Search results

The purpose of this study is to develop a new hybrid method that combines interpretative structural modeling (ISM) and matrix cross-impact multiplication applied to classification (MICMAC) to investigate the influencing factors of sustainable infrastructure vulnerability (SIV).

(1) Literature review and case study were used to identify the possible influencing factors; (2) a semi-structured interview was conducted to identify representative factors and the interrelationships among influencing factors; (3) ISM was adopted to identify the hierarchical structure of factors; (4) MICMAC was used to analyze the driving power (DRP) and dependence power (DEP) of each factor and (5) Semi-structured interview was used to propose strategies for overcoming SIV.

Results indicate that (1) 18 representative factors related to SIV were identified; (2) the relationship between these factors was divided into a five-layer hierarchical structure. The 18 representative factors were divided into driving factors, dependent factors, linkage factors and independent factors and (3) 12 strategies were presented to address the negative effects of these factors.

The findings illustrate the factors influencing SIV and their hierarchical structures, which can benefit the stakeholders and practitioners of an infrastructure project by encouraging them to take effective countermeasures to deal with related SIVs.

Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC projects.

A case study methodology was adopted, including individual case analyses and comparative multiple-case analyses.

The results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with “leveraging the diverse features of certain mature DT” being a shared recognition of all studied companies.

This research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service customization.

This research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.

With growing concern about sustainable development and increased awareness of environmental issues, digital technologies (DTs) are gaining prominence and becoming a promising trend to improve productivity, sustainability and project performance in the construction industry. Nonetheless, the uptake of DTs in the construction industry has been limited and plagued with roadblocks. This study aims to identify critical barriers for construction organisations to adopt DTs and to demonstrate relationships between organisational characteristics and the perceived DTs adoption barriers.

This study adopted an explanatory sequential design by combining the advantages of quantitative and qualitative data. Data collection methods include literature review, a pilot study, questionnaire survey, and semi-structured interviews. Questionnaire data were analysed by using SPSS and multivariate regression technique. The interview data were processed by using content analysis to validate and supplement findings from the questionnaire.

Based on the survey and interview results, eight critical barriers were identified: the three top critical barriers are (1) “status quo industry standards”, (2) “lack of client interest” and (3) “lack of financial need/drive for using DTs”. The eight critical barriers were further classified into technical, environmental, and social dimensions to determine the major constructs that hinder DTs adoption. A theoretical framework articulating critical barriers with underlying components and root causes was also proposed. Furthermore, by using multivariate regression analysis, a model was developed to link the organisational characteristics with barriers to DTs adoption.

By referring to the framework and the model developed, academics, industry practitioners, and decision makers can identify pivotal areas for improvement, make informed decisions and implement remedial measures to remove the barriers to digitalisation transformation.

This study contributes to the literature on construction innovations by investigating barriers to DTs adoption holistically as well as perceptions of the impact of organisational attributes on these barriers. It establishes the groundwork for future empirical research into the strategic consolidation of movement of DTs adoption and diffusion.

The purpose of this paper is to elicit the expectations for resilient post-disaster rebuilds from Caribbean project end-users. In anticipation of future climatological, meteorological, hydrological or geophysical disasters disaster, key stakeholders can articulate and incorporate strategies for resilience development, thus leading to improved end-users’ satisfaction and confidence.

This paper engages the results of a systematic literature review that identified 24 empirical resilience factors for post-disaster reconstruction projects. These factors informed a semi-structured questionnaire to elicit the perspectives of Caribbean end-users on a seven-point Likert scale. The quantitative analysis of both factor ranking and principal component analysis was performed to identify correlations and provides further interpretations on the desires of the end-users for resilient rebuilds.

The results presented in this paper highlight the collective perspectives on the Caribbean end-users on what they perceived to be aiding more resilient reconstruction projects. They identified reconstruction designs mindful of future hazards, policies that aid climate change mitigation, active assessment of key structures, readily available funding sources and ensuring stakeholder’s unbiased interest as the top-most empirical factors. Factor analysis suggested collaborations with inclusive training and multi-stakeholder engagement, critical infrastructure indexing and effective governance as the critical resilience development factors.

