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1 – 10 of over 227000Indian railways (IR) is one of the largest railway networks in the world. As a part of its strategic development initiative, demand forecasting can be one of the indispensable…
Abstract
Purpose
Indian railways (IR) is one of the largest railway networks in the world. As a part of its strategic development initiative, demand forecasting can be one of the indispensable activities, as it may provide basic inputs for planning and control of various activities such as coach production, planning new trains, coach augmentation and quota redistribution. The purpose of this study is to suggest an approach to demand forecasting for IR management.
Design/methodology/approach
A case study is carried out, wherein several models i.e. automated autoregressive integrated moving average (auto-ARIMA), trigonometric regressors (TBATS), Holt–Winters additive model, Holt–Winters multiplicative model, simple exponential smoothing and simple moving average methods have been tested. As per requirements of IR management, the adopted research methodology is predominantly discursive, and the passenger reservation patterns over a five-year period covering a most representative train service for the past five years have been employed. The relative error matrix and the Akaike information criterion have been used to compare the performance of various models. The Diebold–Mariano test was conducted to examine the accuracy of models.
Findings
The coach production strategy has been proposed on the most suitable auto-ARIMA model. Around 6,000 railway coaches per year have been produced in the past 3 years by IR. As per the coach production plan for the year 2023–2024, a tentative 6551 coaches of various types have been planned for production. The insights gained from this paper may facilitate need-based coach manufacturing and optimum utilization of the inventory.
Originality/value
This study contributes to the literature on rail ticket demand forecasting and adds value to the process of rolling stock management. The proposed model can be a comprehensive decision-making tool to plan for new train services and assess the rolling stock production requirement on any railway system. The analysis may help in making demand predictions for the busy season, and the management can make important decisions about the pricing of services.
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Yusuf Katerega Ndawula, Mori Neema and Isaac Nkote
This study examines the relationship between policyholders’ psychographic characteristics and demand decisions for life insurance products in Uganda.
Abstract
Purpose
This study examines the relationship between policyholders’ psychographic characteristics and demand decisions for life insurance products in Uganda.
Design/methodology/approach
The study is based on a cross-sectional survey. Using a purposive sampling method, 389 questionnaires were administered to life insurance policyholders in the four geographical regions of Uganda. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the primary data, specifically to test the relationships between the dependent and independent variables.
Findings
The findings indicate a positive and significant influence of psychographic characteristics on demand decisions for life insurance products. In addition, the analysis indicates that the two first-order constructs of psychographic characteristics, namely price consciousness and consumer innovativeness, are positive and significant predictors of demand decisions for life insurance products. In contrast, the third first-order construct religious salience, exhibits a negative and nonsignificant effect on demand decisions for life insurance products.
Practical implications
For insurance practitioners, to influence demand decisions, they should emphasize premium-related appeals in their marketing messages (price consciousness) ignore product decisions based on religious beliefs and norms (religious salience). They should also ensure that insurance products are highly trustable and experiential (consumer innovativeness). For insurance policymakers, it offers an in-depth understanding of customer psychographic characteristics, which can be used to identify exploitative information embedded in certain marketing campaigns targeting specific psychographic characteristics, for better regulation.
Originality/value
The study provides a basis for understanding lifestyle and personality characteristics (psychographics), which may influence demand decisions for life insurance products in a developing country like Uganda, where the insurance industry is at an early stage of development.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0440
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Nan Chen, Jianfeng Cai, Devika Kannan and Kannan Govindan
The rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the…
Abstract
Purpose
The rapid development of the Internet has led to an increasingly significant role for E-commerce business. This study examines how the green supply chain (GSC) operates on the E-commerce online channel (resell mode and agency mode) and the traditional offline channel with information sharing under demand uncertainty.
Design/methodology/approach
This study builds a multistage game model that considers the manufacturer selling green products through different channels. On the traditional offline channel, the competing retailers decide whether to share demand signals. Regarding the resale mode of E-commerce online channel, just E-tailer 1 determines whether to share information and decides the retail price. In the agency mode, the manufacturer decides the retail price directly, and E-tailer 2 sets the platform rate.
Findings
This study reveals that information accuracy is conducive to information value and profits on both channels. Interestingly, the platform fee rate in agency mode will inhibit the effect of a positive demand signal. Information sharing will cause double marginal effects, and price competition behavior will mitigate such effects. Additionally, when the platform fee rate is low, the manufacturer will select the E-commerce online channel for operation, but the retailers' profit is the highest in the traditional channel.
Originality/value
This research explores the interplay between different channel structures and information sharing in a GSC, considering price competition and demand uncertainty. Besides, we also considered what behaviors and factors will amplify or transfer the effect of double marginalization.
