Most recent issue published online in the International Journal of Advanced Operations Management.
International Journal of Advanced Operations Management
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International Journal of Advanced Operations Management
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International Journal of Advanced Operations Management
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http://www.inderscience.com/browse/index.php?journalID=340&year=2023&vol=15&issue=3
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Recruitment process outsourcing motivators: a study of the industrial sector
http://www.inderscience.com/link.php?id=135790
Recruitment process outsourcing (RPO) is considered a strategic need for every organisation for getting the success; to increase the efficiency and effectiveness of the resources, reduction of cost, improve the performance and long term sustainability of the organisation. This article aims to identify the most vital motivator factor that influences the outsourcing of recruitment and selection process and perception of employers regarding RPO motivators in the industrial sector. The sample has been collected from 400 respondents (200 employers each from the service and manufacturing sectors) for the study by using the convenience sampling method. For this purpose, analysis was done using descriptive statistics, confirmatory factor analysis through AMOS software, and independent sample t-test. After analysis, it was found that strategic factor is the most significant factor that influences RPO in the industrial sector among four factors: economic, strategic, innovative, and quality. A significant difference was found among employers' perceptions of RPO regarding innovative and quality factors across any type of industry.
Recruitment process outsourcing motivators: a study of the industrial sector
Poonam
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 189 - 206
Recruitment process outsourcing (RPO) is considered a strategic need for every organisation for getting the success; to increase the efficiency and effectiveness of the resources, reduction of cost, improve the performance and long term sustainability of the organisation. This article aims to identify the most vital motivator factor that influences the outsourcing of recruitment and selection process and perception of employers regarding RPO motivators in the industrial sector. The sample has been collected from 400 respondents (200 employers each from the service and manufacturing sectors) for the study by using the convenience sampling method. For this purpose, analysis was done using descriptive statistics, confirmatory factor analysis through AMOS software, and independent sample t-test. After analysis, it was found that strategic factor is the most significant factor that influences RPO in the industrial sector among four factors: economic, strategic, innovative, and quality. A significant difference was found among employers' perceptions of RPO regarding innovative and quality factors across any type of industry.]]>
10.1504/IJAOM.2023.135790
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 189 - 206
Shirsendu Das
Swarup Paul
Biswanath Doloi
Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India
recruitment process outsourcing
RPO
recruitment process outsourcing motivators
manufacturing sector
service sector
India
2024-01-05T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
15
3
189
206
2024-01-05T23:20:50-05:00
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New models for the two-sided assembly line balancing problem
http://www.inderscience.com/link.php?id=135791
In this paper, we are interested in the two-sided assembly line balancing problem. This type of configuration is typically used to produce large-size high-volume products such as those in the automotive industry. We consider the minimisation of the line cycle time. We propose two mathematical models for this problem: a mixed integer linear programming model and a constraint programming model. A comparative study shows the efficiency of our models and the complementary between linear programming and constraint programming. The study also indicates that the density of precedence relations between the tasks determines the instances' hardness.
