Optimal inventory policies for short life cycle successive generations’ technology products

Nagpal, Gaurav; Chanda, Udayan

doi:10.1080/23270012.2021.1881922

Cited by 6 publications

(6 citation statements)

References 79 publications

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“…Therefore, we handled stochastic production lead time in our study. Furthermore, most of the researchers handled the single period (Nagpal & Chanda, 2022;Chen et al, 2015;Parlar, 1985;Pasternack & Drezner, 1991) or multi-period inventory problem with substitution where the demand and lead time are usually deterministic and the inventory review is periodic. They used mathematical programming approaches, calculus or heuristic methods as solution methodology.…”

Section: Related Literaturementioning

confidence: 99%

“…On the other hand, it is obvious that frequent innovations cause overproduction which leads to the waste of natural resources and the growth of e-waste (Nagpal & Chanda, 2022;Pal & Sana, 2022). Today, air pollution, water pollution and climate change are the major environmental problems and adopting green practices has become one of the core responsibilities of the companies (Taleizadeh et al, 2020;Sana, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Part transformation-based spare parts inventory control model for the high-tech industries

Güçdemir,

Taşoğlu

2024

10.5267/j.ijiec

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Timely and cost-effective supply of spare parts is the main purpose of spare parts inventory management and substitution is an effective way to fulfill demand on time. However, direct substitution of spare parts is not suitable for the high-tech industries due to the ever-changing nature of the product structures. Hence, parts should be transformed to be used as substitutes. This paper provides a novel spare parts inventory control model for the high-tech industries. In the proposed model, part transformation-based substitution is considered and the near-optimal values of spare part inventory levels (s, S) that minimize total cost are determined by using a simulated annealing-based simulation optimization approach. Computational analyses are performed for a hypothetical inventory system by considering transformation and no-transformation cases. The results reveal that transformation is very useful for the companies who endure long production lead times and high penalty costs associated with backorders.

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Section: Related Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Part transformation-based spare parts inventory control model for the high-tech industries

Güçdemir,

Taşoğlu

2024

10.5267/j.ijiec

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“…Li [24,39] studied inventory planning during the transition period of multi-generation products, focusing on the substitution effect and pricing between old and new products. Nagpal et al [42] built an EOQ model for successive multi-generation product-diffusion scenarios; however, their model did not include production. Specifically, Ruidas et al [43] conducted extensive and in-depth research on the multi-generation product renewal problem and proposed a model that incorporates factors such as price, advertising, demand disruption, product substitution, inventory, and production and provides the optimal inventory and pricing strategy under carbon emissions trading.…”

Section: Production and Inventory In The Diffusion Processmentioning

confidence: 99%

Modeling and simulating the multi-generation product sales, production and inventory system within the context of quality upgrades

Bo,

Yuan,

2024

PLoS ONE

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The rapid development of science and technology has led to an increasing number of high-tech enterprises offering new products through successive generations of product upgrades. This trend presents a new challenge for the sustainable operations of enterprises. Based on the Norton-Bass model, this study begins by constructing a multi-generation product diffusion model within a single enterprise in the context of a monopoly under the quality upgrade scenario. Subsequently, a supply model is established based on this foundation, and these two models are seamlessly integrated using product sales volume as an interface, culminating in a comprehensive sales-supply system. This study analyzes the effects of new-product pricing, quality levels, initial stock, and production capacity on the performance of this system. The system dynamics (SD) method was used to simulate and solve the system in the decentralized and centralized decision-making modes, and the two decision-making modes were compared and analyzed. The research reveals several key findings. i) Comprehensive decision optimization yields enhanced profitability through joint optimization calculation of the multi-generation product diffusion system and the supply adjustment system. ii) consumer price sensitivity significantly affects product quality upgrades and profits. A negative correlation exists between consumer price sensitivity and both factors. The upgrades of product quality should be carefully traded off with consideration of pricing and quality costs. iii) Maximizing profits by maintaining a certain order level of backlog or stock shortage is beneficial for overall enterprise profitability. Additionally, optimal production capacity has been identified as a crucial element in efficient operational inventory management. This study expands the multi-generation product diffusion operational theory and provides valuable theoretical support and decision-making foundations for the sustainable management of enterprises.

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“…The theory suggests that the success of an innovation depends on how it is implemented (Xia et al, 2022). More specifically, a complete and accurate inventory system can set the groundwork for implementing product innovation and contribute to the success of new products (Nagpal and Chanda, 2022). Similarly, new product launches may introduce new technologies to improve inventory management.…”

Section: Inventory Leanness and Product Innovation 1377mentioning

confidence: 99%

The relationship between inventory leanness and product innovation with the contingent role of market concentration

Wang,

Yao,

Zhu

2023

JMTM

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PurposeThis study aims to demonstrate the simultaneous effects between inventory leanness and product innovation, with market concentration being a moderator.Design/methodology/approachUsing a large panel data collected from 3071 listed manufacturing enterprises from 2004 to 2021, this research employs a simultaneous system of equations via the three-stage least square method to explore the simultaneous relationship between inventory leanness and product innovation. In addition, the moderating role of market concentration is demonstrated via one four-model system.FindingsAs its core, inventory leanness positively impacts product innovation, while product innovation negatively affects inventory leanness. Moreover, there are differential impacts of the leanness of three inventory types on product innovation. Specifically, the inventory leanness of raw material negatively affects product innovation, while the inventory leanness of work-in-process and finished goods positively affect product innovation. Further, moderation analysis highlights that market concentration is a key moderator of this relationship.Practical implicationsManagers should carefully gauge the tradeoffs between inventory leanness and product innovation. Concretely, managers ought to consider the connections between inventory types and product innovation. In addition, managers are suggested to emphasis on market strategy.Originality/valueThis paper not only contributes to the current understanding of inventory leanness by verifying the impact of inventory leanness on product innovation but also investigates the simultaneous relationship between various inventory types and product innovation. Furthermore, it empirically demonstrates the moderating effect of market concentration on the relationship between inventory leanness and product innovation.

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Optimal inventory policies for short life cycle successive generations’ technology products

Cited by 6 publications

References 79 publications

Part transformation-based spare parts inventory control model for the high-tech industries

Part transformation-based spare parts inventory control model for the high-tech industries

Modeling and simulating the multi-generation product sales, production and inventory system within the context of quality upgrades

The relationship between inventory leanness and product innovation with the contingent role of market concentration

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