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The purpose of this study is to quantify port efficiency assessment indicators to analyze the impact of COVID-19 on Chinese One Belt One Road (OBOR) ports.

This study utilized a grey prediction model GM(1,1) to forecast five relevant indicators for each of the 17 OBOR ports both with and without COVID-19 background conditions. Additionally, the data envelopment analysis (DEA) efficiency assessment approach was used to analyze the impact of COVID-19 on port efficiency.

The results indicate that cargo and container throughput growth rates during the COVID-19 pandemic are reduced by 1.7 and 2.1%, respectively. There was also a noticeable reduction in technological efficiency (TE) as well as pure technological efficiency (PTE), while scale efficiency (SE) remained largely unaffected. Furthermore, the dynamic efficiency MI was mainly negatively impacted by changes in overall efficiency change (EFFCH), where pure efficiency change (PECH) less than one contributed significantly towards overall regression of port efficiencies during this period.

This paper is unique in its use of a combination of the grey prediction model and DEA efficiency assessment to quantify changes in important indicators during pandemic periods. This approach not only provides a quantitative understanding of the impact on port-level efficiency through numerical quantification but also offers readers an intuitive understanding.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

In the multilayered capability framework the authors integrate two layers, namely functional level production capabilities and shop floor-level production routines (PRs). The authors examine how these two layers are interlinked, and additionally, they explore how these layers contribute to firm performance.

The authors tested the hypotheses using structural equation modeling (SEM) on a sample of manufacturing firms.

Regarding the capability layers, the authors found that at the functional level, production dynamic capabilities (PDCs) drive the renewal of production ordinary capabilities (POCs), and that at the shop floor level, deployment of Industry 4.0 (I4.0) is influenced by lean production. Regarding the direct links between capability layers, the authors showed that PDCs and POCs have different roles in shaping shop floor PRs: PDCs is linked to I4.0, and lean methods is impacted by POCs. Concerning performance implications, only PDC and POC have significant impact on firm performance (the latter is negative), while PRs do not.

Although, contextual factors (e.g. technology intensity, size) do not influence our findings, the potential country-effect and the dominance of medium-sized firms offer future research directions.

If production managers want to contribute to business performance, they should be more susceptible to resource renewal (PDCs) than to their general (POCs) or specific (PRs) exploitation efforts. As they exploit current resource stocks, they face a trade-off: they must consider that beyond their positive impacts on operational performance, their implications on business performance will be controversial.

Scholars usually examine one layer of capabilities, either capabilities or routines, and associate that with one dimension of performance, either financial and market measures or operational indicators. The authors propose a multilayered capability framework with a complex view on performance implications.

This study provides empirical evidence on the impact of the Panama Canal expansion (PCE) on the economies of Latin American and Caribbean (LAC) countries, particularly in light of the emergence of larger container ships such as neo-Panamax and post-Panamax vessels.

This study uses the Bayesian structural time Series (BSTS) model to evaluate the economic effects of the PCE on 21 countries within the LAC region. It utilized the World Bank's gross domestic product (GDP) figures between 2000 and 2019 as the primary variable, alongside the human development index (HDI) (X1), container throughput (TEU) (X2) and unemployment rates (UNEMPL) (X3) covariates. This allowed a precise and robust approach to analyzing time series data while accounting for uncertainties and allowing the inclusion of various components and external factors.

The findings revealed that the PCE has a positive and statistically significant impact on most countries within the Caribbean Transshipment Triangle, ranging from 9.2% in Belize to 46% in Cuba. This suggests that the causal effect of the PCE on regional economies was not confined to any specific type of economy or geographical location within the LAC region. Where the growth rates were statistically insignificant, primarily in some Latin American countries, it coincided with countries that are primarily driven by exports and service industries, where bulk and oil tanker vessels are likely to be the main carriers for exports rather than container vessels.

The practical implications of this research are crucial for various stakeholders in the maritime industry and economic planning. The factors influencing economic growth resulting from investing in maritime activities are vital for decision-makers to create policies that lead to positive outcomes and sustainable development in regions and countries with flourishing maritime industries. The methodology and findings have significant implications for governments, managers, professionals, policy-makers and investors.

This study examines the moderating role of information sharing on the effect of lead-time management on the performance of firms in the Zimbabwean motor industry.

Data were collected using Likert-based structured questionnaires from a sample of 105 employees in Zimbabwe. In addition, Pearson Correlation, Linear Regression and Moderation Regression analysis were employed to test the relationship between study variables.

The study found that fixed lead time, preprocessing lead time, processing lead time and postprocessing lead time significantly influence the performance of firms in the motor industry. The results also demonstrate that information sharing moderates the effect of lead-time management on firm performance in the motor industry.

