A forecasting model of packaging costs : case plain packaging

Abstract

Businesses need to secure the continuity of their operations also in unforeseen events, where severe market disturbances are present. Risk assessments, including cost forecasting analyses, are needed to identify different types of risks in order to mitigate them. Furthermore, the carbon footprint of raw materials, production processes and products should be minimized, driven by the tightening legislation aiming to minimize climate change. The efforts needed can sometimes be costly e.g. regarding the modernization of existing production technology. However, these kinds of investments can be justified in enabling the utilization of renewable, recyclable materials and the minimization of waste streams.

The objective of this doctoral dissertation is to describe how the calculation model being created by the author (A forecasting model of packaging cost, or FMPC) is suited for forecasting packaging costs within value chains in such above-mentioned situations. The cigarette packaging value chain has been selected for the case study; the functionality of the model has been demonstrated with certain scenarios focusing on the influences of the plain packaging legislation, which was first taken into use in Australia in 2012.

The Design Science Research (DSR) methodology has been followed when designing, developing, and evaluating the FMPC. Even though the case study focuses on cigarette packaging, the FMPC has been created in a way that it can also be utilized for evaluating other types of packaging production processes and value chains, increasing its theoretical value. The empirical results illustrated in the scenarios are descriptive in nature as a reallife production test arrangement-based evaluation is also needed. The design principles of the extended FMPC follow the same guidelines used in the earlier version of the model as its evaluation has been validated in the industry. The results of the research illustrate the advantages of the FMPC in increasing knowledge regarding the cost structures of the packaging value chains and in making the required risk assessments to support business decisions. Furthermore, by utilizing the output data, it becomes possible to forecast the carbon footprint of the selected production processes and raw materials enabling possibilities for minimizing their environmental load and related costs.