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This study aims to introduce and evaluate the COPULA framework, a construction project monitoring solution based on blockchain designed to address the inherent challenges of construction project monitoring and management. This research aims to enhance efficiency, transparency and trust within the dynamic and collaborative environment of the construction industry by leveraging the decentralized, secure and immutable nature of blockchain technology.

This paper employs a comprehensive approach encompassing the formulation of the COPULA model, the development of a digital solution using the ethereum blockchain and extensive testing to assess performance in terms of execution cost, time, integrity, immutability and security. A case analysis is conducted to demonstrate the practical application and benefits of blockchain technology in real-world construction project monitoring scenarios.

The findings reveal that the COPULA framework effectively addresses critical issues such as centralization, privacy and security vulnerabilities in construction project management. It facilitates seamless data exchange among stakeholders, ensuring real-time transparency and the creation of a tamper-proof communication channel. The framework demonstrates the potential to significantly enhance project efficiency and foster trust among all parties involved.

While the study provides promising insights into the application of blockchain technology in construction project monitoring, future research could explore the integration of COPULA with existing project management methodologies to broaden its applicability and impact. Further investigations into the solution’s scalability and adaptation to various construction project types and sizes are also suggested.

This research offers a comprehensive blockchain solution specifically tailored for the construction industry. Unlike prior studies focusing on theoretical aspects, this paper presents a practical, end-to-end solution encompassing model formulation, digital implementation, proof-of-concept testing and validation analysis. The COPULA framework marks a significant advancement in the digital transformation of construction project monitoring, providing a novel approach to overcoming longstanding industry challenges.

This study aims to predict customer churn in resort hotels by calculating the churn probability of repeat customers for future stays in the same hotel brand.

Based on the recency, frequency, monetary (RFM) paradigm, random forest and logistic regression supervised machine learning algorithms were used to predict churn behavior. The model with superior performance was used to detect potential churners and generate a priority matrix.

The random forest algorithm showed a higher prediction performance with an 80% accuracy rate. The most important variables were RFM-based, followed by hotel sector-specific variables such as market, season, accompaniers and booker. Some managerial strategies were proposed to retain future churners, clustered as “hesitant,” “economy,” “alternative seeker,” and “opportunity chaser” customer groups.

This study contributes to the theoretical understanding of customer behavior in the hospitality industry and provides valuable insight for hotel practitioners by demonstrating the methods that facilitate the identification of potential churners and their characteristics.

Most customer retention studies in hospitality either concentrate on the antecedents of retention or customers’ revisit intentions using traditional methods. Taking a unique place within the literature, this study conducts churn prediction analysis for repeat hotel customers by opening a new area for inquiry in hospitality studies.

Reducing the number of generated mutants by clustering redundant mutants, reducing the execution time by decreasing the number of generated mutants and reducing the cost of mutation testing are the main goals of this study.

In this study, a method is suggested to identify and prone the redundant mutants. In the method, first, the program source code is analyzed by the developed parser to filter out the effectless instructions; then the remaining instructions are mutated by the standard mutation operators. The single-line mutants are partially executed by the developed instruction evaluator. Next, a clustering method is used to group the single-line mutants with the same results. There is only one complete run per cluster.

The results of experiments on the Java benchmarks indicate that the proposed method causes a 53.51 per cent reduction in the number of mutants and a 57.64 per cent time reduction compared to similar experiments in the MuJava and MuClipse tools.

Developing a classifier that takes the source code of the program and classifies the programs' instructions into effective and effectless classes using a dependency graph; filtering out the effectless instructions reduces the total number of mutants generated; Developing and implementing an instruction parser and instruction-level mutant generator for Java programs; the mutant generator takes instruction in the original program as a string and generates its single-line mutants based on the standard mutation operators in MuJava; Developing a stack-based evaluator that takes an instruction (original or mutant) and the test data and evaluates its result without executing the whole program.

Senior Indigenous leadership positions across the Australian higher education sector has increased over the past decade. Despite this advancement, there is limited understanding in terms of how to best integrate Indigenous leadership into existing governance structures of Australian universities. In 2018 the Walan Mayiny: Indigenous Leadership in Higher Education project commenced, aimed at establishing a model of best practice for the inclusivity of Indigenous leadership in higher education governance structures. This article presents key findings from the project, namely, a model of senior Indigenous leadership within the Australian universities based on the perceptions of a group of Indigenous academics.

Through qualitative semi-structured interviews with Indigenous academic staff, the perceived value, characteristics and challenges of senior Indigenous leadership were examined. The varying opinions held by Indigenous academics in relation to the qualifications and experience required to fulfil a senior Indigenous leadership position were also highlighted. In doing so, a model of senior Indigenous leadership within the Australian higher education system is presented. The model of best practice presented in this article is underpinned by Indigenous Institutional Theory (Coates et al., 2022), a theoretical framework developed from the Walan Mayiny study.

The research findings highlight the diverse opinions of Indigenous academics in relation to the qualifications and experience required to fulfil a senior Indigenous leadership position. The six essential components are built upon the core characteristics, values and behaviours that senior Indigenous leaders need to have according to Indigenous academics, in order to advance Indigenous success within the academy.

Given Australian universities are being called upon to ensure that senior Indigenous leaders are in the best position possible to forge institutional change, senior Indigenous leaders within the academy may find the contextual Indigenous leadership model beneficial. The model allows one to uphold cultural integrity and fulfil the responsibilities and obligations of their higher education institution, while being able to serve their Indigenous colleagues and communities, leading to the advancement of Indigenous higher education outcomes. Importantly, the model can be adapted to suit all First Nations Peoples globally, who also find themselves working within the shackles of Western institutions.

The purpose of this article is to challenge the balanced budget practices of U.S. state governments and offer alternatives that may lead to better fiscal, economic and policy outcomes. We contend that the norm of balance may be leading U.S. states to make fiscal decisions that result in less-than-ideal outcomes, especially during economic downturns.

This is a normative article. We examine the scholarly evidence regarding balanced budget practices to assess the appropriateness of balanced budget norms. We also examine the fiscal rules followed by Eurozone countries to draw potential lessons for U.S. states.

We conclude that state governments should move away from strict norms of budget balance and seek more flexible approaches. We suggest that instead of following strict rules and norms of balance, U.S. states should consider implementing escape clauses, debt and deficit ceilings, and fiscal councils. We also suggest that the Federal Reserve be open to lending directly to states during fiscal crises to ensure that states have access to affordable credit.

The balanced budget norm has become ingrained in U.S. state budgeting practices, so much so that public officials and scholars alike rarely question it. The novel contribution of our article is to question this practice in a systematic way and propose alternative approaches.