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This study underscores the critical importance of well-functioning sewer systems in achieving smart and sustainable urban drainage within cities. It specifically targets the pressing issue of sewer overflows (SO), widely recognized for their detrimental impact on the environment and public health. The primary purpose of this research is to bridge significant research gaps by investigating the root causes of SO incidents and comprehending their broader ecological consequences.

To fill research gaps, the study introduces the Multi-Phase Causal Inference Fuzzy-Based Framework (MCIF). MCIF integrates the fuzzy Delphi technique, fuzzy DEMATEL method, fuzzy TOPSIS technique and expert interviews. Drawing on expertise from developed countries, MCIF systematically identifies and prioritizes SO causes, explores causal interrelationships, prioritizes environmental impacts and compiles mitigation strategies.

The study's findings are multifaceted and substantially contribute to addressing SO challenges. Utilizing the MCIF, the research effectively identifies and prioritizes causal factors behind SO incidents, highlighting their relative significance. Additionally, it unravels intricate causal relationships among key factors such as blockages, flow velocity, infiltration and inflow, under-designed pipe diameter and pipe deformation, holes or collapse, providing a profound insight into the intricate web of influences leading to SO.

This study introduces originality by presenting the innovative MCIF tailored for SO mitigation. The combination of fuzzy techniques, expert input and holistic analysis enriches the existing knowledge. These findings pave the way for informed decision-making and proactive measures to achieve sustainable urban drainage systems.

This study investigates the variables that impact initial public offerings (IPO) initial returns witnessed in Pakistan from 1996 to 2019 using pre-listing information variables, namely country-level institutional quality, sponsor ownership and pricing mechanism. IPO oversubscription is included as a moderating variable.

This research is motivated by the premise that the Pakistani IPO market is characterised by a broad range of institutional and regulatory frameworks. Multiple regression studies, i.e. ordinary least square (OLS) and quantile least square (QLS), were performed on 102 IPOs issued on the Pakistan stock market.

The present study findings suggest that the quality of public service, the independence of civil service from political influences and the legitimacy of government increase investors’ confidence in the prospects of companies, hence increasing the demand for IPO and initial returns. In addition, good regulatory quality enhances market transparency and lowers uncertainty, hence signalling high-quality IPOs and leading in substantial initial returns. The negative effect of the lock-up ratio on the initial return of an IPO is consistent with the risk-return trade-off theory, which asserts that the lock-up ratio indicates the quality of the IPO.

The results provide market regulators, policymakers, investors and underwriters with useful data for assuring proper subscriptions of issued shares, as these variables are crucial for company transparency and market efficiency. The findings will also help investors make better IPO subscription decisions.

The present study explains the important influencing factors of IPO initial return in the Pakistani market.

The study evaluates whether an application of Ind-AS that converged with IFRS in India has enhanced financial reporting quality (FRQ) and how that is reflected in financial performance (FP).

Design/methodology/approach: The study uses discretionary accruals (DACC) to measure FRQ. In addition, it uses ordinary least square (OLS) regression to examine the association between Corporate Governance attributes, FRQ, and financial performance for a sample of 24 textile companies from 2010 to 2021.

The results indicate that adopting IFRS has a role in monitoring CG attributes to enhance FRQ; this means the financial reporting qualit improves somewhat with some CG attributes under Ind-AS. In addition, the results demonstrate that financial reporting quality positively influences FP.

There are significant effects on authorities and decision-makers. The findings from this research can benefit lawmakers by providing Ind-AS policy enforcement with more consideration. The results are also helpful for policymakers who want to improve CG and need proof of the significance of high FRQ in this respect.

Given the dearth of research on FRQ in India, the study extends prior literature on FRQ by examining the quality of financial reporting according to the transformation to IFRS in Indian textile firms. The theoretical contribution of the current study is the testing of agency theory towards practices of corporate governance mechanisms on FRQ and FP in the context of the textile sector.

This study aims to assess the factors influencing the effective implementation of extended producer responsibility (EPR) practices within the context of sustainable accounting goals and circular economy principles. It seeks to provide insights into the significance of EPR policies for manufacturing industries striving to enhance their environmental, social and governance performance while ensuring sustainable accounting of their business operations.

