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1 – 10 of 23Xiaoli Su, Lijun Zeng, Bo Shao and Binlong Lin
The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production…
Abstract
Purpose
The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production planning problem when a manufacturer can observe historical demand data with high-dimensional mixed-frequency features, which provides fine-grained information.
Design/methodology/approach
In this study, a two-step data-driven optimization model is proposed to examine production planning with the exploitation of mixed-frequency demand data is proposed. First, an Unrestricted MIxed DAta Sampling approach is proposed, which imposes Group LASSO Penalty (GP-U-MIDAS). The use of high frequency of massive demand information is analytically justified to significantly improve the predictive ability without sacrificing goodness-of-fit. Then, integrated with the GP-U-MIDAS approach, the authors develop a multiperiod production planning model with a rolling cycle. The performance is evaluated by forecasting outcomes, production planning decisions, service levels and total cost.
Findings
Numerical results show that the key variables influencing market demand can be completely recognized through the GP-U-MIDAS approach; in particular, the selected accuracy of crucial features exceeds 92%. Furthermore, the proposed approach performs well regarding both in-sample fitting and out-of-sample forecasting throughout most of the horizons. Taking the total cost and service level obtained under the actual demand as the benchmark, the mean values of both the service level and total cost differences are reduced. The mean deviations of the service level and total cost are reduced to less than 2.4%. This indicates that when faced with fluctuating demand, the manufacturer can adopt the proposed model to effectively manage total costs and experience an enhanced service level.
Originality/value
Compared with previous studies, the authors develop a two-step data-driven optimization model by directly incorporating a potentially large number of features; the model can help manufacturers effectively identify the key features of market demand, improve the accuracy of demand estimations and make informed production decisions. Moreover, demand forecasting and optimal production decisions behave robustly with shifting demand and different cost structures, which can provide manufacturers an excellent method for solving production planning problems under demand uncertainty.
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Zuanbo Zhou, Wenxin Yu, Junnian Wang, Yanming Zhao and Meiting Liu
With the development of integrated circuit and communication technology, digital secure communication has become a research hotspot. This paper aims to design a five-dimensional…
Abstract
Purpose
With the development of integrated circuit and communication technology, digital secure communication has become a research hotspot. This paper aims to design a five-dimensional fractional-order chaotic secure communication circuit with sliding mode synchronous based on microcontroller (MCU).
Design/methodology/approach
First, a five-dimensional fractional-order chaotic system for encryption is constructed. The approximate numerical solution of fractional-order chaotic system is calculated by Adomian decomposition method, and the phase diagram is obtained. Then, combined with the complexity and 0–1 test algorithm, the parameters of fractional-order chaotic system for encryption are selected. In addition, a sliding mode controller based on the new reaching law is constructed, and its stability is proved. The chaotic system can be synchronized in a short time by using sliding mode control synchronization.
Findings
The electronic circuit is implemented to verify the feasibility and effectiveness of the designed scheme.
Originality/value
It is feasible to realize fractional-order chaotic secure communication using MCU, and further reducing the synchronization error is the focus of future work.
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Elisabetta Savelli, Barbara Francioni, Ilaria Curina and Marco Cioppi
The purpose of this study is to extend the research on fashion renting (FR) by investigating how personal and social motives (i.e. “subjective norms”, “perceived behavioural…
Abstract
Purpose
The purpose of this study is to extend the research on fashion renting (FR) by investigating how personal and social motives (i.e. “subjective norms”, “perceived behavioural control”, “sustainable orientation” and “FR benefits”) affect consumers’ attitudes and intentions towards it. In addition, personality traits are investigated as potential antecedents of FR, resulting in the proposal of an overall framework that combines the theory of planned behaviour with the trait theory approach.
Design/methodology/approach
Data were collected in Italy from a sample of 694 consumers, mainly females (88%), with an average age of 28.8 years and coming from all over the country. The collected data were then processed via structural equation modelling.
Findings
The results indicated that intention towards FR is influenced by attitude, which, in turn, is affected by social norms, perceived behavioural control, sustainable orientation and FR benefits. Furthermore, only fashion leadership acts as a direct antecedent of FR attitude, while the need for uniqueness and materialism plays critical roles as predictors of personal and social motives. Subjective norms and perceived behavioural control also serve as mediators of the significant relationships between personality traits and attitudes towards FR.
