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1 – 10 of 690Yan 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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Santonab Chakraborty, Rakesh D. Raut, T.M. Rofin and Shankar Chakraborty
Supplier selection along with continuous evaluation of their performance is a crucial activity in healthcare supply chain management for effective utilization of scarce resources…
Abstract
Purpose
Supplier selection along with continuous evaluation of their performance is a crucial activity in healthcare supply chain management for effective utilization of scarce resources while providing quality service at an affordable price, and minimizing chances of stock-out, avoiding serious consequences on the illness or fatality of the patients. Presence of both qualitative and quantitative evaluation criteria, set of potential suppliers and participation of different stakeholders with varying interest make healthcare supplier selection a challenging task which can be effectively solved using any of the multi-criteria decision making (MCDM) methods.
Design/methodology/approach
To deal with various qualitative criteria, like cost, quality, delivery performance, reliability, responsiveness and flexibility, this paper proposes integration of grey system theory with a newly developed MCDM tool, i.e. mixed aggregation by comprehensive normalization technique (MACONT) to identify the best performing supplier for pharmaceutical items in a healthcare unit from a pool of six competing alternatives based on the opinions of three healthcare professionals.
Findings
While assessing importance of the six evaluation criteria and performance of the alternative healthcare suppliers against those criteria using grey numbers, and exploring use of three normalization procedures and two aggregation operations of MACONT method, this integrated approach singles out S5 as the most compromised healthcare supplier for the considered problem. A sensitivity analysis of its ranking performance against varying values of both balance parameters and preference parameters also validates its solution accuracy and robustness.
Originality/value
This integrated approach can thus efficiently solve healthcare supplier selection problems based on qualitative evaluation criteria in uncertain group decision making environment. It can also be deployed to deal with other decision making problems in the healthcare sector, like supplier selection for healthcare devices, performance evaluation of healthcare units, ranking of physicians etc.
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Madurachcharige Hasini Vidushima Fernando, Duleepa Dulshan Costa, Buddha Koralage Malsha Nadeetharu and Udayangani Kulatunga
A comprehensive literature review was conducted to identify the lean principles and the challenges of building refurbishment. To have an in-depth investigation of the application…
Abstract
Purpose
A comprehensive literature review was conducted to identify the lean principles and the challenges of building refurbishment. To have an in-depth investigation of the application of lean principles to address the challenges of refurbishment projects, ten expert interviews following a qualitative research approach were utilised in this research. Data were analysed using manual content analysis to derive the framework.
Design/methodology/approach
The refurbishment of buildings has attracted the attention of the present construction industry. However, uncertain project characteristics, information deficiency, limited space for construction activities and less stakeholder involvement make it complex. Since the lean concept effectively deals with complex and uncertain projects, this study focusses to investigate the application of lean principles to overcome the challenges of refurbishment projects in Sri Lanka by developing a framework.
Findings
It was found that the five main lean principles of customer value, value stream, value flow, pull and perfection are appropriate for building refurbishment projects in Sri Lanka. Precise identification of clients and end-users, value adding and non-value adding activities, interruptions and stakeholder communication chains, setting scope, examining the possible technologies and taking measures to deliver the exact product to ensure the successful application of lean principles for refurbishment projects. Further, 27 benefits of five lean principles were identified which can be used to address the 13 identified challenges of building refurbishment of projects. Finally, a framework has developed portraying the application of lean principles in building refurbishment.
Practical implications
The framework developed is beneficial for the building refurbishment project team to address the barriers of refurbishment projects by applying lean principles.
Originality/value
This framework can be used as a guideline for the implementation of building refurbishment projects by addressing their challenges with lean principles.
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The author develops a bilateral Nash bargaining model under value uncertainty and private/asymmetric information, combining ideas from axiomatic and strategic bargaining theory…
Abstract
The author develops a bilateral Nash bargaining model under value uncertainty and private/asymmetric information, combining ideas from axiomatic and strategic bargaining theory. The solution to the model leads organically to a two-tier stochastic frontier (2TSF) setup with intra-error dependence. The author presents two different statistical specifications to estimate the model, one that accounts for regressor endogeneity using copulas, the other able to identify separately the bargaining power from the private information effects at the individual level. An empirical application using a matched employer–employee data set (MEEDS) from Zambia and a second using another one from Ghana showcase the applied potential of the approach.