The methodology proposed in this article is based on the decision-making trial and evaluation laboratory (DEMATEL) technique. This approach formulates a structural framework for evaluating influential elements among critical recognized factors. By using DEMATEL, the study examines the interconnectedness between assessed factors through a cause-and-effect diagram, facilitating the integration of EPR into sustainable accounting practices.

The research findings reveal that the most impactful contributors to sustainable accounting practices of EPR within the framework of sustainable development goals and circular economy are producers, consumers, eco-design, public awareness and the support of local authorities. These findings underscore the importance of considering these factors in implementing EPR and advancing sustainable accounting practices.

This paper contributes to the literature by proposing a DEMATEL-based model for evaluating the factors affecting the implementation of EPR within the context of sustainable accounting goals and circular economy principles.

This study aims to comprehensively examine the relationship between initial public offering (IPO) activities and macroeconomic factors in Sri Lanka.

This study uses principal component analysis (PCA) and autoregressive distributed lag (ARDL) techniques to examine the relationship between IPO activities and macroeconomic factors. Ten macroeconomic variables are transformed into principal components (factors) using PCA. Then, ARDL is applied to investigate the long- and short-term relationships between IPO activities and the transformed macroeconomic factors.

The empirical investigation identifies three principal factors from the ten macroeconomic variables, of which two factors have a significant long-run association with IPO activities: “return on investment (RTOI)” and “economic and market development (ECMD).” In the short run, “trade openness and banking sector development (TOBD)” and RTOI are significantly associated with IPO activities.

The study was based on 30 years of observations, which passed all diagnostic tests but may be insufficient for generalizing the findings. Future studies could use high-frequency data (monthly or quarterly) to increase the number of observations and repeat the method and analysis. Also, while the symmetrical ARDL method was used in this study, an asymmetrical ARDL method may provide more insightful results and interpretations.

The study highlights the importance of considering both long- and short-term associations when analyzing the impact of macroeconomic variables on IPO activities.

This study is the first to comprehensively examine the relationship between IPO activities and macroeconomic variables using PCA and the ARDL technique. The study provides insight into the macroeconomic factors that influence IPO activities in Sri Lanka and highlights the importance of considering long- and short-term associations.

This study aims to determine the export price pass-through elasticity, specifically for Indian exports. It employs static and dynamic panel data techniques to estimate these elasticities. Notably, the pass-through effect is more significant in the long term compared to the short term. The dynamic panel analysis, considering broader economic factors, identifies trade openness and global demand as statistically significant in explaining export price variations. Additionally, the study reveals that the response of export prices to exchange rate changes depends on the nature of those changes, with depreciation having a lesser impact than appreciation. Furthermore, this chapter emphasizes the importance of analyzing these effects at the product level for a comprehensive understanding of the underlying mechanisms. The implications of these findings underscore the crucial role of exchange rates as a policy tool for promoting exports and economic growth, as well as their potential in reducing current account deficits.

The emergence of Construction 4.0 technologies provides an impetus for radical change and rejuvenates the interest of stakeholders in addressing long-standing performance issues in the construction sector. However, construction firms struggle to implement Construction 4.0 technologies for performance measurement and improvement. Therefore, the purpose of this research is to develop a conceptual model of innovation management for implementing Construction 4.0 that guides and facilitates the strategic transformation of construction firms.

A conceptual model of innovation management is presented, and the findings are synthesised based on a literature review, 20 semi-structured interviews, two focus group discussions, three workshops, expert consultation and observations on three digitally-enabled projects. Data were inductively analysed using thematic analysis.

The analysis of empirical data revealed: (i) Four scenarios that could lead the industry to different futures, based on the extent of research and development, and the extent of integration/collaboration; (ii) Construction 4.0 capability stages for a sustained implementation route; (iii) Possible business model configurations derived from servitisation strategies; and (iv) Skills management challenges for organisations.

First, the empirical data was only collected in the UK with its unique industry context, which may limit the applicability of the results. Second, most of the research data comes from the private sector, without the views of public sector organisations. Third, the model needs to be further validated with specific data-driven use cases to address productivity and sustainability issues.

Successful Construction 4.0 transformation requires a concerted effort of stakeholders, including those in the supply chain, technology companies, innovation networks and government. Although a stakeholder’s action would depend on others’ actions, each stakeholder should undertake action that can influence the factors within their control (such as the extent of collaboration and investment) and the outcomes.

