Information sharing in capacity constrained supply chains under lost sales

Despite the importance of supply chain learning for competitiveness, little is known about how to enable such learning. This study empirically investigates the impact of information sharing on different types of supply chain learning (internal, supplier, and customer learning) and their influences on flexibility performance. Grounded in absorptive capacity theory, we use structural equation modelling to test the conceptual model based on data collected from 213 manufacturing firms in China. We find that supplier and customer learning improve internal learning. Further, our findings indicate that information sharing improves all three dimensions of supply chain learning. We also find that internal and customer learning have direct influences on flexibility performance, whereas internal learning mediates the relationship between supplier learning and flexibility performance. Moreover, information sharing moderates the relationship between supplier learning and flexibility performance. Our findings contribute to the literature and offer a new framework to understand the relationship between information sharing, supply chain learning and flexibility performance. The findings also furnish managers to seek competitive advantage through information sharing and supply chain learning.

Section: Production Research Literature On Information Sharing Sc Lementioning

confidence: 99%

The impact of information sharing on supply chain learning and flexibility performance

Huo

Haq

2020

“…Results indicate that as the manufacturer's capacity increases, the benefit of sharing order policy information becomes greater because the supplier gains flexibility in scheduling production. More recently, Davis et al (2011) utilise a Markov decision process to evaluate the value of information sharing in a serial supply chain. In an environment where both the manufacturer and the retailer are capacitated and where there are lost sales, the authors determine that the supplier receives most of the benefit when information is shared, although the retailer benefits from a significant decrease in lost sales.…”

Section: Literature Reviewmentioning

confidence: 99%

The incremental value of central control in serial supply chains

Salzarulo

Jacobs

2013

We consider a two-echelon serial supply chain where a single manufacturer replenishes a single downstream customer who faces random, stationary and discrete demand. In this setting, we compare the performance of a traditional supply chain having no information sharing to one where the customer shares demand and inventory information with the manufacturer. We also consider the case of central control where the manufacturer has full control over replenishments. This full information sharing with control by the manufacturer captures what has been called a vendor-managed inventory scenario in the literature. In order to estimate the performance of these three supply chain scenarios, we utilise renewal theory to develop probability models for each. A computational analysis of the models determines the benefit which information sharing offers as well as the incremental benefit central control provides beyond that of information sharing alone, a value which has not typically been considered in the literature despite its importance. Results indicate central control offers a 4.0% improvement over the no-information sharing setting; however, information sharing alone accounts for some of that benefit, offering an average cost savings of 1.8% compared to the no-information sharing setting. We then conclude that central control offers only an additional 2.2% benefit over the information sharing setting.Keywords: supply chain management; vendor-managed inventory; value of information; central control IntroductionFirms have traditionally made their own inventory control decisions, including the timing of shipments and order quantities. However, a great deal of value may be obtained if a firm coordinates and shares information with its supply chain partners as it enables better decision-making with regards to ordering and production planning (Chan and Chan 2010). The academic literature has investigated such partnerships to determine the benefit offered but findings are often inconsistent (Cachon and Fisher 2000;Li and Wang 2007). For example, Gavirneni, Kapuscinski, and Tayur (1999) report that sharing information on the retailer's ordering policy and point-of-sale data can improve system performance by 1-35%. Fry, Kapuscinski, and Olsen (2001) found that costs could be reduced by up to 23%. In contrast, Chen (1998) reports more conservative results, finding that the benefit of using demand information and echelon stock policies leads to an average benefit of only 1.75%, while Cachon and Fisher (2000) found savings of approximately 2.2%.There are several reasons for the wide range of results found in studies which investigate the value of information combined with the use of centralised control. The most obvious reasons are the structure of the supply chain being investigated, the replenishment logic employed and the parameter levels used in the mathematical and simulation models (Gavirneni 2001). Studies in this area have typically established the value of information by comparing a model having full information sharing to a ...

“…Wu et al (2011) study a two-level supply chain consisting of two competing suppliers and one buyer, and evaluate the benefits of sharing information on suppliers product quality with the buyer using game theory. Davis et al (2011) consider a two-stage capacity-constrained supply chain consisting of a supplier and a retailer. They quantify the value of information sharing and construct several performance measures to identify the benefits to both the retailer and supplier as a result of the information sharing partnership.…”

Section: Literature Reviewmentioning

confidence: 99%

The value of updated information on future price behaviour

Liao¹,

Zequeira²,

Seifert³

2013

This paper studies the value of information on future price behaviour. We consider a one-period inventory modelling framework with random period length and two order opportunities. The selling price is determined dynamically and the demand is price-sensitive. The second ordering-pricing decision reflects the updated information on future price behaviour on supply chain flexibility. We consider three models with different levels of flexibility: the static model, the quantity flexible model and the combined quantity and timing (fully) flexible model. We compare between the values of three different features in the supply chain: updated information on price behaviour, dynamic pricing and supply flexibility. And we demonstrate the effect of holding cost and demand uncertainty on these three values. We also consider a specific condition with fixed selling prices. We give explicit analysis on the optimal order decisions, and analytically show the impact of information and quantity flexibility on the optimal order decisions.