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1 – 10 of 99Pasquale Legato and Rina Mary Mazza
An integrated queueing network focused on container storage/retrieval operations occurring on the yard of a transshipment hub is proposed. The purpose of the network is to support…
Abstract
Purpose
An integrated queueing network focused on container storage/retrieval operations occurring on the yard of a transshipment hub is proposed. The purpose of the network is to support decisions related to the organization of the yard area, while also accounting for operations policies and times on the quay.
Design/methodology/approach
A discrete-event simulation model is used to reproduce container handling on both the quay and yard areas, along with the transfer operations between the two. The resulting times, properly estimated by the simulation output, are fed to a simpler queueing network amenable to solution via algorithms based on mean value analysis (MVA) for product-form networks.
Findings
Numerical results justify the proposed approach for getting a fast, yet accurate analytical solution that allows carrying out performance evaluation with respect to both organizational policies and operations management on the yard area.
Practical implications
Practically, the expected performance measures on the yard subsystem can be obtained avoiding additional time-expensive simulation experiments on the entire detailed model.
Originality/value
As a major takeaway, deepening the MVA for generally distributed service times has proven to produce reliable estimations on expected values for both user- and system-oriented performance metrics.
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Nasser Abdali, Saeideh Heidari, Mohammad Alipour-Vaezi, Fariborz Jolai and Amir Aghsami
Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model…
Abstract
Purpose
Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.
Design/methodology/approach
This paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.
Findings
To investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.
Originality/value
Prioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.
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Yan Zhou and Chuanxu Wang
Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to…
Abstract
Purpose
Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.
Design/methodology/approach
This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.
Findings
The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.
Originality/value
Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.
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K. Sandar Kyaw, Yun Luo and Glauco De Vita
This study empirically examines the moderating role of geopolitical risk on the tourism–economic growth nexus by applying a recent geopolitical risk indicator developed by…
Abstract
Purpose
This study empirically examines the moderating role of geopolitical risk on the tourism–economic growth nexus by applying a recent geopolitical risk indicator developed by Caldara and Iacoviello (2022) in a cross-country panel data growth model context for a sample of 24 countries.
Design/methodology/approach
A Dummy Variable Least Squares panel data model, nonparametric covariance matrix estimator and SYS-GMM estimation techniques are employed for the analysis. The authors capture the GPR moderating effect by disaggregating the cross-country sample according to low versus high country GPR score and through a GPR interaction coefficient. Several controls are included in the models such as gross fixed capital formation and—consistent with Barro (1990)—government consumption. Trade openness is used to account for the export-led growth effect. In line with neoclassical growth theory (e.g. Barro, 1991), the authors also include the real interest rate, to account for policy makers' commitment to macroeconomic stability, financial depth, as a proxy for financial development, population growth and the level of secondary school education. The authors also control for unobserved country-specific and time-invariant effects.
Findings
The research finds that the interaction term of geopolitical risk significantly contributes to the predictive ability of the regression and provides empirical evidence that confirms that only in low geopolitical risk countries international tourism positively and significantly contributes to economic growth. Important theoretical and policy implications flow from these findings.
Originality/value
The study not only contributes to advancing academic knowledge on the tourism–growth nexus, it also has impact beyond academia. Many countries have in the past pursued and many continue to pursue, tourism specialization and/or tourism-led growth strategies based on the theoretically well-established and empirically validated positive link between inbound tourism and economic growth. The findings alert policy makers in such countries to the significant moderating role that geopolitical risk plays in affecting the above-mentioned relationship and to the importance of prioritizing geopolitical stability as a policy precursor for the successful implementation of such strategies.
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Gurmeet Singh, Asheefa Shaheen Aiyub, Tuma Greig, Samantha Naidu, Aarti Sewak and Shavneet Sharma
This paper aims to identify factors that influence customers' panic buying behavior during the COVID-19 pandemic.
Abstract
Purpose
This paper aims to identify factors that influence customers' panic buying behavior during the COVID-19 pandemic.
Design/methodology/approach
A self-administered questionnaire was distributed to 357 participants in Fiji, and structural equation modeling to analyze the collected data.
