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1 – 10 of over 5000Peng Peng and Zhigang Xu
Large-scale farm management in China has developed rapidly in recent years. Large-scale farmers face substantial operating risks, requiring extensive price risk management…
Abstract
Purpose
Large-scale farm management in China has developed rapidly in recent years. Large-scale farmers face substantial operating risks, requiring extensive price risk management. However, the agricultural insurance and futures markets in China are incomplete. This study aims to analyze the price-risk-management behaviors of large-scale farmers under incomplete market conditions, with a focus on the interconnections between large scale farmers' subjective preferences (risk preferences, time preferences), liquidity constraints and their price risk management.
Design/methodology/approach
The authors construct an analysis framework to reveal the impact of large-scale farmers' risk preferences, time preferences and liquidity conditions on their price-risk-management behaviors under incomplete market conditions. Using data from field surveys and subjective preference experiments involving 409 large-scale grain farmers in China, an empirical analysis was conducted using the bivariate probit model.
Findings
The results show that risk-averse farmers will use risk transfer (such as contract farming) and risk diversification (such as multi-period sales) to avoid price risk. However, farmers subject to liquidity constraints and strong time preferences will not choose risk diversification, and the interaction between time preferences and liquidity constraints will strengthen this decision. The larger the farm-management scale, the greater the impact.
Originality/value
The authors focus on rapidly developed large-scale farm management in China. Appropriate price risk management is required by large-scale farmers due to their substantial operating risks. Considering the incomplete conditions of agricultural insurance and futures markets, the results of this study will help identify behavioral characteristics of large-scale farmers and optimize their price-risk-management strategies, further stabilizing large-scale farm management.
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The purpose of this study is to automatically generate a construction schedule by extracting data from the BIM (Building Information Modeling) model and combining an ontology…
Abstract
Purpose
The purpose of this study is to automatically generate a construction schedule by extracting data from the BIM (Building Information Modeling) model and combining an ontology constraint rule and a genetic algorithm (GA).
Design/methodology/approach
This study developed a feasible multi-phase framework to generate the construction schedule automatically through extracting information from the BIM, utilizing the ontology constraint rule to demonstrate the relationships between all the components and finally using the GA to generate the construction schedule.
Findings
To present the functionality of the framework, a prototype case is adopted to show the whole procedure, and the results show that the scheme designed in this study can quickly generate the schedule and ensure that it can satisfy the requirements of logical constraints and time parameter constraints.
Practical implications
A proper utilization of conceptual framework can contribute to the automatic generation of construction schedules and significantly reduce manual errors in the Architectural, Engineering, and Construction (AEC) industry. Moreover, a scheme of BIM-based ontology and GA for construction schedule generation may reduce additional manual work and improve schedule management performance.
Social implications
The hybrid approach combines the ontology constraint rule and GA proposed in this study, and it is an effective attempt to generate the construction schedule, which provides a direct indicator for the schedule control of the project.
Originality/value
In this study, the data application process of the BIM model is divided into four modules: extraction, processing, optimization, and output. The key technologies including secondary development, ontology theory, and GA are introduced to develop a multi-phase framework for the automatic generation of the construction schedule and to realize the schedule prediction under logical constraints and duration interference.
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Huijuan Zhou, Rui Wang, Dongyang Weng, Ruoyu Wang and Yaoqin Qiao
The interruption event will seriously affect the normal operation of urban rail transit lines,causing a large number of passengers to be stranded in the station and even making…
Abstract
Purpose
The interruption event will seriously affect the normal operation of urban rail transit lines,causing a large number of passengers to be stranded in the station and even making the train stranded in the interval between stations. This study aims to reduce the impact of interrupt events and improve service levels.
Design/methodology/approach
To address this issue, this paper considers the constraints of train operation safety, capacity and dynamic passenger flow demand. It proposes a method for adjusting small loops during interruption events and constructs a train operation adjustment model with the objective of minimizing the total passenger waiting time. This model enables the rapid development of train operation plans in interruption scenarios, coordinating train scheduling and line resources to minimize passenger travel time and mitigate the impact of interruptions. Regarding the proposed train operation adjustment model, an improved genetic algorithm (GA) is designed to solve it.
Findings
The model and algorithm are applied to a case study of interruption events on Beijing Subway Line 5. The results indicate that after solving the constructed model, the train departure intervals can be maintained between 1.5 min and 3 min. This ensures both the safety of train operations on the line and a good match with passengers’ travel demands, effectively reducing the total passenger waiting time and improving the service level of the urban rail transit system during interruptions. Compared to the GA algorithm, the algorithm proposed in this paper demonstrates faster convergence speed and better computational results.
Originality/value
This study explicitly outlines the adjustment method of using short-turn operation during operational interruptions, with train departure times and station stop times as decision variables. It takes into full consideration safety constraints on train operations, train capacity constraints and dynamic passenger demand. It has constructed a train schedule optimization model with the goal of minimizing the total waiting time for all passengers in the system.