Practical implications
The study provides useful implications for fashion rental companies in attracting consumers and offers a foundation for further research on transforming traditional consumption into a more sustainable one.
Originality/value
The study presents new knowledge on the rental phenomenon in the fashion sector by responding to the call to deepen the analysis of factors that influence consumers’ adoption of FR from the perspectives of personal and social motives and personality traits.
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Pawan Kumar, Bindu Aggarwal, Ranjeet Verma and Gursimranjit Singh
As the world continues to urbanise, cities face increasing pressure to become more sustainable, efficient and livable. Sustainable smart cities are emerging as a promising…
Abstract
As the world continues to urbanise, cities face increasing pressure to become more sustainable, efficient and livable. Sustainable smart cities are emerging as a promising solution to this challenge, leveraging technology and data to improve urban systems and services while reducing environmental impact. This chapter provides an overview of the concept of sustainable smart cities and its implications for urban development. It explores the key features of sustainable smart cities, including their focus on technology, data and citizen engagement and the challenges they are facing in terms of infrastructure, data management, social equity, environmental sustainability, governance and regulations. The chapter also highlights the implications of sustainable smart cities for urban planners, policymakers and other stakeholders, emphasising the need for collaborative approaches that engage citizens and stakeholders in the design and implementation of smart city initiatives.
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Maria Babar, Habib Ahmad and Imran Yousaf
This study examines the information transmission (return and volatility spillovers) among energy commodities (crude oil, natural gas, Brent oil, heating oil, gasoil, gasoline) and…
Abstract
Purpose
This study examines the information transmission (return and volatility spillovers) among energy commodities (crude oil, natural gas, Brent oil, heating oil, gasoil, gasoline) and Asian stock markets which are net importers of energy (China, India, Indonesia, Malaysia, Korea, Pakistan, Philippines, Taiwan, Thailand).
Design/methodology/approach
The information transmission is investigated by employing the spillover index of Diebold and Yilmaz, using daily data for the period January 2000 to May 2021.
Findings
A Strong connectedness is documented between the two classes of asset, especially during crisis periods. Our findings reveal that most of the energy markets, except gasoil and natural gas, are net transmitters of information, whereas all the stock markets, excluding Indonesia and Korea, are net recipients.
Practical implications
The findings are helpful for portfolio managers and institutional investors allocating funds to various asset classes in times of crisis.
Originality/value
All data is original.
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Xian-long Ge, MuShun Xu, Bo Wang and Zuo-fa Yin
As of December 2022, there were 119,000 gas stations, 10,800 gas stations and 4,488,000 charging piles nationwide, while the number of vehicles reached 312 million, including…
Abstract
Purpose
As of December 2022, there were 119,000 gas stations, 10,800 gas stations and 4,488,000 charging piles nationwide, while the number of vehicles reached 312 million, including 11.49 million new energy vehicles. The imbalance between transportation energy supply and energy replenishment demand leads to crowded queues of vehicles at some stations and idle resources in others. How to reduce the phenomenon of large queues and improve the utilization rate of idle resources is the key to alleviating the imbalance between supply and demand.
Design/methodology/approach
Therefore, from the perspective of spatio-temporal equilibrium of urban transportation energy supply stations, multi-energy supply station cooperation is established in view of the phenomenon of large spatio-temporal differences among different energy supply stations, and corresponding inducing strategies are adopted for energy supplement vehicles in the road network, so that part of queued users go to energy supply stations with fewer vehicles, so as to balance the supply and demand of transportation energy in the region. On this basis, the income distribution of urban transportation energy supply station is discussed.
Findings
The total revenue after the cooperation was 13,095, an increase of 22.9%. Secondly, in terms of distribution rationality, three impact factors are selected and Shapley correction value is used to distribute the total income. Compared with independent operation, both sites have a certain degree of increase.