The conceptual model brings together and establishes the relationships between the scenarios, Construction 4.0 capability stages, business models and skills management. It provides the first step that guides the fuzzy front-end of Construction 4.0 implementation, underpins the transformation to the desired future and builds long-term innovation capabilities.

The purpose of this study is to examine the influence of an online course on gender equality in tourism on the knowledge, attitudes and practices (KAP) of students concerning sustainable development goals (SDGs) at two universities in Spain and Mexico.

The study uses 38 online qualitative surveys administered to participants both before and after the university online course. The methodology incorporates the three variables of the KAP model: knowledge, attitudes and practice.

Following the online course, disparities in knowledge levels were observed, accompanied by positive shifts in attitudes and practices toward SDG 5 among university students from Mexico and Spain. The results suggest that a positive initial attitude markedly enriches the learning experience, even without extensive preexisting knowledge and notably increases the likelihood of participants engaging in practical actions postcourse completion.

The study proposes an innovative framework for designing SDGs-oriented training courses within university settings. Additionally, it outlines a pathway by which enhancements in knowledge, attitudes and practices related to SDGs, with a focus on SDG 5, empower students to act as catalysts for societal change.

This study presents a novel application of the KAP model’s variables in analyzing the results of a university course within the tourism sector. It underscores the essential role of expert-led instruction using real-life case studies for SDG education, providing fresh perspectives on augmenting the contribution of higher education to sustainable development.

Facilities management (FM), which is crucial for the operation and sustainability of buildings and infrastructure across the world, covers a wide range of competencies that may vary across regions. Focusing on Sri Lanka and Hong Kong, this study aims to reveal and compare the importance and current competency levels of FM competencies in these regions, based on which appropriate education and training can be formulated to enhance the growth of their FM sectors.

After an extensive literature review, 12 FM competency attributes (CAs) were identified. A questionnaire survey in Sri Lanka and Hong Kong solicited the industry practitioners’ perceived importance and current levels of the CAs. The survey responses, 126 from Sri Lanka and 148 from Hong Kong, were analysed by a modified Importance-Competency Analysis matrix, followed using the Mann−Whitney U test to identify any differences in the responses between the two regions.

Between Sri Lanka and Hong Kong, significant differences were found to exist in the importance and current competency levels of over half of the CAs. Among the CAs requiring priority attention, “operation and maintenance” and “leadership” are the top two in Sri Lanka while the top two in Hong Kong are “technology” and “leadership”.

This study yielded insightful results on the importance of FM competencies and the current competency levels in a developing region and a developed region, which are useful for the development of FM education and research.

This study aims to enhance productivity monitoring and control in the construction industry by integrating data-driven analytics with expert insights.

A novel framework combines expert knowledge and data analysis to identify productivity trends and devise improvement strategies. A machine learning model predicts productivity ranges using historical data and project-specific factors’ evaluated by surveys, supported by a warning dashboard for proactive decision-making.

The findings reveal that integrating expert insights with data analytics significantly enhances the ability to monitor and control productivity, leading to proactive strategies for construction stakeholders. The machine learning model demonstrates robust accuracy in forecasting productivity ranges, allowing for early identification of potential issues. The dashboard system proves invaluable, offering semi-real-time alerts and facilitating swift action to prevent productivity lapses. These results highlight the effectiveness of the proposed approach in detecting trends, predicting outcomes and enabling timely interventions, thereby contributing to the overall productivity improvement of construction projects.

There are also limitations to consider, including potential data availability, constraints in the expert pool, implementation challenges and the need for long-term evaluation; these factors should be considered when interpreting the study’s findings and applying the proposed framework to construction projects. Future research can focus on expanding the application of this framework to different types of construction projects and evaluating its scalability.

This study introduces a framework with a warning dashboard for early detection of issues, combining expert insights and data analysis for improved project outcomes. This research suggests a shift toward more expert, data-driven, insightful decision-making in construction, aiming for enhanced performance and reduced disruptions. An important implication of this research is the need to balance digital tools and expert judgment. Project managers are advised to use a holistic strategy that ensures informed and comprehensive decision-making.

This research introduces a unique methodology that blends traditional expertise with modern analytics to address construction productivity challenges. It offers a practical solution for stakeholders to enhance decision-making, resource allocation and project planning, marking a significant contribution to construction management literature.