To the best of the authors’ knowledge, this paper is first of its kind to explore the perspective of the Caribbean people regarding disaster reconstruction projects. It addresses developmental avenues for measurement indicators towards resilience monitoring and improvement. Additionally, the perspectives can provide construction industry professionals with tools for improved operational resilience objective-setting guidance, for Caribbean construction.

Microblogs are communication platforms for companies and consumers that challenge companies' brand marketing strategies. This paper provides a theoretical basis for expanding microblog applications and a practical basis for improving the effectiveness of brand marketing.

The authors use factor analysis to extract the factors of microblog user influence and construct a structural equation model to reveal the interaction mechanism of the influencing factors. Additionally, the authors clarify the promotion and enhancement effects of these factors.

Microblog user influence can be converted into richness, interaction and value factors. The richness factor significantly affects the latter two, whereas the interaction factor does not affect the value factor.

First, the sample used is limited to media industry practitioners. To increase generalizability, diverse groups should be included in future studies. Second, this model's theoretical explanatory ability can be further developed by adding other meaningful factors beyond the existing ones.

This study analyzes the factors of microblog user influence in China and validates the relevant elements. As a result, it improves the influence research on social media users and benefits the practice of information recommendation and microblog marketing.

The study examines health care inequities in viral load testing among hepatitis C (HCV) antibody-positive patients. The analysis predicts whether individual and census tract sociodemographic characteristics impact the likelihood of viral load testing.

This a study of 26,218 HCV antibody-positive patients in Orange County, California, from 2010 to 2020. The case data were matched with the 2017 American Community Survey to help understand the role of neighborhood socioeconomic characteristics in testing for viral load. Multivariable logistic regression was used to predict the probability of ever testing for HCV viral load.

Thirty-six percent of antibody-positive persons were never viral load tested. The results show inequalities in viral load testing by sociodemographic factors. The following groups were less likely to ever test for viral load than their counterparts: (1) individuals under 65 years old, (2) females, (3) residents of census tracts with lower levels of health insurance enrollment, (4) residents of census tracts with lower levels of government health insurance, and (5) residents of census tracts with a higher proportion of non-white residents.

This is a secondary database from public health department reports. Using census tract data raises the issue of the ecological fallacy. Detailed medical records were not available. The results of this study emphasize the social inequality in viral load testing for HCV. These groups are less likely to be treated and cured, and may spread the disease to others.

This chapter is unique as it combines routinely collected public health department data with census tract level data to examine social inequities associated with lower rates of HCV viral load testing.

The authors hope to filter valuable information from online reviews, obtain objective and accurate information about the demands of auto consumers and help auto companies develop more reasonable production and marketing strategies for healthy and sustainable development. This paper aims to discuss the aforementioned objectives.

The authors collected review data from online automotive forums and generated a corpus after pre-processing. Then, the authors extracted consumer demands and topics using the LDA model. Finally, the authors used a trained Word2vec tool to extend the consumer demand topics.

Different types of vehicle consumers have the same demands, such as “Space,” “Power Performance,” and “Brand Comparison,” and distinct demands, such as “Appearance,” “Safety,” “Service,” and “New Energy Features”; consumers who buy new energy vehicles are still accustomed to comparing with the brands or models of fuel vehicles; new energy vehicles consumers pay more attention to services and service quality during the purchasing and using process.

The development time of new energy vehicles is relatively short, with some models being available for only one year or even six months. The smaller amount of available data may impact the applicability of topic models. The sample size, especially for new energy vehicles, needs to be increased to improve the general applicability of topic models further.

First, this measure helps online review websites improve their existing review publication mechanisms, enhance the overall quality of online review content, increase user traffic and promote the healthy development of online review websites. Second, this allows for timely adjustments in future product production and sales plans and further enhances automotive companies' ability to leverage online reviews for Internet marketing.

The authors have improved the accuracy and stability of the fused topic model, providing a scientific and efficient research tool for multi-dimensional topic mining of online reviews. With the help of research results, consumers can more easily understand the discussion topics and thus filter out valuable reference information. As a result, automotive companies may gain information about consumer demands and product quality feedback and thus quickly adjust production and marketing strategies to increase sales and market share.