New models for the two-sided assembly line balancing problem
Meriem Mejri; Sana Bouajaja; Hatem Hadda; Najoua Dridi
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 207 - 223
In this paper, we are interested in the two-sided assembly line balancing problem. This type of configuration is typically used to produce large-size high-volume products such as those in the automotive industry. We consider the minimisation of the line cycle time. We propose two mathematical models for this problem: a mixed integer linear programming model and a constraint programming model. A comparative study shows the efficiency of our models and the complementary between linear programming and constraint programming. The study also indicates that the density of precedence relations between the tasks determines the instances' hardness.]]>
10.1504/IJAOM.2023.135791
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 207 - 223
Meriem Mejri
Sana Bouajaja
Hatem Hadda
Najoua Dridi
Université de Tunis El Manar, Ecole Nationale d'Ingénieurs de Tunis, OASIS, BP 37, Le belvédère, Tunis 1002, Tunisia ' Université de Tunis El Manar, Ecole Nationale d'Ingénieurs de Tunis, OASIS, BP 37, Le belvédère, Tunis 1002, Tunisia ' Université de Tunis El Manar, Ecole Nationale d'Ingénieurs de Tunis, OASIS, BP 37, Le belvédère, Tunis 1002, Tunisia ' Université de Tunis El Manar, Ecole Nationale d'Ingénieurs de Tunis, OASIS, BP 37, Le belvédère, Tunis 1002, Tunisia
line balancing
two-sided assembly line
mixed integer linear programming
MILP
constraint programming
2024-01-05T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
15
3
207
223
2024-01-05T23:20:50-05:00
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Impacts of pandemics on supply chains: lessons learned, transition, and future
http://www.inderscience.com/link.php?id=135800
The major epidemics and pandemics, which have affected supply chains include MERS, H1N1, SARS, Ebola, and Zika. The most recent pandemic, which has influenced today's intertwined supply chains, is COVID-19, which disrupted the global supply chains. Common impacts include manufacturing disruption, work backlog, and supply issues. This paper aims to study these impacts, identify similarities and differences between the impacts of these pandemics, and develop practical recommendations. This paper systematically reviews the previous work on the effects of epidemics and pandemics on supply chains. In particular, it compares COVID-19 with other recent pandemics and epidemics. This paper aims to help businesses see how their supply chains could affect lead-time, supply and demand, financial management, and delivery. Furthermore, it proposes actionable recommendations to supply chain managers.
Impacts of pandemics on supply chains: lessons learned, transition, and future
Nima Zaerpour; Amir Gharehgozli; Sonia Siddique; Phuong Dung Dao
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 224 - 247
The major epidemics and pandemics, which have affected supply chains include MERS, H1N1, SARS, Ebola, and Zika. The most recent pandemic, which has influenced today's intertwined supply chains, is COVID-19, which disrupted the global supply chains. Common impacts include manufacturing disruption, work backlog, and supply issues. This paper aims to study these impacts, identify similarities and differences between the impacts of these pandemics, and develop practical recommendations. This paper systematically reviews the previous work on the effects of epidemics and pandemics on supply chains. In particular, it compares COVID-19 with other recent pandemics and epidemics. This paper aims to help businesses see how their supply chains could affect lead-time, supply and demand, financial management, and delivery. Furthermore, it proposes actionable recommendations to supply chain managers.]]>
10.1504/IJAOM.2023.135800
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 224 - 247
Nima Zaerpour
Amir Gharehgozli
Sonia Siddique
Phuong Dung Dao
College of Business Administration, California State University, San Marcos, CA, USA ' College of Business and Economics, California State University, Northridge, CA, USA ' College of Business Administration, California State University, San Marcos, CA, USA ' College of Business Administration, California State University, San Marcos, CA, USA
supply chain disruption
pandemics
epidemics
COVID-19
competitive advantage
2024-01-05T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
15
3
224
247
2024-01-05T23:20:50-05:00
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Analysing the imperfect production model for decaying products with advertisement and stock dependent demand
http://www.inderscience.com/link.php?id=135806
This study examines the impact of inflation on trade credit period under an imperfect production model for decaying products with advertisement and stock-dependent demand. The model takes into account the impact of inflation on various cost components, including production, ordering, and holding costs, as well as the effect of the trade credit period on demand and cash flow. The created items have been inspected for imperfections, but the production rate is better than the screening rate. The study highlights the interplay between inflation and other parameters such as advertising efforts and stock levels in determining optimal trade credit policies that maximise the firm's profits. The results suggest that inflation has a significant impact on trade credit period, and firms need to adjust their trade credit policies to remain competitive in an inflationary environment. The study provides valuable insights for firms operating in the context of decaying products and highlights the importance of considering inflation in trade credit policy decisions. A solution process is provided to establish the most favourable ordering policy. Finally, sensitivity analysis on different parameters has been approved.
