Customer information systems for deregulated ASEAN countries

In similar fashion to western countries, ASEAN countries are also gearing up towards deregulation. Despite potentially different motivating drivers, the ultimate objectives are free market competition leading to efficient pricing signals as well as providing customers with the freedom to choose their electricity provider and benefit from competitive prices. This paper provides an ASEAN electricity market analysis and describes the development of electricity deregulation in ASEAN countries. By way of background it also highlights the objectives of deregulation, the potential challenges and also the impact areas focusing on existing Customer Information Systems (CIS) that have been developed by other utilities. In addition, this paper proposes a new framework for improving CIS for ASEAN utilities facing deregulation. The framework outlines a CIS, which has intelligent features enabling the utility to estimate and predict customer behaviour with respect to consumption patterns. It describes how these features can assist the utility companies to retain their existing customers as well as attract more customers

Development of an intelligent analytics-based model for product sales optimisation in retail enterprises

A retail enterprise is a business organisation that sells goods or services directly to consumers for personal use. Retail enterprises such as supermarkets enable customers to go around the shop picking items from the shelves and placing them into their baskets. The basket of each customer is captured into transactional systems. In this research study, retail enterprises were classified into two main categories: centralised and distributed retail enterprises. A distributed retail enterprise is one that issues the decision rights to the branches or groups nearest to the data collection, while in centralised retail enterprises the decision rights of the branches are concentrated in a single authority. It is difficult for retail enterprises to ascertain customer preferences by merely observing transactions. This has led to quantifiable losses. Although some enterprises implemented classical business models to address these challenging issues, they still lacked analytics-based marketing programs to gain competitive advantage. This research study develops an intelligent analytics-based (ARANN) model for both distributed and centralised retail enterprises in the cross-demographics of a developing country. The ARANN model is built on association rules (AR), complemented by artificial neural networks (ANN) to strengthen the results of these two individual models. The ARANN model was tested using real-life and publicly available transactional datasets for the generation of product arrangement sets. In centralised retail enterprises, the data from different branches was integrated and pre-processed to remove data impurities. The cleaned data was then fed into the ARANN model. On the other hand, in distributed retail enterprises data was collected branch per branch and cleaned. The cleaned data was fed into the ARANN model. According to experimental analytics, the ARANN model can generate improved product arrangement sets, thereby improving the confidence of retail enterprise decision-makers in competitive environments. It was also observed that the ARANN model performed faster in distributed than in centralised retail enterprises. This research is beneficial for sustainable businesses and consideration of the results is therefore recommended to retail enterprises.ComputingM Sc. (Computing