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This study aims to identify and rank the key success factors linked with digitalization in the Indian construction sector. Because the construction firms in India are in the early stages of implementing digitalization in their operations, it provides a framework from which they may focus on the effectiveness of digitalization.

This research study examines 12 success factors related to digitalization in construction, which are derived from various sectors. Furthermore, experts from the construction industry and academia have validated these factors with respect to the Indian construction sector. The multi-criteria decision-making techniques are further used to examine the interrelationship, ranking and weightage of digitalization success. Finally, the success factors are validated through a questionnaire-based empirical study followed by ranking using a t-test. The results from both approaches (company-specific and generalized) are compared and discussed.

This research identifies that selecting appropriate digital methods and techniques is a critical success factor as far as digitalization in the Indian construction scenario is concerned. Besides that, continuous monitoring and control in digital implementation significantly impact other factors.

While similar results are obtained from approaches adopted in the study, a few success factors appear to differ in terms of their ranking position. Further studies can explore the finer details that can explain the behavior pattern. This study can also be extended by assessing the structural relationship among the identified factors that can throw more light on the dynamics of the continuation of digitalization in construction which can further help in formulating policies or digitalization rollout.

The outcome of this study sheds light on construction business knowledge by stressing key success elements connected to digitalization in construction processes in the Indian construction sector. Moreover, this study shows that the success of digitalization in construction is similar to that of transformation in the information technology industry, where adopting suitable digital methods and techniques plays a vital role in the transformation process.

Despite the multiple benefits of construction digitalization, limited research focuses on digitalization success factors, making this study unique. Furthermore, this study demonstrates that integrating Fuzzy decision-making trial and evaluation laboratory and maximum mean de-entropy approaches may be used to successfully prioritize success factors in the nascent stage of construction digitalization.

The study aims to analyze factors impacting firms’ success and persistence in a digital platform competition using the structure-conduct-performance (SCP) framework. The study also includes real-life cases that are beneficial to academicians and practitioners to understand and develop strategies for success and persistence during uncertainty.

A literature review to identify the factors that impact success and persistence in a digital platform competition was conducted following Webster and Watson (2002). Findings were integrated into a SCP framework to examine and understand the identified factors’ relational impact.

While analyzing factors under the SCP framework, all factors were divided into three categories: those impacting positively, those impacting negatively and those with ambiguous impact on the success and persistence in digital platform competition. Digital platform firms can exploit the positively impacting factors to increase market share by being distinctive from other digital platform firms and becoming dominant by withstanding competition. On the other hand, negatively impacting factors increase barriers to entry, intensify competition and reduce the distinctiveness of digital platform firms. Lastly, a few factors may have either a positive or a negative impact depending upon the particular characteristics of the firm/industry.

The study opens the scope for future research on empirically testing the developed conceptual framework and relationships by developing propositions to posit the possible impact of these factors on digital platforms’ success and persistence.

The study contributed to the existing literature by using SCP framework to analyze the factors affecting firm’s success and persistence in a digital platform competition. Also, the study has discussed the relational impact of factors rather than their impact in isolation.

As the complexity and uncertainty of megaprojects make it difficult for traditional management models to address the difficulties, this paper aims to design a performance incentive contract through IT applications, thereby promoting the formation of an information-based governance mechanism for megaprojects and facilitating the transformation and upgrading of the construction management model of megaprojects to informatisation.

This paper introduced IT applications into the performance assessment and used the proportion of IT applications replacing traditional manual management as a variable. It analysed different replacement ratios to obtain the optimal solution for the change of contractors behaviours and promote the optimal performance incentive for the informatisation in megaprojects.

The results show that under the condition of the optimal replacement ratio, achieving the optimal state of a mutual win-win situation is possible for the benefit of both sides. The counter-intuitive finding is that the greater the replacement ratio is not, the better, but those other constraints are also taken into account.

This study enriched the research of the performance configuration incentive from a practical perspective. It extended the research framework of IT incentive mechanisms in the governance of megaprojects from a management theory perspective. It clarified the role of IT applications in incentive mechanisms and the design process of optimal incentive contracts under different performance incentive states. The incentives made the contractors work harder to meet the owner's requirements, and it could improve the efficiency of megaprojects, thus better achieving megaproject objectives.

