the Norwegian ferry market matches required conditions to pass the “chasm” of uncertainties associated with transitioning to new technology. Some disparities between the adoption of LNG and the electric batteries in the Norwegian ferry markets are observed.

To the authors’ knowledge, no study has explored the adoption of new energies in the maritime industry based on the technology adoption process through a similar perspective. The analysis is helpful to shed light on the barriers associated with a high level of uncertainties when it comes to adopting new marine energies.