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The article addresses the optimization of safety stock service levels for parts in a repair kit. The work was undertaken to assist a public transit entity that stores thousands of…
Abstract
Purpose
The article addresses the optimization of safety stock service levels for parts in a repair kit. The work was undertaken to assist a public transit entity that stores thousands of parts used to repair equipment acquired over many decades. Demand is intermittent, procurement lead times are long, and the total inventory investment is significant.
Design/methodology/approach
Demand exists for repair kits, and a repair cannot start until all required parts are available. The cost model includes holding cost to carry the part being modeled as well as shortage cost that consists of the holding cost to carry all other repair kit parts for the duration of the part’s lead time. The model combines deterministic and stochastic approaches by assuming a fixed ordering cycle with Poisson demand.
Findings
The results show that optimal service levels vary as a function of repair demand rate, part lead time, and cost of the part as a percentage of the total part cost for the repair kit. Optimal service levels are higher for inexpensive parts and lower for expensive parts, although the precise levels are impacted by repair demand and part lead time.
Social implications
The proposed model can impact society by improving the operational performance and efficiency of public transit systems, by ensuring that home repair technicians will be prepared for repair tasks, and by reducing the environmental impact of electronic waste consistent with the right-to-repair movement.
Originality/value
The optimization model is unique because (1) it quantifies shortage cost as the cost of unnecessary holding other parts in the repair kit during the shortage time, and (2) it determines a unique service level for each part in a repair kit bases on its lead time, its unit cost, and the total cost of all parts in the repair kit. Results will be counter-intuitive for many inventory managers who would assume that more critical parts should have higher service levels.
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Zabih Ghelichi, Monica Gentili and Pitu Mirchandani
This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to…
Abstract
Purpose
This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.
Design/methodology/approach
This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.
Findings
An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.
Originality/value
The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.
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Peixu He, Hanhui Zhou, Qiongyao Zhou, Cuiling Jiang and Amitabh Anand
Employees may adopt deceptive knowledge hiding (DKH) due to nonworking time information and communication technology (ICT) demands. Drawing from the conservation of resources…
Abstract
Purpose
Employees may adopt deceptive knowledge hiding (DKH) due to nonworking time information and communication technology (ICT) demands. Drawing from the conservation of resources (COR) theory, this study aims to develop and test a model of deceptive knowledge hiding (DKH) due to nonworking time information and communication technology (ICT) demands.
Design/methodology/approach
In total, 300 service employees have joined the three-wave surveys. Path analysis and bootstrapping methods were used to test the theoretical model.
Findings
Results suggest that knowledge requests during nonworking time could deplete employees’ resources and increase their tendency to engage in DKH, whereas work recovery and emotional exhaustion mediate this relationship. In addition, employees’ work–family segmentation preferences (WFSP) were found to moderate the direct effects of nonworking time ICT demands on employees’ work recovery and emotional exhaustion and the indirect effects of knowledge requests after working hours on DKH through employees’ work recovery and emotional exhaustion.
Originality/value
First, the findings of this study shed light on the relationship between knowledge requests during employees’ nonworking time and knowledge hiding, suggesting that knowledge hiding could occur beyond working hours. Second, drawing on COR theory, this study explored two joint processes of resource replenishment failure and depletion and how nonworking time ICT demands trigger knowledge hiding. Third, the interaction effect of individuals’ WFSP and nonworking time factors on knowledge hiding deepens the understanding of when nonworking time ICT demands may induce knowledge hiding through various processes.
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Mengying Zhang, Zhennan Yuan and Ningning Wang
We explore the driving forces behind the channel choices of the manufacturer and the platform by considering asymmetric selling cost and demand information.
Abstract
Purpose
We explore the driving forces behind the channel choices of the manufacturer and the platform by considering asymmetric selling cost and demand information.
Design/methodology/approach
This paper develops game-theoretical models to study different channel strategies for an E-commerce supply chain, in which a manufacturer distributes products through a platform that may operate in either the marketplace channel or the reseller channel.
Findings
Three primary models are built and analyzed. The comparison results show that the platform would share demand information in the reseller channel only if the service cost performance is relatively high. Besides, with an increasing selling cost, the equilibrium channel might shift from the marketplace to the reseller. With increasing information accuracy, the manufacturer tends to select the marketplace channel, while the platform tends to select the reseller channel if the service cost performance is low and tends to select the marketplace channel otherwise.