The aim of this study is first, to investigate the relative effect of user-generated content (UGC) and firm-generated content (FGC) on online brand advocacy, and second, to examine the mediation effect of customer engagement and the moderation effect of brand familiarity in the relationship between UGC and FGC and online brand advocacy. The differential impact of UGC and FGC on consumer behavior has yet to receive sufficient academic attention among hospitality scholars.

Based on social learning theory, cognitive consistency theory and schema theory, this study established an integrated research framework to explain the relationship between the constructs of the study. This study adopts a scenario-based experimental design in two separate studies within contexts to examine the proposed hypotheses.

The results revealed that UGC is a stronger predictor of online brand advocacy than FGC. A mediation analysis supported that the effect of digital content marketing types on online brand advocacy occurs because of customer engagement. Further, when the brand was familiar, participants showed a higher level of online brand advocacy than when they were exposed to FGC (vs. unfamiliar brand), whereas the effect of familiar and unfamiliar brands on online brand advocacy remains slightly close to each other when the participants were exposed to UGC. Brand familiarity positively enhanced participants’ engagement when they were exposed to UGC. Further, customer engagement is only a significant mediator when the brand is unfamiliar.

This paper presents significant managerial implications for hospitality companies about how they can effectively enhance brand advocacy in the online medium.

This research provides a novel contribution by examining the differential impact of UGC and FGC on online brand advocacy as well as uncovering the underlying mechanism of how and under what conditions user- and firm-generated content promotes online brand advocacy in the hospitality context.

Accurate and rapid tracking and counting of building materials are crucial in managing on-site construction processes and evaluating their progress. Such processes are typically conducted by visual inspection, making them time-consuming and error prone. This paper aims to propose a video-based deep-learning approach to the automated detection and counting of building materials.

A framework for accurately counting building materials at indoor construction sites with low light levels was developed using state-of-the-art deep learning methods. An existing object-detection model, the You Only Look Once version 4 (YOLO v4) algorithm, was adapted to achieve rapid convergence and accurate detection of materials and site operatives. Then, DenseNet was deployed to recognise these objects. Finally, a material-counting module based on morphology operations and the Hough transform was applied to automatically count stacks of building materials.

The proposed approach was tested by counting site operatives and stacks of elevated floor tiles in video footage from a real indoor construction site. The proposed YOLO v4 object-detection system provided higher average accuracy within a shorter time than the traditional YOLO v4 approach.

The proposed framework makes it feasible to separately monitor stockpiled, installed and waste materials in low-light construction environments. The improved YOLO v4 detection method is superior to the current YOLO v4 approach and advances the existing object detection algorithm. This framework can potentially reduce the time required to track construction progress and count materials, thereby increasing the efficiency of work-in-progress evaluation. It also exhibits great potential for developing a more reliable system for monitoring construction materials and activities.

Digital transformation (DT) innovation is a monumental contribution that has had a profound effect on several worldwide industries. The aim of this research is to evaluate the current and future trends in DT specifically focusing in construction industry.

This study adopts a qualitative analysis approach grounded on descriptive and bibliometric analyses. In total, 283 papers from Scopus between January 2015 and April 2023 were retrieved in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) review methodology. This study examines the publishing trends, most productive nation, university, publications and authors. Keyword co-occurrence analysis and thematic evolution were analyzed through Vosviewer and Biblioshiny.

The results illustrate a growing desire to use digital technologies in the construction industry, which shows the topic's power and expanding popularity. This research reveals various emerging themes based on technology usage in construction sector. Out of 14 themes, occupational health and safety, mass customization, virtual reality and artificial intelligence were identified as isolated themes. Further, this study elaborates the difficulties encountered by the construction industry while employing digital technologies and examines the interrelationships among various keywords in DT and reveals the paradoxes and hotspots.

This research adds to the body of literature as it identifies the research areas and gaps in the existing DT domain in construction industry. The integration of technology in this sector has an intense positive future vision as various subareas have immense potential for technology application.

The purpose of this paper is to conduct a critical analysis of the commonly projected visions on the future of built environment, focusing on transformative research. The primary question is will the construction sector be able to make the projected transformative leap even if the history of technology adoption in construction suggests otherwise? And, what role can academic research play?

