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Contemporary technological disruptions are espoused as though they stimulate sustainable growth in the built environment through the Green Internet of Things (G-IoT). Learning from discipline-specific experiences, this paper articulates recent advancements in the knowledge and concepts of G-IoT in relation to the construction and smart city sectors. It provides a scoping review for G-IoT as an overlooked dimension. Attention was paid to modern circularity, cleaner production and sustainability as key benefits of G-IoT adoption in line with the United Nations’ Sustainable Development Goals (UN-SDGs). In addition, this study also investigates the current application and adoption strategies of G-IoT.

This study uses the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) review approach. Resources are drawn from Scopus and Web of Science repositories using apt search strings that reflect applications of G-IoT in the built environment in relation to construction management, urban planning, societies and infrastructure. Thematic analysis was used to analyze pertinent themes in the retrieved articles.

G-IoT is an overlooked dimension in construction and smart cities so far. Thirty-three scholarly articles were reviewed from a total of 82 articles retrieved, from which five themes were identified: G-IoT in buildings, computing, sustainability, waste management and tracking and monitoring. Among other applications, findings show that G-IoT is prominent in smart urban services, healthcare, traffic management, green computing, environmental protection, site safety and waste management. Applicable strategies to hasten adoption include raising awareness, financial incentives, dedicated work approaches, G-IoT technologies and purposeful capacity building among stakeholders. The future of G-IoT in construction and smart city research is in smart drones, building information modeling, digital twins, 3D printing, green computing, robotics and policies that incentivize adoption.

This study adds to the normative literature on envisioning potential strategies for adoption and the future of G-IoT in construction and smart cities as an overlooked dimension. No previous study to date has reviewed pertinent literature in this area, intending to investigate the current applications, adoption strategies and future direction of G-IoT in construction and smart cities. Researchers can expand on the current study by exploring the identified G-IoT applications and adoption strategies in detail, and practitioners can develop implementation policies, regulations and guidelines for holistic G-IoT adoption.

The purpose of this study is to investigate the current construction progress monitoring (CPM) process in relation to the contractual obligations, how project management teams carry out this activity in the field and why teams continue to adopt the current method. The study aims to provide a comprehensive understanding of the current monitoring process and its effectiveness, identify any shortcomings and propose recommendations for improvements that can lead to better project outcomes.

The study conducted semi-structured interviews with 28 construction management practitioners to explore their views on contractual requirements, traditional progress monitoring practices and advanced monitoring methods. Thematic analysis was used to identify existing processes, practices and incentives for advanced monitoring.

Standard construction contracts mandate current progress monitoring practices, which often rely on manual, document-centric and labor-intensive methods, leading to slow and erroneous progress reporting and project delays. Key barriers to adopting advanced tools include rigid contractual clauses, lack of incentives and the absence of reliable automated tools. A holistic automated approach that covers the entire CPM process, from planning to claim management, is needed as a viable alternative to traditional practices.

The study's findings can inform researchers, stakeholders and decision-makers about the existing monitoring practices and contribute to enhancing project management practices.

The study identified contractually mandated progress monitoring processes, traditional methods of collecting, transferring, analyzing and dispensing progress-related information and potential incentives and points of departure towards technologically advanced methods.

The purpose of the study was to develop a performance flat-plate solar collector that would be used as a solar drier for fruit fig (Ficus carica L). This study proposes how and why solar energy is important for drying the agricultural products. This study aims to expand the domain of solar collector for different purposes and, most important, for agricultural resource normally found in the literature.

The paper opted for an exploratory study using the flat-plate solar collector with drying chamber for drying purposes of agricultural products. During the experiment, the data were collected with moisture content, drying rate of the product and solar irradiation falls on the collector.

This paper describes that how flat-plate collector works for agricultural products and how to reduce the moisture content in the product (fig). Efficiency of collector was evaluated under the ambient temperatures of 24°C. Efficiency also significantly increased from 53 to 55 per cent with an increase in ambient temperature from 22 to 24 °C. Figs (Ficus carica L) were dried in the drying chamber of the flat-plate solar collector. The products were dried at temperature of 55-65°C and 15 to 20 per cent humidity.

Because of this research chosen, the research results are beneficiary for agricultural users for drying purposes. Therefore, the researchers are encouraged to dry the agricultural product with flat-plate solar collector, because it reduced the moisture content of the product very fast.

