Optimal timing of big data application in a two-period decision model with new product sales

Yang, Lei; Jiang, Anqian; Zhang, Jiahua

doi:10.1016/j.cie.2021.107550

Cited by 6 publications

(1 citation statement)

References 55 publications

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“…In the era of big data, massive amounts of data are collected, stored, transferred, and processed [6][7][8]. Leveraging big data helps companies to improve the quality and agility of decision-making and brings great business value.…”

Section: Introductionmentioning

confidence: 99%

Flexible supplier selection and order allocation in the big data era with various quantity discounts

Wang

2023

PLoS ONE

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This paper studies the flexible large-scale supplier selection and order allocation problem with various quantity discounts, i.e., no discount, all-unit discount, incremental discount, and carload discount. It fills a literature gap that models usually formulate one or seldom two types because of the modeling and solution difficulty. All suppliers offering the same discount are far from reality, especially when the number of suppliers is large. The proposed model is a variant of the NP-hard knapsack problem. The greedy algorithm, which solves the fractional knapsack problem optimally, is applied to cope with the challenge. Three greedy algorithms are developed using a problem property and two sorted lists. Simulations show the average optimality gaps are 0.1026%, 0.0547%, and 0.0234% and the model can be solved in centiseconds, densiseconds, and seconds for supplier numbers 1000, 10000, and 100000. This allows the full use of data in the big data era.

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Section: Introductionmentioning

confidence: 99%

Flexible supplier selection and order allocation in the big data era with various quantity discounts

Wang

2023

PLoS ONE

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Data science and big data analytics: a systematic review of methodologies used in the supply chain and logistics research

2023

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Data science and big data analytics (DS &BDA) methodologies and tools are used extensively in supply chains and logistics (SC &L). However, the existing insights are scattered over different literature sources and there is a lack of a structured and unbiased review methodology to systematise DS &BDA application areas in the SC &L comprehensively covering efficiency, resilience and sustainability paradigms. In this study, we first propose an unique systematic review methodology for the field of DS &BDA in SC &L. Second, we use the methodology proposed for a systematic literature review on DS &BDA techniques in the SC &L fields aiming at classifying the existing DS &BDA models/techniques employed, structuring their practical application areas, identifying the research gaps and potential future research directions. We analyse 364 publications which use a variety of DS &BDA-driven modelling methods for SC &L processes across different decision-making levels. Our analysis is triangulated across efficiency, resilience, and sustainability perspectives. The developed review methodology and proposed novel classifications and categorisations can be used by researchers and practitioners alike for a structured analysis and applications of DS &BDA in SC &L.

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Adoption time of a maturing disruptive technology in a duopoly market

Sun

Lin

2021

RAIRO-Oper. Res.

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New disruptive technologies invalidate the traditional competition dimension in continuous innovation and reconstruct the competitive landscape. These technologies leave a management gap in the adoption of new technologies by competing companies. Accordingly, this research establishes a duopoly game model based on horizontal and vertical differentiations for technology competition problems with asymmetric features. Competition between firms and technologies are investigated simultaneously. We find that a profit increase from new technologies is typically eliminated by the increased technology competition. Thus, firms with competitive advantages in the old market may be late in adopting new technologies, and the competition will further delay the adoption process. We then introduce a preemption strategy for adopting disruptive technologies, and test it in both current established competition and threat competition from the entrants. Results show that leading companies may hesitate in deterring new entrants for fear of losing the leadership in the current competition. At last, we provide a time strategy that can help the market leader maintain a leadership position with minimal losses. Our research has contributed to the studies of both the interpretation of the “innovator's dilemma” and the direction of technology adoption research under multi-dimensional technologies and multiple competitors.

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Optimal timing of big data application in a two-period decision model with new product sales

Cited by 6 publications

References 55 publications

Flexible supplier selection and order allocation in the big data era with various quantity discounts

Flexible supplier selection and order allocation in the big data era with various quantity discounts

Data science and big data analytics: a systematic review of methodologies used in the supply chain and logistics research

Adoption time of a maturing disruptive technology in a duopoly market

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