CHAPTER 2: LITERATURE REVIEW
2.2 The credibility of forecast sharing
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results show that both the manufacturer and the retailer can benefit from information sharing in the make-to-stock scenario. Other literature examined forecast sharing in different context. Spiliotopoulou et al. (2016) examined whether demand forecast sharing between retailers and a benevolent central planner is reliable both in theory and in practice where inventory decisions are made at a centralized level relying on demand forecast information passed from regional managers within a supply chain. Terwiesch et al. (2005) empirically studied the relationship of buyer’s forecasting behavior and semiconductor equipment suppliers’ delivery performance in the semiconductor equipment supply chain. Gümüş (2014) studied the impact of forecast sharing on the decisions, profits and costs of channel partners in a supply chain model with a buyer facing a demand risk and two suppliers competing for order allocation from the buyer.
Most research before focused on the impact of forecast sharing on retailers and manufacturers. Such as under what conditions could be beneficial for both retailer and manufacturers (Yue & Liu, 2006) to share demand forecasts. Unlike them, our research focuses on examining forecast information sharing between an electronic device manufacturer and a semiconductor distributor. We empirically investigate the impacts of forecast sharing from an electronic device manufacturer on the distributor’s performance which is specified as inventory and sales in a semiconductor supply chain.
2-2 The credibility of forecast sharing
There is a growing body of literature on the role of trust and trustworthiness in information sharing and supply chain performance. The credibility of forecast sharing is getting attention in supply chain management (Ozer, Zheng, Chen, 2011; Voigt and Inderfurth, 2012; Ebrahim‐Khanjari, Hopp, & Iravani, 2012; Hyndman, Kraiselburd, Watson, 2013; Inderfurth,Sadrieh, Voigt, 2013; Gümüş, 2014; Spiliotopoulou, Donohue
& Gürbüz, 2016; Fu, Dong, Liu, & Han, 2016). Our research focuses on what factors
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can impact the credibility of forecast. According to previous research, supply chain complexity, which is categorized as internal and external complexity, can impact manufacturing plant performance (Bozarth, Warsing & Flynn, 2009). We therefore assume that supply chain complexity of semiconductor distributor can also impact the credibility of forecast in inventory and sales management. Internal complexity of manufacturing plant was defined as complexity resulting from within the plant such as number of products, number of parts and low volume batch productions etc. While external complexity of manufacturing was defined as complexity resulting from connections with downstream and upstream partners such as demand variability, number of suppliers and long and unreliable supplier lead times etc. (Bozarth, Warsing
& Flynn, 2009). In our research, internal complexity is defined as order diversification, the order structure in customer’s hubs managed by the distributor. While external complexity is defined as forecast fluctuation resulting from customers’ forecast behavior. Previous literature also examined factors that affect the credibility of forecast.
Some of them are related to external complexity, while the others are regarding internal complexity.
Literatures regarding to external complexity factors that affected the credibility and supply chain performance are as below. Özer and Wei (2006) are the first to analyze the credibility of the forecast sharing between a supplier and a manufacturer. They suggested different degree of forecast information asymmetry, which was the external complexity resulting from the connections between the supply chain members, affected the contract type should be adopted to enable credible forecast sharing between the supplier and a manufacturer. The forecast information asymmetry degree was categorized as symmetry, low asymmetry, and high asymmetry. In addition, Gümüş (2014) studied when and how a buyer could credibly share his forecast information with his upstream suppliers, and how it impacted on the intensity of price competition. In
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the study, the degree of demand information asymmetry, which was an external complexity, could affect when and how a credible forecast sharing could be sustainable.
They found out that the buyer could use a procurement mechanism called request for quotation (RFQ) with quantity restrictions as a credible signal for forecast sharing as long as the degree of demand information asymmetry was not too high. They also found out that under asymmetric information, the equilibrium prices that emerged between competing suppliers may indeed increase if the buyer could not share forecast information credibly with its upstream partners. Oh and Özer (2013) investigated the role of time in forecast information sharing and decision making under uncertainty in a dynamic environment, where supplier had problem of eliciting credible forecast information from a manufacturer when both firms obtained forecast information over time. Time in the study was an external factor that indicated how long the supplier and manufacturer interacted with each other. The supplier relied on the demand forecast information to make capacity investment decisions. However, because the manufacturer had superior relationship with the market, she could get forward-looking information. Therefore, firms had asymmetric information that changed over time. The study examined what was the right time for the supplier to elicit credible information and make the capacity investment decision. Terwiesch et al. (2005) showed that supplier might not achieve potential performance improvements from forecast sharing because of buyer’s forecasting behavior: forecast inflation and forecast volatility. In the study, forecast inflation and forecast volatility were two external complexity resulted from buyer’s response to market demands. Also, the two factors affected the way the supplier acted to the forecast orders. The study suggested that if the customer changed the requested delivery more frequently, which was referred to as forecast volatility, the supplier was more likely to delay the order. Similarly, if the customer cancelled forecast orders more frequently in the past, which was referred as forecast inflation, the supplier
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was more likely to delay production. Spiliotopoulou et al. (2016) examined the reliability of demand forecast sharing in the context of one central planner and multiple retailers within a company. They found that the forecasts reported by regional managers are somewhat informative, and the planner partially used the forecast information to make and inform the aggregate inventory decision. However, inventory competition and demand uncertainty were two external factors that decreased the planner’s reliance on forecasts.
In addition to external complexity factors, research that examined internal complexity factors or both internal and external complexity is as followed. Fu et al.
(2016) proposed a quantitative method to study the trust relationship between a retailer and an agent in the supply chain where retailer procured the optimal quantity of a product from a suppler based on the demand forecast information shared by the agent.
They studied how retailer’s updated trust in the agents influence decisions of the retailer and the agent and their impacts on the supply chain performance. In the study, social characteristics of the agents was found to affect the decisions and supply chain performance. Social characteristics of the agents can be the internal complexity as it’s the different kind of nature of agents. Özer et al. (2011) examined the issue of forecast information sharing in a single supplier and manufacturer context. The suppliers somewhat depended on manufacturers’ forecast to make capacity decisions although manufacturers tended to inflate the forecasts. In the research, trust of forecast was affected by two factors, capacity costs and market uncertainty, which are internal complexity and external complexity. For example, when the capacity cost is low, the loss caused by trusting manufacturers’ forecasts is lower, so the suppliers tend to believe the reports from manufacturers. Therefore, manufacturers are less likely to inflate forecasts for sufficient supply, resulting in more effective forecast information sharing and cooperation in a supply chain. Lower market uncertainty can decrease forecast
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inflation and increase overall channel efficiency when capacity cost is high. In our research, we also examine the credibility of forecast sharing, and examine external and internal complexity factors that might affect the credibility of forecasts, and, hence impact distributor’s performance. However, unlike the literature mentioned above, we focus on the forecast sharing between semiconductor distributor and its customers instead of between retailers and manufacturers. Our research examines both external and internal complexity factors that affect the credibility of forecasts, which are forecast fluctuation and order diversification.