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Dark tourism, a phenomenon encompassing visits to sites associated with death, suffering, and historical atrocities, has gained increasing scholarly attention in recent years. This chapter explores the concept's historical roots, motivations for engagement, and its transformative impact on heritage sites, culminating in a case study of the Malcha Mahal Haunted Heritage Walks in Delhi. Despite being abandoned for centuries, this historic site gained prominence with the occupation by the self-proclaimed royal family of Oudh in the 1980s. The introduction of the Haunted Heritage Walk by Delhi Tourism aimed to harness the dark tourism potential of this previously neglected monument. However, initial challenges such as deteriorating conditions and safety concerns necessitated collaborative efforts with government departments for conservation and site preparation. Interviews with visitors revealed diverse motivations for attendance, ranging from thrill-seeking to appreciation of the monument's historical significance. Since the walk's inception, conservation efforts have commenced, accompanied by landscaping initiatives and amenities for visitors. While the future conservation and tranquility of Malcha Mahal remain uncertain amid increasing tourist interest, its transformation into an alternative destination within Delhi underscores the potential of dark tourism to revitalize neglected heritage sites. Sustainable tourism planning is essential to preserve the monument's unique features and manage tourism while maintaining its integrity for future generations.

Consumer-perceived review attitude determines consumer overall information adoption and is a core part of consumer’s online-shopping. This study aims to focus on factors that could influence consumer review attitude and can be used by marketers to shape individual information perception.

The study used the questionnaire method to collect data from online shoppers and the modelling of structural equations as an empirical approach to analyse the data.

The findings demonstrate that both systematic and heuristic cues impact the reviewer’s credibility and perceived website attitude differently, which, in turn, influence review attitude. Review characteristics, such as factuality, consistency and relevancy, have a positive relationship with reviewer credibility, while only review consistency and relevancy appears to have a relationship with review attitude. Website characteristics such as reputation, familiarity and social interactivity positively influence the website attitude, which positively influences review attitude. Apart from this, review skepticism has a significant negative relationship with review attitude.

This study could help to foster a positive attitude towards online reviews. Digital marketers need to motivate trusted reviewers to post consistent, fact-based reviews. Further improving the overall website reputation and interactivity could bring a positive attitude towards the reviews. Also, digital marketers must filter and avoid contradictory reviews or reviews that have a bipolar message and reviews expressing numerous emotions to enhance review relevance and consistency.

The current study addresses the need to understand the formation of consumer review attitude through both review and website characteristics using heuristic – systematic model. The paper captures the complex process undergone by the consumer to decipher review attitude and thereby extend the understanding of consumer information processing.

Many economic, political and socio-cultural events in the 2020s have been strong headwinds for architecture, engineering and construction (AEC). Nevertheless, technological advancements (e.g. artificial intelligence (AI), big data and robotics) provide promising avenues for the development of AEC. This study aims to map the state of the literature on automation in AEC and thereby be of value not only to those researching automation and its composition of a variety of distinct technological and system classes within AEC, but also to practitioners and policymakers in shaping the future of AEC.

This review adopts scientometric methods, which have been effective in the research of large intra and interdisciplinary domains in the past decades. The full dataset consists of 1,871 articles on automation in AEC.

This overarching scientometric review offers three interdisciplinary streams of research: technological frontiers, project monitoring and applied research in AEC. To support the scientometric analysis, the authors offer a critical integrative review of the literature to proffer a multilevel, multistage framework of automation in AEC, which demonstrates an abundance of technological paradigm discussions and the inherent need for a holistic managerial approach to automation in AEC.

The authors underline employee well-being, business sustainability and social growth outcomes of automation and provide several managerial implications, such as the strategic management approach, ethical management view and human resource management perspective. In doing so, the authors seek to respond to the Sustainable Development Goals proposed by the United Nations as this becomes more prevalent for the industry and all levels of society in general.

Prodigious teamwork is the basis for augmenting the level of productivity on construction projects. Globalisation of the construction market has meant that many practitioners work outside of their geographical spectrum; however, the multicultural dissimilarities of construction workforces within the project management team (and how these may impact upon project productivity performance) have been given scant academic attention. To bridge this knowledge gap, this paper aims to analyse the effects of a multicultural workforce on construction productivity.

The epistemological positioning of the research adopted mixed philosophies (consisting of both interpretivism and postpositivism) to undertake a deductive and cross-sectional survey to collate primary quantitative data collected via a closed-ended structured questionnaire. Census sampling and convenience sampling techniques were adopted to target Ghana’s construction workforce and their opinions of the phenomenon under investigation. Out of 96 questionnaires administered, 61 were retrieved. The data obtained were analysed by using mean score ranking, relative important index, one sample t-test and multiple regression. The reliability of the scale was checked by using Cronbach’s alpha coefficient.

