Figure 3
The diagram is enclosed in a large horizontal rectangle. Inside the rectangle, at the center, there is a three-dimensional block with three visible faces in different colors. A small point labeled “A” appears on the upper right edge of the block. Three axes extend from the block: one upward labeled “Value”, one leftward labeled “Methodology”, and one rightward labeled “Concept”. Surrounding the block is a dashed circular arrow path with several short arrows indicating rotation. To the right of the three-dimensional block is a horizontal dashed rectangle with a small dashed text box inside labeled “Output”, with an icon of a magnifying glass with the letter W. An upward arrow extends from this rectangle and points leftward to another dashed rectangle positioned on the left of the three-dimensional block. This rectangle comprises two small dashed text boxes inside. The upper text box reads “Optimization algorithms or M L models” along with an icon of a magnifying glass. The bottom text box is labeled “Tools or Software” along with an icon of tools on a desktop screen. A downward arrow from this dashed rectangle points to a large dashed horizontal rectangle at the bottom comprising six text boxes arranged in two rows of three. In the top row, the first text box is labeled “Theoretical-construct label” along with an icon of a connected-node graphic. The second text box is labeled “Objective function or Fitness function” along with an icon of a gear. The third text box is labeled “Context of research” along with an icon of a document. In the bottom row, the first text box is labeled “Standards” along with an icon of a checklist. The second text box is labeled “Building’s function” along with an icon of a building. The third text box is labeled “Design variables” along with an icon of a control panel. A horizontal arrow extends from the left side of this rectangle toward the right side, and moving upward pointing to “Output”.The three-dimensional dialectical system thinking-based variables for analysing application of optimisation algorithms and ML in life cycle performance optimisation. Source: The authors, adapted from Pan et al. (2018)