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Retail sales usually exhibit strong trend and seasonal patterns. Practitioners have typically used seasonal autoregressive integrated moving average (ARIMA) models to predict retail sales exhibiting these patterns. Due to economic instability, recent retail sales time-series data show a higher degree of variability and nonlinearity, which makes the ARIMA model less accurate. This chapter demonstrates the feasibility and potential of applying empirical mode decomposition (EMD) in forecasting aggregate retail sales. The hybrid forecasting method of integrating EMD and neural network (EMD-NN) models was applied to two real data sets from two different time periods. The one-period ahead forecasts for both time periods show that EMD-NN outperforms the classical NN model and seasonal ARIMA. In addition, the findings also indicate that EMD-NN can significantly improve forecasting performance during the periods in which macroeconomic conditions are more volatile.

The purpose of this paper is to develop an adoption model to identify the critical factors that affect firms' intention to adopt mobile enabled supply chain systems (mSCM) in retail industry. This study focuses on inter‐organizational dimension since mSCM is an inter‐organizational system that provides both inter‐ and intra‐organizational linkages for firms across the supply chain.

A survey method was used to test the proposed model. Data from this study were obtained from South Korean firms.

Supply chain awareness was shown to be a strong predictor of both inter‐organizational dependence and inter‐organizational trust which positively affects firms' long‐term relationship with their trading partners. Institutional pressures, long‐term relationship, and top management support also had a significant influence firms' mSCM adoption intention.

First, only executives and managers in retail industry of South Korea were surveyed, thus, the results may not be generalized to retail industry in other countries. Second, the current study focuses on a firm's mSCM adoption intention rather than actual adoption.

This study provides useful insights for practitioners to better manage institutional pressures and nurture long‐term relationship in order to promote co‐adoption of mSCM.

This study provides useful insights for supply chain members on how to overcome barriers to adopting an innovation and to increase the chance of successfully adopting mSCM in the retail supply chain.