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At the beginning of the Corona Virus Disease 2019 (COVID-19) pandemic, a digitalized construction environments surfaced in the heating, ventilation and air conditioning (HVAC) systems in the form of a modern delivery system called demand controlled ventilation (DCV). Demand controlled ventilation has the potential to solve the building ventilation's biggest problem of managing indoor air quality (IAQ) for controlling COVID-19 transmission in indoor environments. However, the improper evaluation and information management of infection prevention on dense crowd activities such as measurement errors and volatile organic compound (VOC) generation failure rates, is fragmented so the aim of this research is to integrate this and explore potentials with machine learning algorithms (MLAs).

The method used is a thorough systematic literature review (SLR) approach. The results of this research consist of a detailed description of the DCV system and digitalized construction process of its IAQ elements.

The discussion revealed that DCV has a potential for being further integrated by perceiving it as a MLAs and hereby enabling the management of IAQ level from the perspective of health risk function mechanism (i.e. VOC and CO₂) for maintaining a comfortable thermal environment and save energy of public and private buildings (PPBs). The appropriate MLA can also be selected in different occupancy patterns for seasonal variations, ventilation behavior, building type and locations, as well as current indoor air pollution control strategies. Furthermore, the conceptual framework showed that MLA application such as algorithm design/Model Predictive Control (MPC) integration can alleviate the high spread limitation of COVID-19 in the indoor environment.

Finally, the research concludes that a large unexploited potential within integration and innovation is recognized in the DCV system and MLAs which can be improved to optimize level of IAQ from the perspective of health throughout the building sector DCV process systems. The requirements of CO₂ based DCV along with VOC concentrations monitoring practice should be taken into consideration through further research and experience with adaption and implementation from the ventilation control initial stage of the DCV process.

This paper seeks to examine the effect of monetary policy rate (MPR) on the lending rates of commercial banks in Ghana.

The paper employed the autoregressive distributed lag (ARDL) model as well as the non-linear autoregressive distributed lag (NARDL) model econometric techniques on a quarterly time series data from 2002 to 2018.

The ARDL results revealed that, MPR has a positive and significant effect on lending rate in the long and short run. Although there exists a direct relationship between MPR and lending rate, from the NARDL revealed an asymmetric effect of MPR on lending rate to the effect that, lending rate in Ghana responds more to positive shock (a rise in MPR) compared to a negative shock (a decrease in MPR) both in the long and short run.

The paper contributes to policy and literature in Ghana by providing empirical evidence on the asymmetric effect that MPR has on lending rates in Ghana. The paper recommends among others, the establishment of a rating system of banks according to their monetary policy compliance, where highly rated banks could have for instance a reduction on borrowed reserves from the central bank.

This study aims to introduce a novel technique for nonlinear sensor time constant estimation and sensor dynamic compensation in hot-bar soldering using an extended Kalman filter (EKF) to estimate the temperature of the thermocouple.

Temperature optimal control is combined with a closed-loop proportional integral differential (PID) control method based on an EKF. Different control methods for measuring the temperature of the thermode in terms of temperature control, error and antidisturbance are studied. A soldering process in a semi-industrial environment is performed. The proposed control method was applied to the soldering of flexible printed circuits and circuit boards. An infrared camera was used to measure the top-surface temperature.

The proposed method can not only estimate the soldering temperature but also eliminate the noise of the system. The performance of this methodology was exemplary, characterized by rapid convergence and negligible error margins. Compared with the conventional control, the temperature variability of the proposed control is significantly attenuated.

An EKF was designed to estimate the temperature of the thermocouple during hot-bar soldering. Using the EKF and PID controller, the nonlinear properties of the system could be effectively overcome and the effects of disturbances and system noise could be decreased. The proposed method significantly enhanced the temperature control performance of hot-bar soldering, effectively suppressing overshoot and shortening the adjustment time, thereby achieving precise temperature control of the controlled object.

