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Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.

Based on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).

The price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.

This paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

This research aims to identify and measure the correlations between building information modelling (BIM) and lean construction (LC) principles at the design and construction phases.

The study investigates BIM-LC principles correlations using the Istanbul Grant Airport (IGA) as a case study. The Delphi technique, performed quantitatively, contributes to the identification and quantification of a set of correlations between 11 selected BIM uses and 13 LC principles, which are supported with practical examples from the case study.

Together, the two research methods provide an evidence-based approach to understand the correlations between BIM and LC. The correlation analysis results in 46 correlations, and the correlations between the LC principles and BIM uses are intensified with the LC principles.

A quantitative understanding BIM use and LC principles correlations and appreciation of their specific uses can guide the practical implementation of BIM and LC, especially in large and mega projects.

BIM and LC practices represent approaches to improve performance in construction projects. While BIM has both information technology (IT) and process perspectives, the LC approach is mainly a process and product-oriented philosophy for project efficiency, effectiveness and the elimination of non-value-adding activities and waste. Many studies have investigated how the two approaches complement each other and concluded that their combined implementation in projects can improve efficiency and effectiveness. However, to date an analytical and granular investigation identifying and measuring correlations between BIM and LC based on empirical data is lacking. This paper fills that gap with an evidence-based analysis of the tightness of coupling and correlations between BIM uses and LC principles.

Recently, many scholars have been paying more attention to studying the existence and application of multifractality. However, most researches concentrate on studying multifractal features of returns or volume separately, and ignore the correlation between them. The purpose of this paper, therefore, is to give an empirical test on multifractal features of price‐volume correlation in China metal futures market and then to conduct a comparative analysis from time and space dimensions, in order to better understand metals futures market behavior.

This paper gives an empirical test by means of multifractal detrended cross‐correlation analysis (MF‐DCCA) approach, which is a technique employed in statistical physics to detect multifractal features of two cross‐correlated nonstationary time series.

Empirical results show that the price‐volume correlation in China metal futures market is multifractal and that long range correlation and non‐Gaussian probability distribution are the main reasons for the existence of multifractality. Also, a comparative analysis is conducted and it is found that although China metal futures market is becoming more and more effective, the effectiveness is lower than that in mature LME metal futures markets. The futures market still needs further development.

The paper's conclusions would help to understand the nonlinear dependency relationship and potential dynamics mechanism in price‐volume correlation.

The relationships between integrated reporting quality (IRQ) and corporate governance characteristics have been studied extensively, but the results are still inconclusive and, sometimes, contradictory. The purpose of this paper is to systematize the results of previously published studies on the relationship between corporate governance and IRQ.

This paper uses several complementary theoretical perspectives (agency, stakeholder and signaling theory). The relevant aspects of the corporate governance system are the attributes and composition of the board, the existence of a social responsibility committee, the quality of the audit committee, integrated report assurance and ownership structures. The sample consisted of 61 papers published in top journals between 2015 and 2021. Meta-analytic procedures were applied on bivariate and partial correlations between IRQ and the identified corporate governance characteristics.

The results confirm that director independence, the existence of a social responsibility committee, institutional ownership and the hiring of a Big 4 auditor are significantly correlated with IRQ. On the other hand, board gender diversity, audit committee independence and dedicated assurance have a positive but nonsignificant impact on IRQ. Chairperson-chief executive officer duality does not seem to impact report quality, while ownership concentration has a negative but nonsignificant impact on IRQ.

Future research can improve the measurement of focal indicators by using a common set of variables for comparability, favoring disaggregate measures of corporate governance and updating the measurement of some indicators. Future research could also propose new indicators in the area of corporate governance and expand the theoretical domain of IRQ research.

The findings emphasize the need to explicitly consider the role of corporate governance structures and arrangements in improving IRQ. Through meta-analysis, the paper aims to provide a comprehensive and generalizable set of findings, suggesting that corporate governance indicators cannot be overlooked as predictors of integrated reporting.

Analyses customer satisfaction with mail‐order speciality foods in the UK and examines the relationship between satisfaction with eight attributes of mail‐order speciality food and their association with overall satisfaction and likelihood of future purchase. Univariate analysis reveals that a high proportion of mail‐order customers experience satisfaction with each of the eight mail‐order attributes, reflected in a high proportion of customers who are satisfied overall and who intend to repurchase the products in the future. Canonical correlation analysis reveals a statistically significant relationship between one set of variables, overall satisfaction and likelihood of future purchase, and another set of variables, the eight mail‐order attributes. Consequently the results indicate that customer satisfaction is associated with service aspects of mail‐order such as the order process and delivery service as well as physical product attributes such as product quality.

