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Occupant behavior can lead to considerable uncertainties in thermal comfort and air quality within buildings. To tackle this challenge, the use of probabilistic controls to simulate occupant behavior has emerged as a potential solution. This study seeks to analyze the performance of free-running households by examining adaptive thermal comfort and CO2 concentration, both crucial variables in indoor air quality. The investigation of indoor environment dynamics caused by the occupants' behavior, especially after the COVID-19 pandemic, became increasingly important. Specifically, it investigates 13 distinct window and shading control strategies in courtyard houses to identify the factors that prompt occupants to interact with shading and windows and determine which control approach effectively minimizes the performance gap.

This paper compares commonly used deterministic and probabilistic control functions and their effects on occupant comfort and indoor air quality in four zones surrounding a courtyard. The zones are differentiated by windows facing the courtyard. The study utilizes the energy management system (EMS) functionality of EnergyPlus within an algorithmic interface called Ladybug Tools. By modifying geometrical dimensions, orientation, window-to-wall ratio (WWR) and window operable fraction, a total of 465 cases are analyzed to identify effective control scenarios. According to the literature, these factors were selected because of their potential significant impact on occupants’ thermal comfort and indoor air quality, in addition to the natural ventilation flow rate. Additionally, the Random Forest algorithm is employed to estimate the individual impact of each control scenario on indoor thermal comfort and air quality metrics, including operative temperature and CO2 concentration.

The findings of the study confirmed that both deterministic and probabilistic window control algorithms were effective in reducing thermal discomfort hours, with reductions of 56.7 and 41.1%, respectively. Deterministic shading controls resulted in a reduction of 18.5%. Implementing the window control strategies led to a significant decrease of 87.8% in indoor CO2 concentration. The sensitivity analysis revealed that outdoor temperature exhibited the strongest positive correlation with indoor operative temperature while showing a negative correlation with indoor CO2 concentration. Furthermore, zone orientation and length were identified as the most influential design variables in achieving the desired performance outcomes.

It’s important to acknowledge the limitations of this study. Firstly, the potential impact of air circulation through the central zone was not considered. Secondly, the investigated control scenarios may have different impacts on air-conditioned buildings, especially when considering energy consumption. Thirdly, the study heavily relied on simulation tools and algorithms, which may limit its real-world applicability. The accuracy of the simulations depends on the quality of the input data and the assumptions made in the models. Fourthly, the case study is hypothetical in nature to be able to compare different control scenarios and their implications. Lastly, the comparative analysis was limited to a specific climate, which may restrict the generalizability of the findings in different climates.

Occupant behavior represents a significant source of uncertainty, particularly during the early stages of design. This study aims to offer a comparative analysis of various deterministic and probabilistic control scenarios that are based on occupant behavior. The study evaluates the effectiveness and validity of these proposed control scenarios, providing valuable insights for design decision-making.

This study aims to examine the relationship between entrepreneurial leadership (EL) and new product development performance (NPDP) at the firm level (level 2) of analysis and employee’s creativity (EC) at the cross level (level 1) of analysis. It also examines the serial mediations of (1) intrinsic motivation (IM)-EC and (2) creative self-efficacy (CSE)-EC on the relationship between EL and NPDP.

A systematic random sampling technique was used to collect data through self-administered surveys from leaders and employees of small and medium-sized enterprises (SMEs) in Pakistan’s IT sector. Analysis was conducted on net responses from 114 leaders and 476 employees.

The results revealed significant positive associations between EL and NPDP at the firm level of analysis and EC at the cross level of analysis. The results of the cross-level serial mediations show that (1) IM and EC, and (2) CSE and EC serially mediate the relationship between EL and NPDP.

This study is among the few to use the Coleman bathtub model to show top-down and bottom-up relationships. The study extends and complements the multilevel perspective on leadership and new product development research by simultaneously examining the relationships between EL and NPDP at the individual and firm levels.

To gain and differentiate competitive advantage, the sustainable service quality is a determining factor that railway companies can use. The purpose of this study is to identify both the importance and performance of rail transportation service quality factors in a case study as well as determine the most influential quality features.

A comprehensive approach namely importance–performance analysis (IPA) technique and decision-making trail and evaluation laboratory (DEMATEL), and interpretive structural modeling (ISM) and Matriced’ Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) techniques was utilized.

The relative position of each attribute is specified on the IPA matrix proposing four strategies of concentrate here, keep up the good work, low priority and possible overkill. This study reveals that attributes of “the company cares about having a good society” are the most influential factor, and “having good business relations with shareholders” is the most permeable factor. Actually, consumers pay attention to how companies act toward society and maintain communication with shareholders. Through ISM technique and by summing the row and column of the consistency matrix, the attributes were partitioned into four levels. Also, MICMAC analysis identified the four clusters of linkage, independent, autonomous and dependent status of the attributes in terms of the driving power and dependence power.

Due to the nature of single case study methodology, caution should be taken into consideration regarding the generazability of the obtained results.

The hybrid DEMATEL-ISM technique is used to analyze service quality factors in Iran’s transportation industry, which can be utilized in other industries as well as other countries.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.