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Zhenhua Luo, Juntao Guo, Jianqiang Han and Yuhong Wang
Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in…
Abstract
Purpose
Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.
Design/methodology/approach
A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.
Findings
The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.
Originality/value
This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.
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Usama Awan, Muhammad Sufyan, Irfan Ameer, Saqib Shamim, Pervaiz Akhtar and Najam Ul Zia
Despite widespread recognition of the importance of mindfulness in organizational science literature, little is known about how mindfulness motivates individuals to configure…
Abstract
Purpose
Despite widespread recognition of the importance of mindfulness in organizational science literature, little is known about how mindfulness motivates individuals to configure information processing and team member exchange relationships to increase creative process engagement. Drawing on motivated information processing theory, this study conceptualizes and empirically examines whether and how mindfulness motivates individuals toward creative process engagement.
Design/methodology/approach
The authors collected data through an online survey from 311 respondents working in the Research and Development (R&D) departments of organizations in multiple industries in Pakistan. For analytical purposes, the authors have applied the structural equation modeling technique.
Findings
This study advances a different view of individual mindfulness on the creative process engagement in the following ways. First, mindfulness enables individuals to self-regulate in specific situations and become effective in fostering creative process engagement. Second, this study extends research on relational information processing by linking it to mindfulness and creative process engagement. Relational information processing partially mediates the relationship between mindfulness and creative process engagement. Third, this study highlights that mindfulness motivates individuals to focus more on developing quality working relationships, but they seem less willing to participate in idea generation and problem-solving solutions.
Originality/value
The study findings provide implications for research on mindfulness, creativity and motivated information processing to enhance individuals’ creative process engagements. The authors also discuss the implications for executives on the relational and creative benefits of mindfulness.
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Aamir Rashid, Rizwana Rasheed, Abdul Hafaz Ngah, Mahawattage Dona Ranmali Pradeepa Jayaratne, Samar Rahi and Muhammad Nawaz Tunio
Supply chain (SC) management is more challenging than ever. Significantly, the pandemic has provoked global and economic destruction that appeared in the manufacturing industry as…
Abstract
Purpose
Supply chain (SC) management is more challenging than ever. Significantly, the pandemic has provoked global and economic destruction that appeared in the manufacturing industry as a “black swan.” Therefore, the purpose of this study was to examine the role of information processing and digital supply chain in supply chain resilience through supply chain risk management.
Design/methodology/approach
This study examines SC risk management and resilience from an information processing theory perspective. The authors used data collected from 251 SC professionals in the manufacturing industry, and the authors used a quantitative method to analyze the data. The data was analyzed using partial least squares-structural equation modeling. To confirm the higher-order measurement model, the authors used SmartPLS version 4 software.
Findings
This study found that information processing capability (disruptive orientation and visibility in high-order) and digital SC significantly and positively affect SC risk management and resilience. Similarly, SC risk management positively mediates the relationship between information processing capability and digital SC. However, information processing capability was found to have a more substantial effect on SC risk management than the digital SC.
Research limitations/implications
This study has both academic and practical contributions. It contributed to existing information processing theory, and manufacturing firms can improve their performance by proactively responding to SC disruptions by recognizing the pivotal role of study variables in risk management for a resilient SC.
Originality/value
The conceptual model of this study is based on information processing theory, which asserts that synchronizing information processing capabilities and digital SCs allows a firm to deal with unplanned events. SC disruption orientation and visibility are considered risk controllers as they allow the firms to be more proactive. An integrated model of conceptualizing the disruption orientation, visibility (higher-order) and digital SC with information processing theory makes this research novel.
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Ahmad Ebrahimi and Sara Mojtahedi
Warranty-based big data analysis has attracted a great deal of attention because of its key capabilities and role in improving product quality while minimizing costs. Information…
Abstract
Purpose
Warranty-based big data analysis has attracted a great deal of attention because of its key capabilities and role in improving product quality while minimizing costs. Information and details about particular parts (components) repair and replacement during the warranty term, usually stored in the after-sales service database, can be used to solve problems in a variety of sectors. Due to the small number of studies related to the complete analysis of parts failure patterns in the automotive industry in the literature, this paper focuses on discovering and assessing the impact of lesser-studied factors on the failure of auto parts in the warranty period from the after-sales data of an automotive manufacturer.