The purpose of this paper is to explore how a politically connected firm moderates the relationship between media coverage and market value. More specifically, the authors are interested in the interplay of an external corporate governance (CG) mechanism with an internal one. By interacting different mechanisms, this paper advances the empirical setting of application and functions of the corporate governance.

This paper tests the hypotheses presented using panel data with a fixed-effect model, by assembling and exploiting a unique, hand-collected set of data on media coverage consisting of over 164,000 media reports and a politically connected board of directors comprising over 12,000 CVs tracked from 2010 to 2014. Data is originally from Brazil, a country where political connections are highly used by firms and that has been a place of much research on corporate political activity.

The results of this paper suggest that a politically connected board of directors can mitigate the negative effects of media coverage on market value. Overall, the results imply that the validity of a CG mechanism might be affected by other mechanisms.

The findings of this paper imply the need for research focusing on the mutual effects of different CG mechanisms. While CG is understood as a set of mechanisms, new research could focus on the interplay of these mechanisms.

The findings suggest that the presence of former politicians and government officers on the board dissipates bad news reported by the media and boosts market value when media is positive. To maximize investment returns, investors should analyze firms' political human capital.

To the best of the authors’ knowledge, this paper is the first to develop hypotheses on the moderation effects of a politically connected board on the relation between media coverage and market value. This is relevant because this brings insights on how firms could jointly manage these mechanisms.

This paper aims to study the interplay between a risk-averse national brand manufacturer's (NBM) selling mode decision and a risk-neutral e-platform's private brand (PB) introduction decision.

A game theory model is used to solve selling mode decision, that is whether transform the selling mode from the wholesale mode to the marketplace mode, and PB introduction decision, that is, whether introduce the PB.

The results show that for the NBM, under certain condition, the NBM's selling mode decision is not affected by the e-platform's PB introduction decision. High revenue-sharing rate is conducive only when the difference in consumer preference between the PB and the national brand (NB) is small. The NBM's risk aversion will improve the applicability of the marketplace mode. For the e-platform, high PB preference of consumers and risk-averse behavior of the NBM is not conducive to PB introduction. For the supply chain, scenarios that the NB monopolizes the market under the wholesale mode and PB introduction under the marketplace mode should be prevented. PB introduction under the wholesale mode will become the only equilibrium with the increase of risk aversion of the NBM. Finally, the authors extend the scenario that consumers prefer the PB and the e-platform is risk-averse enterprise and find that PB introduction under the wholesale mode is detrimental to the NBM but beneficial to the supply chain. The impact of consumers' PB preference on the e-platform's PB introduction is opposite to the basic model. The impact of the e-platform's risk aversion on game equilibrium is opposite to that of the NBM's risk aversion.

This paper is first to study selling mode decision and PB introduction decision when considering enterprises' risk-averse attitude.

This study aims to examine the effects of in-game advertisement congruity, interactivity and intrusiveness on gamers’ attitude towards advertising and purchase intention towards advertised brands based on the stimulus-organism-response (SOR) model.

This study uses a structured online questionnaire to collect the data from 311 gamers aged between 18 and 35 years. This study examines mediation using bootstrapping.

This study authenticates the appropriateness of the SOR model in predicting the advertised brand purchase intentions. The results of this study indicated that attitude has a significant mediating role in the relationship of advertisement congruity, interactivity and intrusiveness with advertised brand purchase intentions. The results further revealed that this mediation was partial for all three relationships.

The outcomes of the study are expected to benefit researchers and scholars to identify future research directions and thereby extend current know-how on gamification in general and in-game advertising in particular. The study findings will hold significance for marketers, advertisers and media planners too. By bringing out specific allied issues connected with in-game advertising, this study will help these stakeholders to plan their marketing campaigns in an efficient manner leading to higher traction and return on investment.

This study provides a new perspective to comprehend the purchase intention of gamers for brands advertised in online games through mediation by applying the underpinnings of the SOR model.