This paper is based on a reflective research and qualitative review of academic articles, white papers and reported projections for the future of construction. The reflections are based on discussions with colleagues and students, including thought experiments.

There is a general agreement across various sources about the key technical and social drivers for the future of construction. However, these projections seem to be emanating from industry insiders, and more diversity and creativity is needed in exploring alternative possibilities.

The paper should be useful for researchers in assessing their research strategy, especially those aiming to focus on the future of construction and transformative research. The findings of this paper suggest the need for collaboration and explorations with diverse disciplines, including those that may not appear immediately connected to digital construction.

The paper should be useful for individuals and organizations, especially start-ups that are seeking novel opportunities to disrupt the future of construction.

The originality and value of this research lies in a timely critique of the commonly projected trends in the future of digital construction. The use of reflective research and thought experiments emphasizes the need for divergent thinking and creative research methods in construction research.

This paper aims to examine how content relevancy influences consumers’ preference to receive and share fake news. Further, it investigates how these receivers perceive the social image of the people who share fake news. Finally, this study examines how brand strength and valence and credibility of fake content influence consumer’s word-of-mouth recommendations, purchase intentions and attitude toward the brand.

Three experiments were conducted to test the hypotheses. The data was analyzed using a two-way analysis of variance and PROCESS techniques.

Findings indicate that people prefer to receive and share relevant content, even if it is fake. Sharing fake news conveys the sender’s sociability but also creates a negative perception of narcissism. Individuals are more likely to recommend a brand if the fake news is perceived as credible and positive (vs negative). Finally, brand-strength can help brands to negate the harmful effects of fake news.

Future research can explore the role of group dynamics, tie-strength and media richness (text, image and videos) in the dispersion of fake news and its impact on brands.

Marketers should communicate and educate consumers that sharing fake content can harm their social image, which can reduce information dispersion. Marketers should also improve brand-strength that can protect the brand against the adverse impact of fake news.

This study contributes to the emerging literature on fake news by studying the impact of fake news on consumer intentions and attitudes toward the brand, which are critical for the success of any brand.

This paper aims at developing an improved method, based on binary search algorithm (BSA) for the steady-state analysis of self-excited induction generators (SEIGs), which are increasingly used in wind energy electric conversion systems. The BSA is also compared with linear search algorithm (LSA) to bring out the merits of BSA over LSA.

All the parameters of SEIG, including the varying core loss of the machine, have been considered to ensure accuracy in the predetermined performance values of the set up. The nodal admittance method has been adopted to simplify the equivalent circuit of the generator and load. The logic and steps involved in the formulation of the complete procedure have been illustrated using elaborate flowcharts.

The proposed approach is validated by the experimental results, obtained on a three-phase 240 V, 5.0 A, 2.0 kW SEIG, which closely match with the corresponding predicted performance values. The analysis is shown to be easy to implement with reduced computation time.

A novel improved and simplified technique has been formulated for estimating the per unit frequency (a), magnetizing reactance (X_m) and core loss resistance (R_m) of the SEIG using the nodal admittance of its equivalent circuit. The accuracy of the predetermined performance is enhanced by considering the SEIG’s varying core loss. Only simple MATLAB programming has been used for adopting the algorithms.

This study aims to develop a model for coordination and communication overhead in distributed software development through case study analysis in the Indian outsourcing software industry. The model is based on business knowledge, which can be classified as domain, regulatory, strategic, business process and operation process knowledge as per existing literature.

Double case study method was used to verify an existing knowledge–management framework of software development from the literature. The stakeholders of both the cases were interviewed, and project documents were verified to reach conclusions.

The findings supported the business knowledge classification from the literature. The concept can be used to analyze the software project in a distributed environment.

The research work findings are based only on two case studies. The study findings cannot be generalized and should be used as a learning tool. There can be large variations of project characteristics with differences in business knowledge requirements. The research shows the importance of business knowledge transfer in global software development.

Projects managers in the distributed software development environment can use the findings in project planning and work allocation for better control over cost and schedule, etc.

There is little research works attempted to study the business knowledge classification in the global software industry making the research novel.