This study intends to examine the relationships between external knowledge sourcing (EKS), organizational ambidexterity (OA), and manufacturing performance (MP) in the context of large manufacturing firms within a dynamic environment setting. The research framework and derived hypotheses are grounded in the knowledge-based view (KBV) and dynamic capability (DC) theories.

A self-administered online survey was used in this study to gather data. Respondents were the operation leaders representing large manufacturing firms. The collected data were screened for invalid responses, and hypotheses were tested using structural equation modeling.

The study reveals that OA and EKS play key roles in achieving a better MP. Likewise, OA also mediates the relationship between EKS and MP.

Cross-sectional data were collected from large manufacturing firms within five focus sectors in Malaysia. A similar study can be conducted with more sectors of different contexts to confirm the findings.

Knowledge is critical for the firm to react to environmental dynamism, and the ability to manage it ambidextrously will enable the firm to enhance its performance.

This study offers empirical insights from the perspective of the large manufacturing firms in Malaysia, which are undergoing an Industrial Revolution 4.0 (IR4.0) transformation. This study bridges the knowledge gap by revealing the value that EKS can facilitate MP, exploring OA as the prevalent factor and demonstrating how KBV and DC can be applied in this study.

Based on self-determination theory (SDT), this study aims to determine the motivation factors of reviewers writing long reviews in the anime industry.

This study analyzes 171,188 online review data collected from an online anime community (MyAnimeList.net).

The findings show that intensity of emotions, experience in writing reviews and helpful votes in past reviews are the most important factors and positively influence review length. The overall rating of the anime moderates the effects of some motivation factors. Moreover, reviewers commenting on their favorite or nonfavorite anime also have varied motivation factors. Furthermore, this study has addressed the p-value problem due to the large sample size.

This study provides a comprehensive and theoretical understanding of reviewers' motivation for writing long reviews.

Online communities can incorporate the insights from this study into website design and motivate reviewers to write long reviews.

Many past studies have investigated what reviews are more helpful. Review length is the most important factor of review helpfulness and positively affects it. However, few studies have examined the determinants of review length. This study attempts to address this issue.

High failure rates characterise the experience of new entrepreneurial ventures in Nigeria and other emerging economies. Reliance on strategic tools such as entrepreneurial orientation (EO) is critical to the growth and survival of new ventures. This empirical study aims to deepen the understanding of the relationship between EO and performance of new venture logistics firms in Nigeria. It further explores the contingent effects of social capital and marketing capabilities on the hypothesised direct relationships from a transport industry perspective.

Managers of 650 new venture logistics service providers in selected Nigerian cities were Web-surveyed. Exploratory and confirmatory factor analyses were performed. Regression analysis was further performed. Common method variance and other validity checks were assessed.

The 469 valid responses showed a positive relationship between EO and new venture performance (NVP). Social capital and marketing capabilities positively moderate the direct relationship between EO and NVP. Managerial implications suggest that context-specific dynamics must be considered when making strategic EO decisions to aid firm growth and survival.

This study directly responds to the contingency approach recommendation of past studies (Anwar et al., 2022; Van Stel et al., 2021; Covin and Wales, 2019) using the logistics service and emerging economy context. It also introduces social capital and marketing capabilities as moderators.

This study aims to investigate the impact of local windfall gains from the Spanish Christmas lottery on household consumption behavior.

The study applies differences-in-differences to assess permanent income hypothesis (PIH) validity, examining pre- and postlottery consumption effects. Additionally, it also uses an instrumental variable regression, using the lottery shock as an instrument for total expenditures, to estimate the Engel curves.

The paper finds a PIH violation; households in winning region notably increase consumption on durable and nondurable goods compared to nonwinning ones. Moreover, durable goods consumption is responsive to lottery winnings, while nondurable goods consumption are unit-elastic to expenditure shocks.

To the best of the author’s knowledge, this is the first paper analyzing the effects of winning regions of the Spanish Christmas lottery in all types of consumption goods, testing its consequences in the PIH and estimating its effects in the Engel curves.