Findings
Results indicate that expected personal outcomes is positively associated with customers' attitudes while expected community-related outcomes negatively impact customers' attitudes. Factors such as attitude, subjective norms, scarcity, time pressure and perceived competition were found to positively influence customers' panic buying intention. Furthermore, scarcity and time pressure were confirmed to positively influence perceived competitiveness while perceived social detection risk negatively influences customer's panic buying intention.
Practical implications
The findings highlight the need for better measures to ensure that every customer has access to goods and services and is not deprived of such necessities in times of a crisis. These results will assist store managers and policymakers in introducing better management, social policies and resource utilization mechanisms to mitigate panic buying during the pandemic.
Originality/value
This study's findings contribute to the literature on customer's panic buying behavior during a global pandemic. Research in this area remain scarce, inconsistent and inconclusive. Novel insights are generated as this study is the first to combine the theory of planned behavior, privacy calculus theory and protection motivation theory. Applying these theories allows new relationships to be tested to better understand customer behavior during a global pandemic. With most studies on customer behavior during crises and disasters in developed countries, this study generates new insights by exploring customer behavior in a developing country.
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Omotayo Farai, Nicole Metje, Carl Anthony, Ali Sadeghioon and David Chapman
Wireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure…
Abstract
Purpose
Wireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure monitoring. One of the main challenges for underground WSN deployment is the limited range (less than 3 m) at which reliable wireless underground communication can be achieved using radio signal propagation through the soil. To overcome this challenge, the purpose of this paper is to investigate a new approach for wireless underground communication using acoustic signal propagation along a buried water pipe.
Design/methodology/approach
An acoustic communication system was developed based on the requirements of low cost (tens of pounds at most), low power supply capacity (in the order of 1 W-h) and miniature (centimetre scale) size for a wireless communication node. The developed system was further tested along a buried steel pipe in poorly graded SAND and a buried medium density polyethylene (MDPE) pipe in well graded SAND.
Findings
With predicted acoustic attenuation of 1.3 dB/m and 2.1 dB/m along the buried steel and MDPE pipes, respectively, reliable acoustic communication is possible up to 17 m for the buried steel pipe and 11 m for the buried MDPE pipe.
Research limitations/implications
Although an important first step, more research is needed to validate the acoustic communication system along a wider water distribution pipe network.
Originality/value
This paper shows the possibility of achieving reliable wireless underground communication along a buried water pipe (especially non-metallic material ones) using low-frequency acoustic propagation along the pipe wall.
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This article aims to explore the engagement of refugees and asylum seekers (RAS) in informal and precarious jobs from a civil society actors' perspective. Despite a burgeoning…
Abstract
Purpose
This article aims to explore the engagement of refugees and asylum seekers (RAS) in informal and precarious jobs from a civil society actors' perspective. Despite a burgeoning literature on refugee integration and a focus on institutional integration programmes, little is known about the early insertion of RAS into informal and precarious employment as an alternative to subsidised integration programmes, when these are available.
Design/methodology/approach
This article draws on rich qualitative data collected through in-depth interviews with social workers, volunteers and other professionals supporting migrants.
Findings
Data analysis shows that migrants' insertion in informal jobs and their rejection of integration programmes may be the result of people's need to access financial capital to cover actual and future needs. Although such an engagement may be criticised for hampering RAS’ integration, it can be seen as an important source of agency against insecurity surrounding one's legal status.
Originality/value
This article highlights the importance of legal status precarity in shaping informal workers' agency and perceptions of them, opening up a debate on the relevance of informal work in terms of long-term integration and future migration trajectories.
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Conghua Wen, Fei Jia and Jianli Hao
Using intraday data, the authors explore the forecast ability of one high frequency order flow imbalance measure (OI) based on the volume-synchronized probability of informed…
Abstract
Purpose
Using intraday data, the authors explore the forecast ability of one high frequency order flow imbalance measure (OI) based on the volume-synchronized probability of informed trading metric (VPIN) for predicting the realized volatility of the index futures on the China Securities Index 300 (CSI 300).