From the t-test analysis, 11 variables sourced from extant literature, and the null hypothesis for the study was not rejected and all factors (except high cost of training and improper gender diversity management) were affirmed as negative effects of the multicultural workforce on construction productivity. Using multiple regression analysis, six of the independent variables were shown to impact upon productivity. The goodness of fit was verified by collinearity and residual analysis. The model’s validation revealed a relatively high predictive accuracy (R² = 0. 589), implying that the results could be generalized. In culmination, these findings suggest that the predictors can be used to accurately predict the effects of multicultural workforce on construction productivity performance.

The findings indicate that multicultural workforce/teams have a substantial effect on overall construction productivity in the construction sector; consequently, stakeholders must address this issue to enhance productivity across the sector.

The current study significantly contributes to our understanding of how multicultural workers/teams affect construction productivity in the construction business perspective and how to respond to the negative menace.

This study aims to assess the usability of augmented reality (AR) based mobile app for excavation and earthmoving processes using a novel tool entitled Excavator Augmented Reality (EAR).

A mixed-methods research approach was used through conducting experimentation to collect qualitative and quantitative data collected from the Sri Lankan construction sector. EAR app was used for experimentation in outdoor areas examining how a 360° tracked hydraulic excavator can be navigated in different physical environments similar to the real prospected job.

The findings reveal that EAR could make a considerable impact on enhancing productivity, safety and training processes. However, the developed EAR App subjected to assessment demonstrated the highest satisfaction gap for the auditory aspects. Among the remaining criterion, the satisfaction met user expectations for comfortability and no-risk practice. An analysis of strengths, weaknesses, opportunities and threats (SWOT analysis) conducted revealed that visualising the excavator activities and the requirements of improved features were the highest agreed strengths and weaknesses of the EAR. Among the opportunities for improvement, the necessity of improving emergency and safety reached the highest agreement. Moreover, the study presented the challenges in introducing mobile augmented reality (MAR) to the construction sector under the political, economic, sociocultural, technological, environmental and legal (PESTEL) model along with solutions to be taken.

This study provides a novel approach to addressing the safety, productivity and training concerns in heavy mobile plants and machinery on construction sites which remains to be unexplored to this end.

Drawing upon the cognitive-affective processing system (CAPS) framework, the current study proposes a dual-pathway model that suggests self-serving leadership has a positive influence on employee knowledge hiding. The study also examines the mediating effects of relative deprivation and emotional exhaustion, as well as the moderating effect of political skill, to provide a comprehensive understanding of these relationships.

This study employed two-wave time-lagged survey data collected from 644 employees in 118 teams within a company based in Shenzhen, China. Moreover, hierarchical linear modeling (HLM) was used to test the hypothesized relationships.

The results indicated that self-serving leadership positively influenced employee knowledge hiding, and this relationship was mediated by relative deprivation and emotional exhaustion. Additionally, political skill was found to negatively moderate both the direct relationship between self-serving leadership and relative deprivation and emotional exhaustion, and the indirect path from self-serving leadership to employee knowledge hiding through relative deprivation and emotional exhaustion.

This study makes a unique contribution to the knowledge management literature in several ways. First, it introduces self-serving leadership as a predictor of employee knowledge hiding, expanding the current understanding of this phenomenon. Second, it offers a novel conceptualization, suggesting that employees coping with self-serving leadership may experience relative deprivation and emotional exhaustion, and these factors can predict their engagement in knowledge hiding. Third, the research findings on the moderating role of political skill push the boundaries of the knowledge-hiding literature, providing new insights into the conditions under which this behavior occurs.

An increase in outsourcing of consultancy services has been observed during procurement and delivery of public-sector infrastructure projects. However, the incidence of project failure has continued unabated despite this shift by public-sector entities. Also, there appears to be limited literature focussed on seeking to provide the rationale governing the decision to outsource or insource consultancy services by public-sector organisations. The purpose of this study was to appraise the performance of public-sector projects in which consultancy services have been outsourced or insourced. These are the gaps which this study was undertaken to fill.

A grounded theory methodology (GTM) research design was adopted based on the nature of evidence sought and gathered from a Provincial Department of Public Works and Infrastructure (PDPWI) in South Africa. Data was obtained from a mixture of semi-structured interviews and project-specific documents spanning a five-year period and was analysed according to the procedures associated with GTM. Accordingly, open coding, axial coding and pattern matching were carried out at several intervals to develop categories and themes.

The findings of the study showed the absence of a structured approach within the PDPWI for facilitating decisions pertaining to outsourcing or insourcing consultancy services within construction projects. Furthermore, the study established that both approaches yielded similar results across all performance facets of cost, time and quality. In addition, a detailed insight into the steps required for the successful application of GTM in built environment research has been provided in the study.

Limited studies have been undertaken to compare the impact of either outsourced or insourced services on the organisational and project performance. This was the gap to which the study reported in this paper was undertaken to contribute.

