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The construction industry has arrived at a crossroads of rapid technological progress. While it is foreseen that the advent of new construction technologies will disrupt the construction industry’s future, such disruptions often create the ideal environment for innovation. As poor payment practices continue to plague the construction industry, the advent of smart contracts has created an opportunity to rectify the inherent flaws in the mitigation of payment problems in traditional construction contracts. Given the intrinsic resistance of construction firms to such revolutionary changes, this study aims to understand the various factors influencing the adoption of smart contracts in the Singapore construction industry.

A mixed method was adopted involving quantifying respondents’ perceptions of the factors influencing smart contract adoption, and validation from a group of interviewees on the matter. Out of 461 registered quantity surveyor members contacted via the Singapore institute of surveyors and valuers website, 55 respondents took part in the survey. This is followed by semi-structured interviews to validate the survey results.

The findings indicate that construction firms have neither a significant knowledge of nor willingness to adopt smart contracts. A total of 29 institutional factors were also identified that significantly influence the adoption of smart contracts. The quantitative findings were further reinforced by qualitative interviews with five industry experts.

With recognition of and the successful formulation of the significant institutional drivers and barriers, the key findings of this study will be integral in driving the commercial adoption of smart contracts within the construction industry.

Traditional construction materials and methodologies are often perceived to be unproductive, labour-intensive and detrimental to the environment. Mass-engineered timber (MET) is a new structural material that is capable of overcoming numerous issues that otherwise affect the built environment. This study was formulated to assess the current attitude and perception of young Singaporeans towards the concept of Engineered Timber Residential Buildings (ETRBs).

The study employs the mixed-method approach. Questionnaires were used as the primary mode of data gathering. These were disseminated to Singaporeans between the age of 18 and 35 years. A total of 179 valid responses were gathered. Semi-structured interviews were subsequently conducted with six individuals with different demographics in order to gain further insightful opinions and to allow cross validation of responses.

Statistical analysis revealed that 80% of respondents were willing to accept ETRBs, but a lack of awareness and knowledge of MET and the presence of misconceptions, such as an association with deforestation, may present concerns. The study also revealed that individual acceptance of ETRBs is not affected by demographics.

The production of MET involves lower overall carbon emissions than that of conventional materials, and this also allows adoption of the Design for Manufacturing and Assembly (DfMA) concept and offers the benefit of carbon sequestration. Residential buildings are the second most common building type in Singapore; significant benefits can be gained if MET is used as the primary material for residential buildings. In general, young stakeholders in Singapore welcome the concept of ETRBs, despite possessing uncertainties about ETRBs—understandable given that the material lacks a track record of usage. Public authorities are thus advised to explore the feasibility of materialising the concept of ETRBs as an option for public housing.

Infrastructure projects are complex, task-based endeavours; the reliability of project schedules is often low, as delays occur. As a result, the infrastructure sector is constantly searching for innovative practices that might improve project performance. This study aims to pursue one research question: what are the benefits and challenges to last planner system (LPS) implementation in Australia’s infrastructure industry? It addresses this question through an examination of two rail infrastructure projects in Victoria, Australia.

The state of Victoria in Australia provides an excellent context for this study. The study was set in one of the programme alliances which was contracted to carry out five level-crossing removal projects. This study uses a combination of qualitative and quantitative research techniques, including surveys, interviews and site visits. The authors collected 43 valid survey responses. Additionally, 19 participants from the alliance programme’s two projects (Projects A and B) took part in the interviews. Extensive empirical evidence has been triangulated to achieve the research goals.

The findings show through the questionnaire survey that the greatest benefits that digital LPS brings are primarily associated with process improvement and social benefits. The interview results acknowledged that the roll-out of digital LPS had a positive impact on schedules, cost, occupational health and safety (OHS) and quality performance. The research also noted a few challenges in the introduction of digital LPS. Overall, the finding presents strong evidence that the introduction of digital LPS has been a clear success in the case company.

This is the first piece of research to fill this major gap in the LPS literature by exploring the issue of digital LPS adoption in Australia’s infrastructure sector. This study has thus laid the foundation for future work on LPS research in the Australian context. The authors are optimistic that this exploratory work will generate interest across other alliances, and perhaps extend into Australia’s construction sector.

