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Purpose This paper aims to forecast inbound and outbound container throughput for Bangkok Port to 2041 and uses the results to inform the future planning and management of the port’s container terminal. Design/methodology/approach The data used cover a period of 16 years (192 months of observations). Data sources include the Bank of Thailand and the Energy Policy and Planning Office. Cause-and-effect forecasting is adopted for predicting future container throughput by using a vector error correction model (VECM). Findings Forecasting future container throughput in Bangkok Port will benefit port planning. Various economic factors affect the volume of both inbound and outbound containers through the port. Three cases (scenarios) of container terminal expansion are analyzed and assessed, on the basis of which an optimal scenario is identified. Research limitations/implications The economic characteristics of Thailand differ from those of other countries/jurisdictions, such as the USA, the EU, Japan, China, Malaysia and Indonesia, and optimal terminal expansion scenarios may therefore differ from that identified in this study. In addition, six particular countries/jurisdictions are the dominant trading partners of Thailand, but these main trading partners may change in the future. Originality/value There are only two major projects that have forecast container throughput volumes for Bangkok Port. The first project, by the Japan International Cooperation Agency, applied both the trend of cargo volumes and the relationship of volumes with economic indices such as population and gross domestic product. The second project, by the Port Authority of Thailand, applied a moving average method to forecast the number of containers. Other authors have used time-series forecasting. Here, the authors apply a VECM to forecast the future container throughput of Bangkok Port.

This paper aims to present the logistics collaboration management model and performance improvement of orchid flower firms in logistics activities for growers and exporters. The collaboration results improving cost, time and reliability to all parties in the chain. The collaboration management model becomes firms' management tools for competitive advantage among rivals in the industry. The logistics performance indicator model uses to measure the activities between pre and post collaboration. The research contributes the uniqueness logistics collaborative management model which value to orchid industry in Thailand. The orchid flower grower and exporter may use this model as their management tool which aims in competitive advantage.

The competitive landscape in which businesses operate is changing rapidly [1]. With globalization, companies can reach out to almost anywhere in the world to locate their manufacturing activities [2]. This provides both opportunities as well as threats. Whether a company is located at home or abroad, competitors will still be present, offering cheaper alternatives or more sophisticated products [3]. In recent years, the manufacturing sector has been increasingly exposed to the challenges of global competition. As a result, a key challenge for a manufacturing company is to reliably position itself in the global supply chain in order to create the best possible competitive advantage. This challenge includes deciding which activities they should focus on and carry out themselves, along with those activities that should be external. Also, where are the most appropriate locations for those internal and external activities within the global supply chain network. Currently, these decisions are often made in an unstructured way and without much appreciation for the overall impact on a company's overall performance [4]. There is therefore an urgent need for research to adopt a holistic approach to define their competitive position in global supply chains. This is referred to as strategic positioning within global supply chains.The research programme began by exploring the strategic positioning decision formation in real practice. The results from the exploratory case studies and existing contribution from literature are then synthesized to form a pilot methodology. This is captured in the form of a paper-based workbook. Subsequently, this methodology has been evaluated and refined through a primary application in two case studies with the researcher taking a role as a participant. Finally, wider applicability of the methodology has been assessed through four more case studies covering different types of manufacturing with the researcher not intervening but instead observing. The final methodology referred to in this paper as the 'SPGC methodology' (SPGC -strategic positioning within global supply chains) has demonstrated that it provides practical support to industrial decision making. This paper is structured to first provide a background to this topic, along with the concept of strategic positioning and an overview of previous research. The research aim and programme are then described, and the final SPGC methodology is presented. Lastly the application of the methodology is discussed. BACKGROUND OF THE RESEARCHThis section describes the background of the research starting with the industrial problem. The concept of strategic positioning is then described and finally followed by a review of previous research work on the strategic positioning decision making process. Industrial problemThe UK is the sixth largest manufacturing country in the world [5]. The manufacturing industry plays a vital role in the UK economy. It generates one-sixth of the UK overall wealth and it is the UK's most innovative sector, representing thr...

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