This research studies a case where there are two manufacturers producing competing products and selling them through a common retailer. The consumer demand depends on two factors: (1) retail price, and (2) service level provided by the manufacturer. Game-theoretic framework is applied to obtained the equilibrium solutions for every entities. This article studies and compares results from three possible supply chain scenarios, (1) Manufacturer Stackelberg, (2) Retailer Stackelberg, and (3) Vertical Nash. Our research concludes that consumers receive more service when every channel members possess equal bargaining power (e.g., Vertical Nash). An interesting but less intuitive result shows that as market base of one product increases, the competitor also benefits but at a less amount than the manufacturer of the first product. Furthermore, when one manufacturer has some economic advantage in providing service, the retailer will act to separate market segment by selling the product with low service at a low price and selling the product with high service at a high price.

A customer value-oriented approach is applied to analyze a case study of an ongoing project in rural Thailand to trace quality produce supplied to upmarket retail in the same country. Traceability, an organizational competence, is seldom in business practice as well as in the literature associated with value. It has been stressed through this study that traceability systems involve more than technical and cost-related challenges. Aspects of traceability as a value-related knowledge resource are evoked through viewing traceability as embedded in a 'value network' construct. This view is applied to a food network in a developing economy. In addition, the case study reveals the impact of new technology, how traceability is organized and costs of this organization in a value network. Food product traceability is described as an organized supply chain resource, not limited to IT-related costs driven by needs to succumb to government requirements, which is also applicable in developing economies due to market development and lower IT costs. This customer value-based understanding is of importance when considering investing in traceability and in the design of food product traceability systems, as well as lowering hindrances associated with developing electronic food product traceability using new information technology.

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The applications of Big Data analytics and Artificial Intelligence (AI) have gained a widespread attention in the construction industry in recent years following the promulgation of Industry 4.0. In the realm of construction research, AI has been utilised widely in areas such as structural design optimization, resource and equipment planning, and project scheduling. The research presented in this paper is aimed to utilise AI to assist with the automatic classification of the large volume of construction material orders created by users through an online marketplace website. Such big data of material orders contained numerous errors (e.g. typographical errors and incorrect units) that were extremely time consuming to correct before the datasets can be used to for further business intelligence analysis. In this research, the dataset was obtained from a business-to-business e-commerce company in Thailand, namely BUILK. The data from BUILK was the construction materials purchase orders created by BUILK's customers through its website, which contained hundreds of thousand unorganized records. In this study, Artificial Neural Networks (ANNs) was applied to automate the categorization of approximately 220,000 records of reinforcement steels orders. The ANNs model was developed and trained using over 32,000 records, with approximately 92 percent of prediction accuracy. The model automatically categorized the steel reinforcement data into 11 groups; Deformed Bars, Round Bars, Wire mesh (Deformed Bars), Wire mesh (Round Bars), Stirrup, Anchor, Material and Others. The outcome of this research helped the company to easily analyze the data to generate insights for its business management and development.

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