This paper fulfills an identified need to study that how flat-plat solar collector can be used.

The purpose of this paper is to investigate the critical decision factors of public–private partnership (PPP) concession which is complex due to a number of uncertain and random variables. To identify critical factors contributing to determination of concession period, this study reviews the published literature. It also identifies countries contributing most in PPP research. As a whole, it provides a mutually beneficial scenario by formulating a decision-making matrix.

This paper reviews the literature published during the period 2005-2015. A two-staged methodology is followed on retrieved scholarly papers: first, countries contributing to PPP are identified along with authors and affiliated institutions. Second, using frequency analysis of shortlisted critical factors, yearly appearance and stakeholders affected, a decision matrix is formulated.

The most contributing country toward PPP research is China, followed by the USA both in terms of country- and author-based contribution. In total, 63 factors are identified that affect PPP concession out of which, 8 per cent are highly critical and 21 per cent are marginally critical for decision-making.

Critical factors of PPP concession period will be identified with the help of decision-making matrix. This will help in adequate resource allocation for handling critical factors ensuring project success. Researchers may also understand the research trends in the past decade to usher ways for future improvements.

This paper reports findings of an original and innovative study, which identifies critical success factors of PPP concession period and synthesizes them into a decision-making matrix. Many of the previous studies have identified and ranked the critical factors but such a synthesis has not been reported.

This paper aims at collecting and reviewing the published literature on the Six Sigma in construction along with its critical success factors (CSFs).

The research is based on literature review. Based on the keyword and semantic search techniques, papers published on the topic of Six Sigma during 2000-2015 are retrieved. Frequency analysis is performed to find out significance of identified CSFs, and zoning is performed based on the product of frequency of appearance and parties affected by the CSFs.

A total of 69 CSFs are identified as published in the literature. Based on an inclusion criterion of minimum 15 appearances, 22 CSFs are shortlisted for further analysis. Of these CSFs, around 32 per cent fall into red zone (most critical), 50 per cent into yellow and 18 per cent into green zone (least critical).

This work is limited by partial identification of CSFs. Though based on an extensive search, the retrieved CSFs may not be all the published ones. However, more thorough search techniques can be applied to improve upon this work.

The findings can be used to facilitate the decision-making in the context of project success.

This work is an original attempt at gathering Six Sigma CSFs applicable to construction projects. It may be used for further research and development to help ensure project quality and success.

The purpose of this paper is to investigate the level of implementation of Six Sigma (SS) in the construction industry of Pakistan along with the current state of affairs and the challenges, and opportunities for a successful implementation.

The research is purely exploratory in nature. Based on published work, critical success factors are gathered, and a number of questionnaire surveys and interviews are conducted to refine and quantify their impact. A system dynamics framework to assess the SS influence on project success is developed and case study project are simulated.

The construction industry of Pakistan is still functioning in a traditional way; marred with low level of awareness and ad hoc approaches, the findings point to a huge improvement opportunity. Further, when under planning projects are exposed to SS, the chances of project success improve better than under execution projects.

The limited level of awareness possessed by the respondents constrains the possible outreach of this work in industrially developed contexts. However, this work may become an impetus for further research in managing quality in construction industry.

The findings can be used to improve the quality provision of construction projects.

This work may trigger an important debate over the research and implementation of SS in the construction industry of developing countries that may greatly benefit by improving the quality of their projects and rectify their diminishing reputation for project success.

The purpose of this paper is to explore the contending role of important external inflows on the economic growth of Pakistan economy. The main purpose behind focusing on Pakistan is that it is receiving significant inflows from different international sources such as International Monetary Fund, World Bank and Asian Development Bank.

The study adopted the autoregressive distributed lag cointegration approach for the purpose of exploring the long-run cointegrating relationship among the variables. As Pakistan Government had been implementing some major liberalization policies during 1990s, data from 1976 to 2018 is used to estimate the specified models to reflect the impact of the surge of foreign inflows occurring from that time. In addition, error correction model is estimated for examining the short-run relationships.