Design/methodology/approach
The interconnected method used in this study for analyzing failure patterns is formed by combining association rules (AR) mining and Bayesian networks (BNs).
Findings
This research utilized AR analysis to extract valuable information from warranty data, exploring the relationship between component failure, time and location. Additionally, BNs were employed to investigate other potential factors influencing component failure, which could not be identified using Association Rules alone. This approach provided a more comprehensive evaluation of the data and valuable insights for decision-making in relevant industries.
Originality/value
This study's findings are believed to be practical in achieving a better dissection and providing a comprehensive package that can be utilized to increase component quality and overcome cross-sectional solutions. The integration of these methods allowed for a wider exploration of potential factors influencing component failure, enhancing the validity and depth of the research findings.
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Sujie Hu, Yuting Qian and Sumin Hu
The purpose of this study is to explore the economic impact of financial restatements by major customers on the audit opinion of their suppliers, showing that non-financial…
Abstract
Purpose
The purpose of this study is to explore the economic impact of financial restatements by major customers on the audit opinion of their suppliers, showing that non-financial information disclosure potentially helps auditors make better assessments.
Design/methodology/approach
Using a sample of China’s listed firms from 2007 to 2021, the authors aim to find the relationship between customers’ financial restatements and their suppliers’ audit opinions. Heckman selection model, placebo tests and other robustness checks are used as well.
Findings
The findings reveal that customers’ financial restatements have a significant effect on the likelihood of suppliers receiving modified audit opinions. This relationship is pronounced when suppliers face a higher level of financial constraints, exhibit poorer accounting conservatism or receive more negative media coverage. Additionally, this effect occurs through increased business risk and information risk, which heightens auditors’ perceived audit risk. Moreover, the study highlights the influence of switching costs, auditor expertise and restatement severity on this relationship.
Practical implications
Risks originating from customers can spread along the supply chain, emphasizing the necessity for auditors to give heightened attention to both the audited firms and their customer information. Moreover, regulators should carefully consider the important impact of customer information disclosures to maximize the protection of the interests of external information users.
Originality/value
This study not only confirms the crucial role of customer information disclosures in annual reports for stakeholders and auditors but also contributes to the existing literature on customer–supplier relationships.
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Flavian Emmanuel Sapnken, Mohammed Hamaidi, Mohammad M. Hamed, Abdelhamid Issa Hassane and Jean Gaston Tamba
For some years now, Cameroon has seen a significant increase in its electricity demand, and this need is bound to grow within the next few years owing to the current economic…
Abstract
Purpose
For some years now, Cameroon has seen a significant increase in its electricity demand, and this need is bound to grow within the next few years owing to the current economic growth and the ambitious projects underway. Therefore, one of the state's priorities is the mastery of electricity demand. In order to get there, it would be helpful to have reliable forecasting tools. This study proposes a novel version of the discrete grey multivariate convolution model (ODGMC(1,N)).
Design/methodology/approach
Specifically, a linear corrective term is added to its structure, parameterisation is done in a way that is consistent to the modelling procedure and the cumulated forecasting function of ODGMC(1,N) is obtained through an iterative technique.
Findings
Results show that ODGMC(1,N) is more stable and can extract the relationships between the system's input variables. To demonstrate and validate the superiority of ODGMC(1,N), a practical example drawn from the projection of electricity demand in Cameroon till 2030 is used. The findings reveal that the proposed model has a higher prediction precision, with 1.74% mean absolute percentage error and 132.16 root mean square error.
Originality/value
These interesting results are due to (1) the stability of ODGMC(1,N) resulting from a good adequacy between parameters estimation and their implementation, (2) the addition of a term that takes into account the linear impact of time t on the model's performance and (3) the removal of irrelevant information from input data by wavelet transform filtration. Thus, the suggested ODGMC is a robust predictive and monitoring tool for tracking the evolution of electricity needs.
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