*3.2. Data Collection and Analysis*

The 42-sector IOT of Fujian Province in 2012 and 2017 were extracted from Fujian Statistics Bureau. The 42 sectors were merged into nine sectors based on the Industrial Classification for Nation Economic Activities (GB/T 4754-2017), as described in Table 1. Table 2 lists the merged economic input-output tables in 2012 and 2017. The data of urban solid waste was obtained from Fujian Statistical Yearbook, related official website and literature [38,39]. A two-level fractional factorial analysis was adopted for designing a set of scenarios. Five sectoral solid waste production (*e<sup>i</sup>* ) and five sectoral direct consumption coefficients (*aij*) were selected as deigned factors, with each divided into low (L) and high (H) levels. According to the number of factors, a 2 (10−5) orthogonal array was chosen to present the experimental scenarios. Thirty-two SPI values were obtained through repeatedly running the model. The square sum of individual factor and factor combinations was calculated.


**Table 1.** Abbreviations of 9 sectors.

**Figure 1.** The formulation and application of the FE-PIOM model.

Figure 1 summarizes the formulation and application of the FE-PIOM model. The first step is to merge a large number of sectors into a small number of sectors in input-output table and transform the monetary input-output model into physical input-output model to describe sectoral linkages; calculate the driving force weight and pulling force weight to detect ecological hierarchy structure and then figure out the exploitation, competition, and mutualism to calculate ecological pairwise relationships. The second step is to select a set of proper factors, choose fractional experimental matrix, repeat the first step according to the matrix, recognize main factors and their interactions and identify a sound strategy.


#### *Sustainability* **2021**, *13*, 8341