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Mohit Datt, Ajay Gupta, Sushendra Kumar Misra and Mahesh Gupta
Theory of Constraints (TOC), though a well-established process improvement methodology in manufacturing, is still a novel philosophy for healthcare and an exhaustive review of…
Abstract
Purpose
Theory of Constraints (TOC), though a well-established process improvement methodology in manufacturing, is still a novel philosophy for healthcare and an exhaustive review of literature is needed to summarize the key findings of various researchers. Such a review can provide a direction to the researchers and academicians interested in exploring the application of TOC in the healthcare sector. This paper aims to review the existing literature of TOC tools and techniques applied to the healthcare environment, and to investigate motivating factors, benefits and key gaps for identifying directions for future research in the domain of healthcare.
Design/methodology/approach
In this paper, different electronic repositories were searched using multiple keywords. The current study identified 36 articles published between January 1999 to mid-2021 to conceptualize and summarize the research questions used in the study. Descriptive analysis along with pictorial representations have been used for better visualization of work.
Findings
This paper presents a thorough literature review of TOC in healthcare and identifies the evolution, current trends, tools used, nature of services chosen for application and research gaps and recommends future direction for research. A variety of motivating factors and benefits of TOC in healthcare are identified. Another key finding of this study is that almost all implementations listed in literature reported positive outcomes and substantial improvements in the performance of the healthcare unit chosen for study.
Practical implications
This paper provides valuable insight to researchers, practitioners and policymakers on the potential of TOC to improve quality of services, flow of patients, revenues, process efficiency and cost reduction in different health care settings. A number of findings and suggestions compiled in the paper from literature study can be used for diagnosing, learning and making substantial changes in healthcare. The methodologies used by different researchers were analysed and combined to propose a generic step by step procedure to apply TOC. This methodology will guide the practising managers about the appropriate tools of TOC for their specific need.
Social implications
Good health is always the first desire of all men and women around the globe. The global aim of healthcare is to quickly cure more patients and ensure healthier population both today and in future. This article will work as a foundation for future applications of TOC in healthcare and guide upcoming applications in the booming healthcare sector. The paper will help the healthcare managers in serving a greater number of patients with limited available resources.
Originality/value
This paper provides original collaborative work compiled by the authors. Since no comprehensive systematic review of TOC in healthcare has been reported earlier, this study would be a valuable asset for researchers in this field. A model has been presented that links various benefits with one another and clarifies the need to focus on process improvement which naturally results in these benefits. Similarly, a model has been presented to guide the users in implementation of TOC in healthcare.
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Molly R. Burchett, Rhett T. Epler, Alec Pappas, Timothy D. Butler, Maria Rouziou, Willy Bolander and Bruno Lussier
The purpose of this paper is to conceptualize the notion of thin crossing points from a social network perspective and to outline the concrete networking strategies that enable…
Abstract
Purpose
The purpose of this paper is to conceptualize the notion of thin crossing points from a social network perspective and to outline the concrete networking strategies that enable salespeople to foster mutually valuable resource exchange (i.e. to thin crossing points) across a selling ecosystem.
Design/methodology/approach
The authors integrate extant theoretical perspectives to advance a conceptual framework of sales-related networking across three key actors in a selling ecosystem: intraorganizational selling actors and actors in customers and external partner organizations.
Findings
Thin crossing points are defined as figurative transaction points at the boundary between organizations or organizational subunits at which actors engage in mutually valuable resource exchange in the process of value cocreation. To thin crossing points with key ecosystem actors, salespeople must adapt networking strategies considering the time and trust constraints inherent in a network relationship. Such constraints inform the most advantageous network centralities (degree, eigenvector and betweenness) and actions to impact key network properties (tie strength, contact diversity) that enable salespeople to efficiently develop social capital and thus to optimally thin crossing points across a selling ecosystem.
Originality/value
To the best of the authors’ knowledge, this study is the first social network-based exploration of salespeople’s role in thinning crossing points with key ecosystem actors. It advances a novel conceptual framework of sales-related networking strategies that foster social capital development and optimally thin crossing points across a selling ecosystem.
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Facing the diverse needs of large-scale customers, based on available railway service resources and service capabilities, this paper aims to research the design method of railway…
Abstract
Purpose
Facing the diverse needs of large-scale customers, based on available railway service resources and service capabilities, this paper aims to research the design method of railway freight service portfolio, select optimal service solutions and provide customers with comprehensive and customized freight services.
Design/methodology/approach
Based on the characteristics of railway freight services throughout the entire process, the service system is decomposed into independent units of service functions, and a railway freight service combination model is constructed with the goal of minimizing response time, service cost and service time. A model solving algorithm based on adaptive genetic algorithm is proposed.
Findings
Using the computational model, an empirical analysis was conducted on the entire process freight service plan for starch sold from Xi'an to Chengdu as an example. The results showed that the proposed optimization model and algorithm can effectively guide the design of freight plans and provide technical support for real-time response to customers' diversified entire process freight service needs.
Originality/value
With the continuous optimization and upgrading of railway freight source structure, customer demands are becoming increasingly diverse and personalized. Studying and designing a reasonable railway freight service plan throughout the entire process is of great significance for timely response to customer needs, improving service efficiency and reducing design costs.
