Main Research Question

Generally CPFR, either fully or partly, is adopted by companies to accomplish their business goals. As mentioned in the literature review (Chapter 2), businesses can achieve several benefits by collaborating with other supply chain partners (Chung and Leung 2005; Simatupang and Sridharan, 2004 a,b). But, the specific role of supply chain information and its impact on production planning or forecasting are not clearly stated in the literature. In order to fill this gap, this research focuses on understanding the collaborative arrangements in different industries and the need of information exchange for better forecasting and planning. Accordingly the main research question can be formulated as follows:

What is the role of information exchange in collaborative supply chains for demand forecasting?

The main research question will be answered in four steps.

This research begins by defining the nature of the collaboration and the subsequent information exchange in supply chain processes in a form of a process map (Handfield and Melnyk, 1998). In this process, four sub-questions are formulated:

Question 1: What types of collaborative arrangement exist between manufacturers and buyers, and what type of information is being exchanged to facilitate CPFR?

This first question is based on the observation from the literature that the collaborative arrangement between manufacturers and retailers was inadequately addressed. The reported benefits of supply chain collaboration are of wide range and include inventory reduction, cost reduction or reduction of lead time. However, there was no mention of what type of collaborative arrangement and SC information exchange helped to achieve specific supply chain benefits. For example, from the literature it is difficult to understand the role of information exchange in forecasting the sales promotions.

Some researchers attempted to relate information exchange with supply chain benefits such as inventory control and cost reductions (Lee et al., 2000; Raghunathan, 2001; Aviv, 2007). But those articles did not explain in detail when and how this data was exchanged and what the significance of this data in different supply chain processes was. Hence, it is vital to understand the impact of supply chain collaboration and information exchange in practice. This will help to comprehend the actual collaborative arrangement and the role of information exchange for production planning, forecasting and replenishment. The case study approach will be employed to answer this question.

Question 2: What techniques can be used to decide on the level of information exchange in CPFR?

The second question considers the information exchange among suppliers and buyers involved in supply chain collaboration. Two different viewpoints have been raised in the literature (Lee et al., 2000; Raghunathan, 2001; Nakano, 2009). One is that POS data helps forecasting and another is that POS data confuses the forecasters. As given in the literature review in Section 2.4, Raghunathan (2001) criticised the investment on technology for exchange of POS data, provided historical data was used for forecasting. In most of the companies, POS data is not used for their forecasts. In many cases only the historical sales data is been used for forecasting. However, POS data may be required to monitor performance of sales against the forecasts during the promotional sales events. The inventory data may also be required to decide on replenishment plans. Likewise several partners of the supply chain may require a variety of SC information specific to their business.

Hence, by answering the proposed research question, it is possible to identify the different factors and signals that explain the demand. This will benefit the companies, particularly involved in sales promotions, to implement various promotional mechanisms in line with the identified factors underlying the demand. Based on the inputs from the case studies, a conceptual model called ‗Reference Demand Model‘ is developed to answer this question.

Question 3: How are the different demand factors related to sales?

Question 3 reflects the fact that forecasters and/or decision makers need to understand the underlying relationship of factors with sales. This will assist them in understanding the

importance of information exchange. While information exchange among supply chain members involves both technology and people, the technology attracts some additional investment. Hence, investment in technology has been questioned by many researchers in the aspect of its contribution to profit (Raghunathan, 2001; Smaros, 2007). This research is trying to identify the relationship among various demand factors and their impact on sales. Though this research does not suggest anything on technology investments, the research findings may assist management decisions for future collaborative arrangement. This research question is answered by constructing ‗structural equal models‘ to identify the underlying structure of demand factors.

Question 4: Can the identified demand factors from RDM help to improve forecast accuracy?

Question 4 relates to the core idea in previous research that collaborative forecasting may improve accuracy, especially when the lead time is shorter (Aviv, 2002). This research relates the previous findings with the actual practice of supply chain collaboration through case studies. The quality and value of information exchange have been widely discussed in the context of organisational resistance for collaboration (Paulraj et al., 2008; Samros, 2007). Some analytical models have been developed to see the impact of information exchange by assuming stable demand (Gavirneni et al., 1999; Aviv, 2007). But, in practice, the demand is not always stable, especially during promotions. Hence, answering the question 4 will be ideal for decision making on the level of collaboration. This question 4 is answered by developing multivariate regression forecast models.

By answering questions 1 to 4, the main research question will be answered. The research conducted for answering these questions will also suggest an ideal collaborative arrangement for all the case companies studied.