Although previous studies have examined the influence of celebrity involvement in behavioural intentions, the role of celebrity dimensions such as attraction, self-expression and centrality in influencing tourists’ intention in the context of developing countries such as Tanzania remains largely unaddressed. This study, therefore, examined the relationship between celebrity involvement and domestic tourists' intentions to visit tourist attractions, attitude being the mediating variable.

A questionnaire was self-administered on a convenient sample of 279 domestic tourists in the Tanzania’s four largest regions, namely, Dar es Salaam, Mbeya, Arusha and Mwanza. Employing a quantitative research approach, structural equation modelling was performed to test the cause-and-effect relationships between celebrity involvement and tourists’ intentions before testing the mediating role of attitude in such a relationship. Confirmatory factor analysis was also performed to test the measurement models.

Attraction emerged to be the main determinant of the celebrity dimension that significantly influenced domestic tourists’ travel intentions, whereas attitude partially mediates such a relationship. Moreover, Bongo Fleva musicians, particularly Diamond Platnumz, one of the leading celebrities in this genre, were found to influence most of the respondents’ travel intentions – he posted a picture on his Instagram account of him touring the Serengeti National Park.

The study focused on domestic tourists residing in four of the Mainland Tanzania’s largest regions, hence excluding those residing on the islands of Unguja and Pemba. Due to cultural differences, including the islands not only could unleash new perspectives on celebrity involvement dimensions but also could have introduced new determinants of travel intentions.

This study offers guidance to tourism businesses on designing their marketing campaigns that they should harness celebrity’s attractive qualities effectively. The focus should be directed not only towards linking destinations with celebrities but also on stimulating positive perception of those destinations, aligning with the attitudes of their followers.

The study has set out a new perspective for researchers, practitioners and tourism businesses to refine their promotional strategies and for academicians to gain a deeper understanding of visitor behavioural intention dynamics.

This study has proposed and verified that attraction is a dominant determinant compared to self-expression and centrality in explaining tourists’ travel intentions and attitudes, which play a significant role in explaining such a relationship. Although the study employed a modified theory of planned behaviour in a celebrity involvement study, the findings have broadened the understanding and its applicability in the context of a developing country.

This study highlights the influence of non-financial sustainability reporting and firm reputation (FR) on the China Stock Exchange. The study is based on the components of sustainability reporting that influence FR.

A simple ordinary least squares (OLS) regression model is initially run to test the hypotheses. Advanced econometric methods are used to detect the presence of heteroskedasticity. The study utilizes fixed-effect, two-stage least squares (2SLS) and two-step generalized method of moments (GMM) regression models to address endogeneity issues.

Findings suggest that NFSR has a negative influence on FR. Conversely, environmental, social and governance (ESG) sustainability reporting exhibited positive associations with a FR in fixed-effect, 2SLS and GMM results.

This study has limitations, and data collection is restricted to the period from January 2018 to June 2023, limiting the scope of findings due to data constraints. Brand equity measurement is considered only one aspect of a company's activities, and other methods can also be considered for measuring brand equity. Another limitation is a standardized method for measuring NFSR. While this study used the Arianpoor and Salehi (2021) model to measure sustainability reporting in the Chinese market, future research could explore different methods.

The findings of this study have important practical implications for corporate management, highlighting reputation challenges and the strategic importance of sustainability. Managers are encouraged to use NFSR strategically to enhance their reputation and corporate strategy.

The social implications highlight ownership and regulatory structures, promoting enhanced sustainability reporting in China's business culture. This insight informs policymakers, businesses and stakeholders regarding the importance of sustainability reporting, guiding decisions on corporate reputation and sustainability regulations.

The research indicates the importance of context-specific sustainability reporting for enhancing reputation. It provides insights into sustainability's impact on a company's reputation, promoting responsible practices for a sustainable global economy. To the best of the authors' knowledge, this is the first research that utilizes the NFSR frameworks and a sample of firms in China to discuss sustainability reporting with different guidelines.

The purpose of the paper is to investigate the marketing and communication activities carried out by small management consulting firms and how they relate to customers.

After the framing of the literature on the subject, the study is based on the results of a survey carried out through an online questionnaire. The sample under investigation is represented by 914 small consulting firms located in central Italy.