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Ahsan Haghgoei, Alireza Irajpour and Nasser Hamidi
This paper aims to develop a multi-objective problem for scheduling the operations of trucks entering and exiting cross-docks where the number of unloaded or loaded products by…
Abstract
Purpose
This paper aims to develop a multi-objective problem for scheduling the operations of trucks entering and exiting cross-docks where the number of unloaded or loaded products by trucks is fuzzy logistic. The first objective function minimizes the maximum time to receive the products. The second objective function minimizes the emission cost of trucks. Finally, the third objective function minimizes the number of trucks assigned to the entrance and exit doors.
Design/methodology/approach
Two steps are implemented to validate and modify the proposed model. In the first step, two random numerical examples in small dimensions were solved by GAMS software with min-max objective function as well as genetic algorithms (GA) and particle swarm optimization. In the second step, due to the increasing dimensions of the problem and computational complexity, the problem in question is part of the NP-Hard problem, and therefore multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment.
Findings
Therefore, non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA) are used to solve 30 random problems in high dimensions. Then, the algorithms were ranked using the TOPSIS method for each problem according to the results obtained from the evaluation criteria. The analysis of the results confirms the applicability of the proposed model and solution methods.
Originality/value
This paper proposes mathematical model of truck scheduling for a real problem, including cross-docks that play an essential role in supply chains, as they could reduce order delivery time, inventory holding costs and shipping costs. To solve the proposed multi-objective mathematical model, as the problem is NP-hard, multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment. Therefore, NSGA-II and NRGA are used to solve 30 random problems in high dimensions.
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Ruben Bostyn, Laurens Cherchye, Bram De Rock and Frederic Vermeulen
We make use of rich microdata from the Belgian MEqIn survey, which contains detailed information on individual consumption, public consumption inside households, and time use. We…
Abstract
We make use of rich microdata from the Belgian MEqIn survey, which contains detailed information on individual consumption, public consumption inside households, and time use. We explain the observed household behavior by means of a collective model that integrates marriage market restrictions on intrahousehold allocation patterns. We adopt a revealed preference approach that abstains from any functional form assumptions on individual utility functions or intrahousehold decision processes. This allows us to (set) identify the sharing rule, which governs the intrahousehold sharing of time and money, and to quantify economies of scale within households. We use these results to conduct a robust individual welfare and inequality analysis, hereby highlighting the important role of detailed consumption and time use data.
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Miguel Núñez-Merino, Juan Manuel Maqueira-Marín, José Moyano-Fuentes and Carlos Alberto Castaño-Moraga
The purpose of this paper is to explore and disseminate knowledge about quantum-inspired computing technology's potential to solve complex challenges faced by the operational…
Abstract
Purpose
The purpose of this paper is to explore and disseminate knowledge about quantum-inspired computing technology's potential to solve complex challenges faced by the operational agility capability in Industry 4.0 manufacturing and logistics operations.
Design/methodology/approach
A multi-case study approach is used to determine the impact of quantum-inspired computing technology in manufacturing and logistics processes from the supplier perspective. A literature review provides the basis for a framework to identify a set of flexibility and agility operational capabilities enabled by Industry 4.0 Information and Digital Technologies. The use cases are analyzed in depth, first individually and then jointly.
Findings
Study results suggest that quantum-inspired computing technology has the potential to harness and boost companies' operational flexibility to enhance operational agility in manufacturing and logistics operations management, particularly in the Industry 4.0 context. An exploratory model is proposed to explain the relationships between quantum-inspired computing technology and the deployment of operational agility capabilities.
Originality/value
This is study explores the use of quantum-inspired computing technology in Industry 4.0 operations management and contributes to understanding its potential to enable operational agility capability in manufacturing and logistics operations.
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This research aimed to assess the leadership role of principals in the implementation of peace education in selected secondary schools in the Western Cape, South Africa.
Abstract
Purpose
This research aimed to assess the leadership role of principals in the implementation of peace education in selected secondary schools in the Western Cape, South Africa.
Design/methodology/approach
This study employed qualitative research approach to assess the leadership role of principals in the implementation of peace education in selected secondary schools in the Western Cape, South Africa. Data were gathered from a small sample of six principals from six selected secondary schools which were engaged in the implementation of a peace education programme, and data were analysed using thematic content analyses.
Findings
Findings of the study suggest that principals possess a low level of understanding or awareness of their leadership role in the implementation of peace education. The study pointed out the constraints such as time constraints and learners' negative attitudes and social influences hinder the effective implementation of peace education in selected secondary schools.
Research limitations/implications
First, the data were self-reported and therefore subject to social desirability bias; participants may have provided socially desirable responses rather than their true belief or experiences. Thus, participants may have overstated their role in and commitment to the peace education programme.
Originality/value
Studies that aim to explore alternative approaches to combat violence, such as peace education, are still limited in South Africa. Hence, this paper served to close that gap by contributing to the growing body of research on the leadership role of the principal in the implementation of peace education in the school and exploring barriers hampering its effective implementation.
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