Selling green first or not? A Bayesian analysis with service levels and environmental impact considerations in the Big Data Era

Shen, Bin; Choi, Tsan‐Ming; Chan, Hau‐Ling

doi:10.1016/j.techfore.2017.09.003

Cited by 79 publications

(43 citation statements)

References 33 publications

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“…Choi [46], Chan et al [47] and Shen et al [48] are three exceptions that consider the sustainability issues with Bayesian information updating. Specifically, Choi [46] studies a quick response strategy with the consideration of carbon footprint tax and Bayesian information updating.…”

Section: (3) Bayesian Information Updatingmentioning

confidence: 99%

“…Specifically, Choi [46] studies a quick response strategy with the consideration of carbon footprint tax and Bayesian information updating. Shen et al [48] investigate the selling sequence of the green and non-green products by using the Bayesian information updating approach. Both Choi [46] and Shen et al [48] do not consider the sustainable investment and consumer environmental awareness, which are salient features of our study.…”

Section: (3) Bayesian Information Updatingmentioning

confidence: 99%

“…Shen et al [48] investigate the selling sequence of the green and non-green products by using the Bayesian information updating approach. Both Choi [46] and Shen et al [48] do not consider the sustainable investment and consumer environmental awareness, which are salient features of our study. Chan et al [47] investigate the supply chain coordination by Bayesian information updating approach with the consideration of sustainable investment.…”

Section: (3) Bayesian Information Updatingmentioning

confidence: 99%

“…In order to capture the characteristics of demand forecast, we consider a Bayesian information updating model. Similar to Chan et al [47] and Shen et al [48], we consider the forecasted base demand of the products in two stages. Let x 0 denote the forecasted base demand of the products at Stage 0.…”

Section: Bayesian Information Updatingmentioning

confidence: 99%

“…We assume that up to Stage 1, the retailer can obtain sufficient amount of data from the market to improve the demand forecast. Following Choi [50] and Shen et al [48], we define n as the number of market observations, which represents the market information that the retailer can use to improve the demand forecast. In the big data era, n could be very large and it tends to infinity when the market observation is real-time [48].…”

Section: Bayesian Information Updatingmentioning

confidence: 99%

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Sustainable Investment in a Supply Chain in the Big Data Era: An Information Updating Approach

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Abstract:We are now living in the big data era, where firms can improve their decision makings by adopting big data technology to utilize mass information. To explore the effects of the big data technology, we build an analytical model to study the sustainable investment in a supply chain, consisting of one manufacturer and one retailer, by using Bayesian information updating approach. We derive the optimal sustainable investment level for the manufacturer and the optimal order quantity for the retailer. Comparing the results with and without the big data technology, we find that whether the manufacturer should make more sustainable investment when the retailer adopts the big data technology depends on the service level at the retailer side. Interestingly, it is not always optimal for the retailer to adopt the big data technology. We identify the conditions under which the manufacturer and retailer are better off with the big data technology. In addition, we investigate the impact of the number of observations regarding the market information and find that the optimal decisions and profits increase in the number of the observations, if and only if the service level is low.

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Section: (3) Bayesian Information Updatingmentioning

confidence: 99%

Section: (3) Bayesian Information Updatingmentioning

confidence: 99%

Section: (3) Bayesian Information Updatingmentioning

confidence: 99%

Section: Bayesian Information Updatingmentioning

confidence: 99%

Section: Bayesian Information Updatingmentioning

confidence: 99%

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Sustainable Investment in a Supply Chain in the Big Data Era: An Information Updating Approach

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The interplay between blockchain adoption and green operations for a firm

Zhang,

Zhu,

Zhang

2024

Manage Decis Econ

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This study considers a firm selling only green products or both ordinary and green ones to consumers with or without blockchain technology. We find that the profitability of adoption of this technology for the firm relies heavily on consumers' environmental awareness. It should be adopted when consumers have relatively high environmental awareness. Here, the selling price, sales, and greenness level of green products are relatively higher compared to those in the case without blockchain. Finally, the firm only sells green products after blockchain adoption when consumers' environmental awareness level is relatively high or the development cost coefficient of green products is relatively small.

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Creative Concept of Visual Communication Art Design in the Era of Big Data

Wang

Pan

2021

Advances in Intelligent Systems and Computing

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Selling green first or not? A Bayesian analysis with service levels and environmental impact considerations in the Big Data Era

Cited by 79 publications

References 33 publications

Sustainable Investment in a Supply Chain in the Big Data Era: An Information Updating Approach

Sustainable Investment in a Supply Chain in the Big Data Era: An Information Updating Approach

The interplay between blockchain adoption and green operations for a firm

Creative Concept of Visual Communication Art Design in the Era of Big Data

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