While cyberloafing has emerged as a prevalent issue in numerous workplaces, research on its consequences is still underdeveloped, highlighting a need for further exploration and analysis. Drawing upon the cognitive appraisal theory of emotion, this study investigates the influence of coworkers' cyberloafing on employees' workplace incivility, mediated by negative emotions and moderated by task interdependence.

In Study 1, the hypothesized research model was tested utilizing three-wave time-lagged survey data collected from 333 employees and their coworkers. In Study 2, an additional sample of 274 employees was surveyed. Data were analyzed using hierarchical regression analysis and the bootstrap method.

The results indicated that coworkers' cyberloafing positively influenced employees' workplace incivility, with this relationship mediated by negative emotions. Additionally, task interdependence was found to positively moderate both the direct relationship between coworkers' cyberloafing and negative emotions and the indirect path from coworkers' cyberloafing to employees' workplace incivility through negative emotions.

This study helps managers gain a deeper understanding of cyberloafing's effects, enabling them to manage and curb it more effectively.

Prior research has predominantly explored the effects of cyberloafing on its implementers. However, this study innovatively shifts focus to the observer perspective, empirically demonstrating whether and how coworkers' cyberloafing affects employees' workplace incivility, enriching and expanding the existing literature.

The study aims to determine the long and short-term causal relationships between the variables associated with the adjustment of monetary policy and the stock market in India in the presence of structural breaks.

The study employed the autoregressive distributed lag (ARDL) bounds test and the Error Correction Model to assess long- and short-term causal relationships. The study also used non-frequentist Bayesian inferences for the validity of estimation robustness. The Bai–Perron test is used to identify breakpoint dates for the Indian stock market index, and the Granger Causality test is employed to ascertain the direction of causality.

The F-bounds test reveals cointegration among the variables throughout the examined period. Specifically, the weighted average call money rate (WACR), inflation (WPI), currency exchange rate (EXE), and broad money supply (M3) exhibit statistical significance with precise signs. Furthermore, the study identifies the negative impact of the COVID-19 outbreak in March 2020 on the Indian stock market.

Although the study provides significant insights, it is not exempt from constraints. A significant limitation is selecting a relatively limited time period, specifically from April 2008 to September 2023. The limited time frame of this study may restrict the applicability of the results to more comprehensive economic settings, as dynamics between the monetary policy and the stock market can be influenced by multiple factors over varying time periods. Furthermore, the utilisation of the Weighted Average Call Money Rate (WACR) rather than policy rates such as the Repo rate presents an additional constraint as it may not comprehensively account for the impacts of particular policy initiatives, thereby disregarding essential complexities in the connection between monetary policy variables and financial markets.

The findings of the study suggest that investors and portfolio managers should consider economic issues while developing long-term investing plans. Reserve Bank of India should exercise prudence to prevent any discretionary measures that may lead to a rise in interest rates since this adversely affects the stock market. To mitigate risk, investors should closely monitor the adjustment of monetary policy variables.

The study has important social implications, especially regarding the lower levels of financial literacy among investors in India. Considering the complex nature of the study’s emphasis on monetary policy adjustments and their impact on the stock market. Investors face the risk of significant losses due to unexpected adjustments in monetary policy. Many individuals may need help understanding how policy changes impact their investments. Therefore, RBI must consider both price and financial stability when formulating monetary policies. Furthermore, market participants should consider the potential impact of fluctuating monetary policy variables when devising their long-term investment strategies. Given that adjustments in interest rates can markedly affect stock market dynamics, investors must carefully assess the implications of monetary policy decisions on their portfolios.

The study uses dummy variables in the ARDL model to represent structural breaks that emerged from the COVID-19 pandemic (as determined by the Bai–Perron multiple breakpoint test). The study also used the Perron unit root test to find out the stationary of the series in the presence of structural breaks. Additionally, the study also employed Bayesian inferences to affirm the robustness of the estimates.

Resident perceptions of tourism impacts are a swiftly growing area in tourism research that has the potential to contribute to sustainability of destinations. Understanding and analyzing the perceptions of local communities for improving destination attractiveness is key to many destinations, the most popular being mountainous regions. Leh, Ladakh, in the northern part of the Trans-Himalayan region is a renowned Indian tourist place, which sees hordes of tourists in the short summer season. The influx of a large number of visitors in the short season has proved beneficial and also a problem for the destination as tourist numbers overpower the local population numbers leading to pressure on natural resources. Costs of mass tourism are becoming prominent each year and if not scrutinized can damage the likeability of the place. This research attempts to understand resident opinions of impacts of tourism in Leh through primary research. It also aims to find out the link between the demographic profile of residents and perceptions of tourism impacts using a Chi-square test. Results suggest that residents perceive many unfavorable impacts of tourism along with positive impacts. The Chi-square test reveals a significant association between demographic variables and tourism impacts.