Originality/value
Traffic congestion at energy supply stations is closely related to the number, location and number of vehicles at energy supply stations. Therefore, using a cooperative approach of energy trading cannot solve the queuing problem. In addition, there are a few research results on the equalization of energy supply station services considering time-of-use pricing. However, these studies do not consider the vehicular grooming at congested stations. As far as the authors know, there are no relevant research results in the research on the service equilibrium of energy supply stations based on cooperative games.
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Chuanmin Mi, Xiaoyi Gou, Yating Ren, Bo Zeng, Jamshed Khalid and Yuhuan Ma
Accurate prediction of seasonal power consumption trends with impact disturbances provides a scientific basis for the flexible balance of the long timescale power system…
Abstract
Purpose
Accurate prediction of seasonal power consumption trends with impact disturbances provides a scientific basis for the flexible balance of the long timescale power system. Consequently, it fosters reasonable scheduling plans, ensuring the safety of the system and improving the economic dispatching efficiency of the power system.
Design/methodology/approach
First, a new seasonal grey buffer operator in the longitudinal and transverse dimensional perspectives is designed. Then, a new seasonal grey modeling approach that integrates the new operator, full real domain fractional order accumulation generation technique, grey prediction modeling tool and fruit fly optimization algorithm is proposed. Moreover, the rationality, scientificity and superiority of the new approach are verified by designing 24 seasonal electricity consumption forecasting approaches, incorporating case study and amalgamating qualitative and quantitative research.
Findings
Compared with other comparative models, the new approach has superior mean absolute percentage error and mean absolute error. Furthermore, the research results show that the new method provides a scientific and effective mathematical method for solving the seasonal trend power consumption forecasting modeling with impact disturbance.
Originality/value
Considering the development trend of longitudinal and transverse dimensions of seasonal data with impact disturbance and the differences in each stage, a new grey buffer operator is constructed, and a new seasonal grey modeling approach with multi-method fusion is proposed to solve the seasonal power consumption forecasting problem.
Highlights
The highlights of the paper are as follows:
A new seasonal grey buffer operator is constructed.
The impact of shock perturbations on seasonal data trends is effectively mitigated.
A novel seasonal grey forecasting approach with multi-method fusion is proposed.
Seasonal electricity consumption is successfully predicted by the novel approach.
The way to adjust China's power system flexibility in the future is analyzed.
A new seasonal grey buffer operator is constructed.
The impact of shock perturbations on seasonal data trends is effectively mitigated.
A novel seasonal grey forecasting approach with multi-method fusion is proposed.
Seasonal electricity consumption is successfully predicted by the novel approach.
The way to adjust China's power system flexibility in the future is analyzed.
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Mohd Tariq Jamal, Imran Anwar, Nawab Ali Khan and Gayas Ahmad
Working remotely in a COVID-19-induced lockdown has been challenging for both organisations and their employees; studies report that job demands changed, and teleworkers…
Abstract
Purpose
Working remotely in a COVID-19-induced lockdown has been challenging for both organisations and their employees; studies report that job demands changed, and teleworkers experienced increased burnout. This paper explores the negative employee outcomes that this work arrangement brings along and offers possible solutions to counter such negative outcomes since they could be detrimental to the much-touted future of work.
Design/methodology/approach
The study adopted a time-lagged longitudinal design and collected two-waved data from 403 quaternary sector employees. The data were analysed using structural equation modelling and model-21 in PROCESS macro for SPSS.
Findings
Findings affirm that employees experienced increased job demands during this crisis. Employees reported an increase in turnover intention because of burnout caused by increased job demands. However, increased task interdependence alone did not have any effect on turnover intention. The perceived organisational task support (POTS) was found to forestall the negative effect of job demands on burnout, and employee resilience (ER) buffered the burnout and turnover intention relationship.
Practical implications
Providing remote work task support and boosting resilience among employees will help in doing away with the negative effects of teleworking. However, managers shall prioritise reducing job demands for teleworkers.
Originality/value
The linkage between work factors and turnover intention is well established. Drawing on the event system theory and using the COVID-19 context, the present study added to the existing knowledge by studying the role of job demands (workload pressure and task interdependence) on turnover intention through the mediation of burnout. The study goes beyond the existing literature by accounting for POTS as a first-level moderator between job demands and burnout relationship, and ER as a second-level moderator between burnout and turnover intention relationship.
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