Practical implications
All these results have been numerically verified in the experiments. At last, we also resort to numerical study and find that as the service cost performance increases, the equilibrium channel may shift from the reseller channel to the marketplace channel. These results provide managerial guidance to online platforms and manufacturers regarding strategic decisions on channel management.
Originality/value
Although prior research has paid extensive attention to the driving forces behind the online channel choice between marketplace and reseller, there is at present few study considering the case where a manufacturer selling through an online platform faces a demand information disadvantage in the reseller channel and sales inefficiency in the marketplace channel. To fill this research gap, our work illustrates the interaction between demand information asymmetry and selling cost asymmetry to identify the equilibrium channel strategy and provides useful managerial guidelines for both online platforms and manufacturers.
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Nastaran Hajiheydari and Mohammad Soltani Delgosha
Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for…
Abstract
Purpose
Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.
Design/methodology/approach
We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.
Findings
Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.
Originality/value
This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.
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Sarit Rashkovits and Esther Unger-Aviram
To better understand employees’ preferred extent for working from home (WFH) setting that implies physical distance from clients and co-workers and enhanced physical proximity to…
Abstract
Purpose
To better understand employees’ preferred extent for working from home (WFH) setting that implies physical distance from clients and co-workers and enhanced physical proximity to others at home, this study, relying on job-demands resources (J-DR) theory, aims to investigate the relationships between this preference with both the perceived increase in emotional job demands and the exposure to childcare demands. Thus, this study aims to investigate the mediating role of perceived job difficulty in the relationship between emotional job demands and the preferred extent for WFH, and the moderating role of gender in the relationship between the number of children and the preferred extent for WFH.
Design/methodology/approach
A total of 239 employees who began WFH during the pandemic completed an online survey. Structural equation modelling was conducted to analyse the data and test the hypotheses.
Findings
As expected, an increase in emotional job demands had a significant negative indirect association with the preferred extent for WFH, through perceived increase in job difficulty. Furthermore, the number of children was negatively related to the preferred extent for WFH among male but not female employees.
Practical implications
The findings provide insights for promoting employees’ preferred extent for WFH.
Originality/value
The study points to a relationship between emotional job demands and employee attitudes towards WFH in terms of increased job difficulty and the preferred extent for WFH. It also points to the need to investigate the interaction between sex and number of children to understand employees’ preferred extent for WFH.
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Weijie Zhou, Tao Wang, Jianhua Zhu, Yuan Tao and Qingzhi Liu
This paper aims to investigate how perceived working conditions affect employee performance, including safety compliance and task performance, through employee well-being (i.e…
Abstract
Purpose
This paper aims to investigate how perceived working conditions affect employee performance, including safety compliance and task performance, through employee well-being (i.e. job satisfaction) in the context of the coal mining sector in China.
Design/methodology/approach
This paper uses the job demands-resources model to test the relationships between working conditions, including job demands (work pressure as a challenge demand and perceived risks and hazards in the workplace and ineffectiveness of the safety system as hindrance demands), job resources (interpersonal harmony), job satisfaction and performance. This study adopts a two-wave design with a three-month lag to reduce possible common method bias.
Findings
Employees who experienced high level of challenge demands, e.g. time pressure workload, reported higher levels of task performance, and this positive relationship seemed to be robust. There is a direct effect of perceived ineffectiveness of the safety system on task performance, while the relationship between perceived risks and hazards and task performance was fully mediated by job satisfaction. Challenge demands, i.e. work pressure, did not impact much on employees’ well-being, and thus job satisfaction did not mediate the relationship between work pressure and performance. Perceived ineffectiveness of the safety system was negatively associated with safety compliance. This result is not surprising since a lack of effective safety system reflects management’s ignorance of workplace safety, which demotivates employees to enact safe behaviors. In contrast, the presence and implementation of an effective safety system would be interpreted by employees as management exhibiting a high level of commitment. Work pressure was positively not negatively related to safety compliance. One possible explanation for this finding is that the effects of work pressure on safety compliance behaviors might be dependent on contextual factors such as safety climate. Interpersonal harmony moderated the relationships between work pressure and employee performance (both safety compliance and task performance) and the relationship between perceived risks and hazards and task performance, but the role of interpersonal harmony appeared more complex. There was no significant correlation between challenging job demands and individual employee performance when there were higher levels of interpersonal harmony. The relationship between perceived risks and hazards, a hindrance job demand and task performance became positive as interpersonal harmony increased but negative as interpersonal harmony decreased.
Originality/value
This paper provides a robust integrative theoretical framework that better explains the various types of job demands and job resources in the working environment of coal mining sector in China and their relationships to employee performance. The findings also offer valuable guidance for managers trying to identify effective ways to enhance employee performance and safety in the workplace.
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