Design/methodology/approach
The authors employ the heterogeneous autoregressive model for realized volatility (HAR-RV) and compare the forecast ability of models with and without the predictive variable, OI.
Findings
The empirical results demonstrate that the augmented HAR model incorporating OI (HARX-RV) can generate more precise forecasts, which implies that the order imbalance measure contains substantial information for describing the volatility dynamics.
Originality/value
The study sheds light on the relation between high frequency trading behavior and volatility forecasting in China's index futures market and reveals the underlying market mechanisms of liquidity-induced volatility.
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Xigang Yuan, Zujun Ma and Xiaoqing Zhang
This paper investigates the dynamic pricing strategy of a firm for the successive-generation products under the conditions of the limited trade-in duration and strategic…
Abstract
Purpose
This paper investigates the dynamic pricing strategy of a firm for the successive-generation products under the conditions of the limited trade-in duration and strategic customers. Further, it explores the effect of a limited trade-in duration on the choice of the myopic and strategic customers, besides the optimal dynamic pricing and trade-in strategy of the firm.
Design/methodology/approach
Based on the choice behavior of the myopic and strategic customers, the authors have developed a two-period game-theoretic analytical model to decide the optimal retail prices of the successive-generation products and the optimal trade-in rebate when the firm adopts a dynamic pricing strategy and then investigate three extensions of the basic model to discuss the change in the results owing to the relaxation of certain conditions.
Findings
The authors find from the results that, in terms of profit maximization, it is better to extend the limited trade-in duration, and hence, the firm should implement a dynamic pricing strategy. However, in the situation of using a static pricing strategy, the firm should extend the limited trade-in duration only if the incremental value of the new generation products is below a certain threshold. Moreover, the firm should use a dual rollover strategy instead of a single rollover one. If all customers in the market are myopic, then the firm should also extend the limited trade-in duration.
Research limitations/implications
This study mainly discusses the impact of limited trade-in duration on the firm's dynamic pricing strategy when facing strategic customers, which provides several directions for future research. First, if the government offers subsidies to consumers, how will strategic consumers make purchase decisions? How would the enterprise make its pricing decision? Second, when asymmetric information exists between consumers and firms, how will it affect consumers' choice behavior and firms' pricing decisions? All these issues are worth exploring in the future.
Practical implications
These results offer certain managerial insights for the firm in the decision making on pricing within the trade-in program.
Originality/value
This is the first work to study the dynamic pricing strategy of the firm for the successive-generation products under the conditions of the limited trade-in duration and strategic customers. Further, this work discusses the changes in results owing to the relaxation of certain conditions.
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Marvin Gonzalez and Gioconda Quesada
The productivity of a port is a measure that is important to different stakeholders: port administrators (port authority), third-party logistics providers, manufacturers and…
Abstract
Purpose
The productivity of a port is a measure that is important to different stakeholders: port administrators (port authority), third-party logistics providers, manufacturers and consumers, among others. This study analyses productivity in terms of vessel movement efficiencies (loading/unloading of cargo) and container release from port facilities. Both factors add to the overall productivity in any port.
Design/methodology/approach
A comparative analysis of the productivity of three ports is measured using a Quality Function Deployment (QFD) and benchmarking analysis to help establish strategies that will help improve productivity. Considering the information confidentially the authors will call the ports according to their geographic location. The ports under study are the USA Southeast Port (Port of America), Central Asian Port (Port of Asia) and Central Europe Port (Port of Europe).
Findings
This study has established an analysis strategy that allows seeing points of sale in the ports. This study will compare three different continents, only to demonstrate the applicability of QFD and benchmarking. Still, the strategy can be used in ports that compete due to their proximity and location. Identifying the variables to be analyzed made it possible to establish a strategy to increase productivity.
Originality/value
There are many studies that analyze port productivity, but none try to standardize the variables to be compared in different scenarios. This study has compared three ports from three different geographical areas, using the same variables in all three cases. The study critically analyses the performance of three ports and proposes a strategy based on QFD and benchmarking research.
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