Identification of determinants during the registration process of industrial heritage using a regression analysis

Abstract

• Industrial sites are evaluated based on 22 distinct criteria under 6 main topics. • Detailed building characteristics are investigated. • Logistic regression applications are implemented to industrial heritage registration decisions. • Factors affecting registration status of industrial sites are quantified. • Regression analysis is an efficient method to criticize previous registration decisions. Due to technological developments, abandoned and damaged Industrial sites in Europe underwent a rapid transformation after World War II. As a reaction to losing these cultural values, the idea of valuing these industrial sites as the heritage of the Industrial Revolution was introduced in the 1950s. Since then, many studies have been conducted on preserving the industrial heritage. In these theoretical and empirical studies, we observe a lack of objective criteria and systematic methodology for identifying a given industrial site as heritage. There are differences in the perceptions of stakeholders, policymakers, and experts about industrial heritage in different countries. This study aims to identify the effective determinants of the registration decisions of industrial heritage sites in Turkey that were previously evaluated for registration. In this study, Ottoman Royal Factories from the 19th century and some important factories of the Early Turkish Republican Era in the first half of the 20th century are investigated, collecting characteristics of a total of 215 buildings from 12 industrial sites in Istanbul, Kocaeli, and Bursa provinces in Turkey. These industrial sites are evaluated based on 22 socio-cultural, architectural, structural, and industrial criteria. A binary logistic regression modeling approach is implemented to identify influential factors in the registration decisions of industrial heritages. Our regression model results reveal that building-specific factors like view, period, uniqueness, reflections of its period, and economic potential play an important role in registration decisions.