Analysing the imperfect production model for decaying products with advertisement and stock dependent demand
Rinki Chaudhary; S.R. Singh; Karuna Rana
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 248 - 269
This study examines the impact of inflation on trade credit period under an imperfect production model for decaying products with advertisement and stock-dependent demand. The model takes into account the impact of inflation on various cost components, including production, ordering, and holding costs, as well as the effect of the trade credit period on demand and cash flow. The created items have been inspected for imperfections, but the production rate is better than the screening rate. The study highlights the interplay between inflation and other parameters such as advertising efforts and stock levels in determining optimal trade credit policies that maximise the firm's profits. The results suggest that inflation has a significant impact on trade credit period, and firms need to adjust their trade credit policies to remain competitive in an inflationary environment. The study provides valuable insights for firms operating in the context of decaying products and highlights the importance of considering inflation in trade credit policy decisions. A solution process is provided to establish the most favourable ordering policy. Finally, sensitivity analysis on different parameters has been approved.]]>
10.1504/IJAOM.2023.135806
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 248 - 269
Rinki Chaudhary
S.R. Singh
Karuna Rana
Department of Mathematics, C.C.S. University, Meerut, India ' Department of Mathematics, C.C.S. University, Meerut, India ' Department of Mathematics, C.C.S. University, Meerut, India
imperfect production
screening process
inflation
advertisement and stock-reliant demand
permissible delay period
2024-01-05T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
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248
269
2024-01-05T23:20:50-05:00
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Multi-objective optimisation for stochastic inventory model using grey wolf optimiser
http://www.inderscience.com/link.php?id=135803
This paper presents a multi-item and multi-period inventory management model to optimise inventory costs and storage space under budget constraints. To minimise the total inventory costs and the storage space, the framework of an integer nonlinear programming model is presented based on random demands. In addition, a multi-objective grey wolf optimisation (MOGWO) approach is employed to realise the optimal inventory management system. The effectiveness of solutions from MOGWO is also verified using numerical examples based on four different scenarios. Unlike previous approaches in inventory management that only consider a single-objective optimisation problem, this approach aims to optimise inventory costs and storage space utilisation simultaneously. The supply chain performance can be significantly enhanced through visibility. With excellent decision-making schemes powered by optimisation algorithms, inventory management software can react to an ever-fluctuating production flow and anticipate the need for changes in a firm's policies.
Multi-objective optimisation for stochastic inventory model using grey wolf optimiser
Nguyen Duy Tan; Hwan-Seong Kim; Le Ngoc Bao Long; Duy Anh Nguyen; Sam-Sang You
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 270 - 292
This paper presents a multi-item and multi-period inventory management model to optimise inventory costs and storage space under budget constraints. To minimise the total inventory costs and the storage space, the framework of an integer nonlinear programming model is presented based on random demands. In addition, a multi-objective grey wolf optimisation (MOGWO) approach is employed to realise the optimal inventory management system. The effectiveness of solutions from MOGWO is also verified using numerical examples based on four different scenarios. Unlike previous approaches in inventory management that only consider a single-objective optimisation problem, this approach aims to optimise inventory costs and storage space utilisation simultaneously. The supply chain performance can be significantly enhanced through visibility. With excellent decision-making schemes powered by optimisation algorithms, inventory management software can react to an ever-fluctuating production flow and anticipate the need for changes in a firm's policies.]]>
10.1504/IJAOM.2023.135803
International Journal of Advanced Operations Management, Vol. 15, No. 3 (2023) pp. 270 - 292
Nguyen Duy Tan
Hwan-Seong Kim
Le Ngoc Bao Long
Duy Anh Nguyen
Sam-Sang You
Department of Logistics, Korea Maritime and Ocean University, Busan, South Korea ' Department of Logistics, Korea Maritime and Ocean University, Busan, South Korea ' Department of Logistics, Korea Maritime and Ocean University, Busan, South Korea ' Department of Mechatronics Engineering, Ho Chi Minh City University of Technology (HCMUT), Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam ' Department of Mechanical Engineering, Northeast-Asia Shipping and Port Logistics Research Center, Korea Maritime and Ocean University, Busan, South Korea
multi-item multi-period inventory
stochastic demand
grey wolf optimiser
GWO
multi-objective optimisation
2024-01-05T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
15
3
270
292
2024-01-05T23:20:50-05:00