Firms in the motor industry should establish long-term relationships with their suppliers and implement effective communication channels for timely and frequent information exchange regarding production schedules, inventory levels, quality standards and potential disruptions.

The current study aims to contribute to the scientific discourse on lead-time management, information sharing and performance in the motor industry. Furthermore, it extends knowledge on the performance of the motor industry in the African region.

This article aims to optimise energy use and consumption by integrating Lean Six Sigma methodology with the ISO 50001 energy management system standard in an Irish dairy plant operation.

This work utilised Lean Six Sigma methodology to identify methods to measure and optimise energy consumption. The authors use a single descriptive case study in an Irish dairy as the methodology to explain how DMAIC was applied to reduce energy consumption.

The replacement of heavy oil with liquid natural gas in combination with the new design of steam boilers led to a CO₂ footprint reduction of almost 50%.

A further longitudinal study would be useful to measure and monitor the energy management system progress and carry out more case studies on LSS integration with energy management systems across the dairy industry.

The novelty of this study is the application of LSS in the dairy sector as an enabler of a greater energy-efficient facility, as well as the testing of the DMAIC approach to meet a key objective for ISO 50001 accreditation.

It has been argued that a mono product economy experiences epileptic growth because it is prone to global dynamics such as epidemic. Therefore, the need to diversify investments cannot be over-emphasized. Hence, the study examined port operation's efficiency and revenue generation in global maritime trade: implications for national growth and development in Nigeria. The objectives of the study are to identify the factors that improve efficiency in port operations, and to ascertain how efficiency of operations will affect revenue generation and national growth.

The study employed correlation and multiple regressions analyses to test the hypothesis which states that port operation's efficiency does not have positive and significant effect on revenue generation in Nigeria. A cross sectional research design and structured questionnaires were deployed in the study and simple random sampling technique was used to select the sample size of 200 respondents.

Results revealed that efficient port operations affect revenue generation and national development.

Port operations in Nigeria are bedeviled with daunting challenges that hamper smooth and efficient working port's system.

The study suggested that modern port's technologies (ICTs) be deployed to enhance operations in the ports and manpower should be trained on regular intervals to understand modern logistics management techniques in the ports. Third, government should provide port infrastructures being the backbone of efficient port system. Lastly, the private sector should be partnered with in several areas including port's concession to facilitate effective and efficient service delivery in the Nigerian ports.

The purpose of this paper is to develop a framework to evaluate and assess the performance of the COVID-19 vaccine distribution process that is sensitive to the unique supply-side and demand-side constraints exhibited in the US vaccine rollout.

A queuing framework that operates under two distinct regimes is formulated to analyze service rates that represent system capacity to vaccinate (under the first regime) and hesitancy-induced throughput (under the second regime). These supply- and hesitancy-constrained regimes form the focus of the present paper, as the former reflects the inherent ability of the nation in its various jurisdictions to mobilize, whereas the latter reflects a critical area for public policy to protect the population’s overall health and safety.

The two-regime framework analysis provides insights into the capacity to vaccinate and hesitancy-constrained demand, which is found to vary across the country primarily by politics and region. The framework also allows analysis of the end-to-end supply chain, where it is found that the ability to vaccinate was likely constrained by last-mile administration issues, rather than the capacity of the manufacturing and transportation steps of the supply chain.

This study presents a new framework to consider end-to-end supply chains as dynamic systems that exhibit different regimes because of unique supply- and demand-side characteristics and estimate rollout capacity and underlying determinants at the national, state and county levels.

The term competitive has always been used as a comparison to provide a distinction between two or more things. Southeast Asia handles billions of tonnes of global seaborne trade annually. Thus, there is a necessity to look in detail at the performance indicators of port competitiveness on the basis of port performance.

This study has categorized 18 Malaysian bulk terminals into two different classes based on various performance indicators. The distinctions used a hierarchical cluster analysis by arranging the performance indicators. The technique is among the most popular techniques used to form homogeneous groups of entities or objects.

In this study, it was found that two classes were classified as being competitive from the homogeneous groups created. Based on the performance metrics chosen, Group 1 had the lowest score and Group 2 had the highest score. It was found that the Westport and Northport of Klang Port had the best performance of all.

A major challenge for the study is the lack of variables relevant to other port competitiveness requirements, and a detailed research study is needed to gather information on the satisfaction of terminal customers, the paperwork involved, the accuracy and consistency of tariffs paid, the level of safety at sea and on land and environmental protection around the facility site.

The study on ports has been given less attention among researchers in this particular area. Therefore, this paper focuses on the port terminals in Malaysia and compares port performance metrics between ports to determine their competitiveness.