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The aim of this study is to develop a new multidimensional index to measure export potential of textile firms by using firm-level data.

After a conceptual model, a structural equation model is developed with five dimensions and 27 observed variables based on resource-based view theory. The measurement model is solved by Linear Structural Relations (LISREL) with maximum likelihood algorithm by using data collected from 454 textile firms in Türkiye.

In this study, a new multidimensional index that measures export potential of textile firms is developed. With the proposed model, the export potential of textile firms can be calculated numerically with the five dimensions: Resources, Dynamism, Knowledge, Innovation and Sustainability. The comparison of the output of the proposed model with the control variable, firm’s actual export values, shows a significantly high success ratio of 90.76%.

The model is applicable for textile firms at different export levels, regions and sub-sectors. The Export Potential Index for Textile Industry model is verified by using Turkish textile industry data. The robustness of the model may be increased by verifying the model by using some other countries data. This model can be implemented to other industrial sectors with some modification of the dimensions and variables.

The proposed model will contribute to the firms by calculating their export potential in five dimensions with their own variables numerically. The model will help firms to develop strategies to increase their export potential and to the governmental and industrial organizations to develop incentives policies.

This paper fills the gap in the literature by proposing a multidimensional index that determines a firm’s export potential numerically by using firm-level data.

The purpose of this paper is to develop a novel tool to support decision making for enhanced demolition process efficiency and material waste sortability through computerised 4D motion workflow simulation.

A time-lapse evaluation model was developed to classify and estimate the impact of building demolition processes and material waste recovery. The dynamic assessment of demolition, collision and mechanical impact was measured through computerised 4D motion game and physics engines. Waste recovery and treatment complemented the simulation algorithm. The simulation of the information workflow was tested through case study using two demolition strategies.

The simulation successfully estimated the efficiency and efficacy of the different demolition strategies. Thus, simulation results can potentially support better decision making related to the definition of demolition strategies associated with recycling and re-use targets.

The simulation was limited to a simple machine-led demolition strategy. Further research is required to understand the impact of complex machine mechanic movements and processes on complex building fabrics.

Modelling and evaluating the demolition process and its impact on material waste recovery with a time dimension is novel. The comparative analysis of quantitative data allows demolition professionals to find optimal and more sustainable demolition solutions and more efficient and safer implementation on site. It also contributes to a better understanding of the relationship between demolition strategy and waste sortability. This research represents a significant advancement in applied computing for building demolition waste recycling and notably, it improves the quality of information available in the definition of building demolition strategies.