The findings revealed the significant role played by different inflows in accelerating the economic growth. According to results, in the long run, all inflows, for example, Foreign direct investment (FDI), debt, official developdment assistance and remittances, have influenced significantly and positively the economic growth. The two control variables such as inflation and employment level included in the model have also played their expected role in the growth process. In the short run, some of the variables such as remittances, FDI and inflation rate have lost their significance level while for debt, aid and employment level, the signs of their coefficients become reversed.

Based on the findings, the study suggests the policymakers of Pakistan economy to liberalize the economy and attract more inflows from the external sources to accelerate economic growth.

To the best of the authors’ knowledge, this is the first comprehensive empirical study on the role of foreign inflows in the process of economic growth in the context of Pakistan economy.

The purpose of this research was to investigate at the influence of technology acceptance model (TAM) characteristics including perceived ease of use, perceived compatibility, and perceived security on the perceived utility and actual use of mobile banking among Yemeni academics. It also investigated the function of perceived utility as a moderator in the link between TAM variables and mobile banking adoption. The sample size was 251 respondents who worked at universities in Yemen and were chosen using stratified random selection. According to the findings, perceived compatibility and perceived security had a substantial positive influence on perceived usefulness and real mobile banking use; however perceived simplicity of use had no effect on mobile banking usage. According to the results, perceived usefulness slightly mediated the association between perceived ease of use and security and mobile banking use, whereas it completely mediated the relationship between perceived compatibility and mobile banking usage. Overall, the research proved the significance of TAM elements in academics’ use of mobile banking in Yemen, offering a credible empirical framework for studying mobile banking usage in this setting.

The purpose of this research is to examine the effect of heuristic biases on investment decisions through multiple mediation mechanisms of risk tolerance and financial literacy in the Tanzanian stock market.

A sample of 316 individual investors in the Tanzanian stock market was obtained through questionnaires. The data were analyzed using structural equation modeling (SEM).

The findings show that financial literacy mediates insignificantly the effects of overconfidence, availability, anchoring and representativeness heuristics on investment decisions. Further, financial literacy does not influence the effect of risk tolerance and investment decisions. Risk tolerance is confirmed as a positive mediator of overconfidence, availability, anchoring and representativeness heuristics in investment decisions. Also, the study shows that overconfidence exerts a stronger influence on investment decisions, followed by availability, representativeness, risk tolerance, anchoring and financial literacy.

The study deals with real investors. Therefore, it uses fewer items to measure the constructs in order to avoid respondent bias. Further research could examine the effects of heuristic biases on investment decisions by adding or modifying the items of particular constructs and studying institutional investors.

The findings can help individual investors to analyze and evaluate their behavior toward stock selection. Securities institutions can use this research to understand investors' behavior, evaluate future market trends and provide advice to the investors.

Previous studies have examined the impact of heuristics on the investment decisions of individual investors. The unique empirical analysis developed in this paper is that it examines the multiple mediation mechanisms of risk tolerance and financial literacy with respect to heuristic biases and investment decisions in the Tanzanian stock market.

Cost estimation is a major concern while planning projects on public–private partnership (PPP) terms in developing countries. To bridge the gap of the right approximation of cost of capital, this study aims to sermon a significant role of investor’s risk perception as unsystematic risk in PPP-based energy projects.

To investigate the effective mechanism of determining cost of capital and valuing the capital budgeting, a pure-play method has been acquired to measure systematic risk. In addition, dynamic conditional correlation (DCC) and generalized autoregressive conditional heteroscedasticity (GARCH) models have been applied to calculate weighted average cost of capital.

Initially, a joint cost of capital of energy-related projects has been calculated using DCC-GARCH and pure-play method. Investors risk perception has been discussed through market point of view using country risk premium modeling. Latter yearly betas have been calculated using DCC signifying the final outcomes that applying a dynamic model can provide a better cost estimation in emerging economies.

The findings are implicating that due to the involvement of international investors, domestic risk is linked with country risk. In such situations, market-related information is a key factor to find out the market performance, helping in the estimation of cost of capital through capital asset pricing model (CAPM). High dynamic nature of emerging economies causes an impediment in the estimation of cost of capital. Consequently, to calculate risk in dynamic markets, this study has acquired DCC model that can predict the value of beta factor.

Study contributes to the body of knowledge by addressing an important issue of investor’s risk perception and effective implication of CAPM using pure-play and DCC-GARCH when data is not promptly available in dynamic situations.