Results show that half of the sample carried out marketing and communication activities, mainly through the website and social media, while others participating in events as speakers at conferences. It also emerges that management consulting firms carry out activities aimed at maintaining relationship with customers even if they do not invest time in market research in order to find potential and new clients.

The study suggests that management consulting firms should adopt a systematic and strategic approach to communication and should develop a complete and integrated digital communication strategy, as well as to rethink the consulting business model.

There are no previous studies that provide insight into the everyday practice of marketing and communication of small management consulting services in today's dynamic and changing economic environment.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

Network embeddedness has been widely considered in enterprise innovation as an effective means of overcoming resource dilemmas. However, while focussing on acquiring external innovation resources, the existing research often ignores the vital role of internal routine updates. Therefore, this study explores the mechanism by which network embeddedness affects innovation performance of enterprises from the perspective of organisational routine updating.

This paper proposes a theoretical model based on social network theory and organisational routines–immune response theory. A total of 328 pieces of research data on high-tech enterprises in China were collected, and the hypotheses were verified using hierarchical regression analysis.

The results show that the two forms of network embeddedness – structural embeddedness and relational embeddedness, have a positive effect on enterprise innovation performance and a significant positive effect on organisational routine revision and organisational routine creation. Both organisational routine revision and organisational routine creation positively affect enterprise innovation performance and partially mediate the relationship between network embeddedness and enterprise innovation performance.

This conclusion provides a new perspective on the impact of network embeddedness on enterprise innovation performance and expands the related research on organisational routine updating. This study provides a theoretical reference for high-tech enterprises to improve their competitiveness and innovation performance through network embeddedness and organisational routine updating.

Lean construction (LC) consists of very effective techniques; however, its implementation varies considerably from one industry to another. Although numerous lean initiatives do exist in the construction industry, the research topic related to LC implementation is still unexplored due to the scarcity of validated assessment frameworks. This study aims to provide the first attempt in developing a structural model for successful LC implementation.

This study developed a Lean construction model (LCM) by critically reviewing seven previous LC frameworks from different countries, defining 18 subprinciples grouped into 6 major principles and formulating testable hypotheses. The questionnaire was pre-tested with 12 construction management experts and revised by 4 specialized academics. A pilot study with 20 construction units enhanced content reliability. Data from 307 Moroccan construction companies were collected to develop a measurement model. SPSS V. 26 was used for Exploratory Factor Analysis, followed by confirmatory factor analysis using AMOS version 23. Finally, a structural equation model statistically assessed each construct's contribution to the success of LC implementation.

This work led to the development of an original LCM based on valid and reliable LC constructs, consisting of 18 measurement items grouped into 6 LC principles: Process Transparency, People involvement, Waste elimination, Planning and Continuous improvement, Client Focus and Material/information flow and pull. According to the structural model, LC implementation success is positively influenced by Planning and Scheduling/continuous improvement (β = 0.930), followed by Elimination of waste (β = 0.896). Process transparency ranks third (β = 0.858). The study demonstrates that all these factors are mutually complementary, highlighting a positive relationship between LC implementation success and the holistic application of all LC principles.

To the best of the authors’ knowledge, this study is the first attempt to develop a statistically proven model of LC based on structural equation modelling analysis, which is promising for stimulating construction practitioners and researchers for more empirical studies in different countries to obtain a more accurate reflection of LC implementation. Moreover, the paper proposes recommendations to help policymakers, academics and practitioners anticipate the key success drivers for more successful LC implementation.

This paper aims to study the influence of cylindrical texture parameters on the lubrication performance of static and dynamic pressure thrust bearings (hereinafter referred to as thrust bearings) and to optimize their lubrication performance using multiobjective optimization.

The influence of texture parameters on the lubrication performance of thrust bearings was studied based on the modified Reynolds equation. The objective functions are predicted through the BP neural network, and the texture parameters were optimized using the improved multiobjective ant lion algorithm (MOALA).

Compared with smooth surface, the introduction of texture can improve the lubrication properties. Under the optimization of the improved algorithm, when the texture diameter, depth, spacing and number are approximately 0.2 mm, 0.5 mm, 5 mm and 34, respectively, the loading capacity is increased by around 27.7% and the temperature is reduced by around 1.55°C.

This paper studies the effect of texture parameters on the lubrication properties of thrust bearings based on the modified Reynolds equation and performs multiobjective optimization through an improved MOALA.