Heritage buildings (HBs) have been identified as iconic buildings vital to sustainable development. Unlike modern buildings that can be maintained without conserving cultural significance, HBs are typically symbols of cultural identity that necessitate specific maintenance management. While effective HB maintenance is critical, research on the influencing factors (IFs) of HB maintenance management (HBMM) is limited. This study investigated IFs in developed and developing regions, namely Hong Kong (HK) and Nigeria, to fill this research gap. First, a systematic literature review was conducted, which resulted in the identification of 17 IFs. Then, a questionnaire survey was conducted to solicit maintenance practitioners’ opinions on the effects of the IFs on HBMM. The Mann–Whitney U test was used to identify commonalities and disparities among 154 valid survey responses. The findings reveal that while the respondents agreed on some IFs’ importance, including international statutory protection guiding HB use, they held divergent opinions about other IFs, which include cultural/religious attachment to HBs. This study revealed the distinctiveness between HK and Nigeria regarding the factors influencing HBMM and provided insights for future researchers to further explore the understudied areas of HBMM. The study’s recommended measures can also help to improve and inform HBMM policy-making.

University towns face many challenges in the 21st century due to urbanization, increased student population, and higher educational institutions’ inability to house all their students on-campus. For university towns to be resilient and sustainable, the challenges facing them must be assessed and addressed. To carry out community resilience assessments, this study adopted a novel methodological framework to harness the power of artificial intelligence and social media big data (user-generated content on Twitter) to carry out remote studies in six university towns on six continents using Text Mining, Machine Learning, and Natural Language Processing. Cultural, social, physical, economic, and institutional and governance community challenges were identified and analyzed from the historical big data and validated using an online expert survey. This study gives a global overview of the challenges university towns experience due to studentification and shows that artificial intelligence can provide an easy, cheap, and more accurate way of conducting community resilience assessments in urban communities. The study also contributes to knowledge of research in the new normal by proving that longitudinal studies can be completed remotely.

Purpose: The paper aims to identify the critical constraints that impede heritage building (HB) facility managers from discharging their duties effectively and develop an index model to guide HB maintenance management (HBMM) practitioners to the critical constraints.Design/methodology/approach: A literature review was conducted to identify HBMM constraints. Facilty management practitioners assessed the constraints' significance through an online survey. The factor analysis was used to shortlist and group the constraints, and the constraint clusters were analyzed by the fuzzy synthetic evaluation technique. A significant index cluster to determine HBMM constraints criticality was generated using the linear additive model.Findings: Embracing a total of 16 HBMM constraints, the three clusters identified are: (1) managerial and inadequacy constraints, (2) pressure and bureaucracy constraints and (3) HB peculiarities constraints. Based on the generated significant index, the HB peculiarities cluster was identified as the most significant.Research limitations/implications: The study was conducted in a particular jurisdiction, limiting the generalizability of the result. Future research should address this limitation by covering more jurisdictions.Practical implications: The significant index model (SIM) developed enables HBMM practitioners to objectively assess the criticality of HB constraints and facilitates them to effectively strategize and allocate resources for HBMM.Originality/value: The SIM, which transforms subjective judgment into the objective assessment of the HBMM constraints' criticality, can assist practitioners, policymakers and other HBMM stakeholders in implementing strategies for the sustainability of HBs.

Purpose: With the increased demand for the application of technology in property activities, there is a growing need for property professionals adept in using digital technology. Hence, it is important to assess the competence of academia in equipping property professionals with digital technology skills. This study, therefore, assesses property academics in Australian universities to identify their level of knowledge and use of digital technology applicable to the property industry.Design/methodology/approach: Online questionnaire surveys were administered to 22 out of 110 property academics contacted through the Australia Property Institute (API) database to achieve this aim. The collected data were analysed using mean score ranking and ANOVA.Findings: The study found that apart from databases and analytics platforms such as Corelogic RP data, price finder and industry-based software such as the Microsoft Office suite and ARGUS software, the academics were not knowledgeable in most identified and sampled proptech tools. Similarly, most proptech tools were not used or taught to the students. It was also found that early career academics (below five years in academia) were the most knowledgeable group about the proptech tools.Research limitations/implications: Relying on the API database to contact property academics potentially excludes the position of property academics who may not be affiliated or have contacts with API, hence, the findings of this study should be generalised with caution.Practical implications: The study bears huge implications for the property education sector and industry in Australia; a low knowledge and use of nascent tools such as artificial intelligence, machine learning, blockchain, drones, fintech, which have received intense interest, reveals some level of skill gap of students who pass through that system and may need to be upskilled by employers to meet the current day demand.Originality/value: In response to the clamour for technology-inclined property professionals, this paper presents itself as the first to assess the knowledge levels and application of digital technology by property academics.