The purpose of this paper is to predict the amount of energy consumption by using a suitable statistical method in some sectors and energy carriers, which has shown a significant correlation with greenhouse gas emissions.

After studying the correlation between energy consumption rates in different sectors of energy consumption and some energy carriers with greenhouse gas distribution (CO₂, SO₂, NO_X and SPM), the most effective factors on pollution emission will be first identified and then predicted for the next 20 years (2015 to 2004). Furthermore, to determine the appropriate method for forecasting, two approaches titled “trend analysis” and “double exponential smoothing” will be applied on data, collected from 1967 to 2014, and their capabilities in anticipating will be compared to each other contributing MSD, MAD, MAPE indices and also the actual and projected time series comparison. After predicting the energy consumption in the sectors and energy carriers, the growth rate of consumption in the next 20 years is also calculated.

Correlation study shows that four energy sectors (industry sector, agriculture, transportation and household-general-commercial) and two energy carriers (electricity and natural gas) have shown remarkable correlation with greenhouse gas emissions. To predict the energy consumption in mentioned sectors and carriers, it is proven that double exponential smoothing method is more capable in predicting. The study shows that among the demand sectors, the industry will account for the highest consumption rate. Electricity will experience the highest rate among the energy careers. In fact, producing this amount of electricity causes emissions of greenhouse gases.

Access to the data and categorized data was one of the main limitations.

By identifying the sectors and energy carriers that have the highest consumption growth rate in the next 20 years, it can be said that greenhouse gas emissions, which show remarkable correlation with these sectors and carriers, will also increase dramatically. So, their stricter control seems to be necessary. On the other hand, to control a particular greenhouse gas, it is possible to focus on the amount of energy consumed in the sectors and carriers that have a significant correlation with this pollutant. These results will lead to more targeted policies to reduce greenhouse gas emissions.

The tendency of communities toward industrialization along with population growth will doubtlessly lead to more consumption of fossil fuels. An immediate aftermath of burning fuels is greenhouse gas emission resulting in destructive effects on the environment and ecosystems. Identifying the factors affecting the pollutants resulted from consumption of fossil fuels is significant in controlling the emissions.

Such analyses help policymakers make more informed and targeted decisions to reduce greenhouse gas emissions and make safer and more appropriate policies and investment.

The purpose of this paper is to investigate the statistical correlation properties of the Shanghai Interbank Offered Rate (SHIBOR) interbank lending market.

The authors apply methods of correlation analysis, random matrix theory (RMT) and minimum spanning tree (MST) to investigate the correlation properties of Chinese interbank lending market and analyze how the SHIBOR panel banks behave in different market periods.

First, the largest eigenvalue λ ₁ is the index to describe the market mode of the whole market when all banks behavior collectively and λ ₁/N is a good estimator of the average correlation <C> of the correlation matrix. Second, notably, the authors find the “market mode” is weakened in two crises periods of 2008 stock market crash and 2009 Global Financial Crisis. This is significantly different from other market where the “market mode” is normally strengthened in crises periods. Third, the authors subtract the contribution of λ ₁, the second and third eigenvalue, λ ₂ and λ ₃, will fall outside of the predicted interval. And both λ ₂ and λ ₃ are getting times larger in the crises periods than in “Non-Crisis” period. Fourth, and in the MST analysis, the authors find again that the average distances of the MST are the times larger in crises periods than in “Non-Crisis” period and the second largest eigenvalue is a good estimator of the average distance of the MST.

According to the best knowledge, this paper is the first work on the study of the statistical properties of an interbank lending market using quotation level data of panel banks, which allows us to analyze the properties of the interest rate formation and how all panel banks behavior in different periods. This work is also the first study on the SHIBOR market using econophysics methods of correlation analysis, RMT and MST.

The purpose of this paper is to investigate the correlation between university libraries and academic research achievement and analyze if university library resources correlate with academic research achievement.

The paper seeks to verify the correlation between university libraries and academic research achievement and to examine which university library resources relate to research achievement. A variety of research questions were posed concerning the relationship between a university's library resources and academic research achievement. Structural equation models (SEMs) were developed to answer the research questions. Most research questions posed were affirmatively answered using the SEM process.

This study confirmed that labor and budget, investment in e‐resources and an investment in university libraries enhances academic research achievement.

An SEM for verifying the correlation between university libraries and academic research achievement was developed in the study.

This study is the first including an investment factor in e‐resources for verifying the correlation between university libraries and academic research achievement.

This paper aims to identify empirically the influence of learning mechanisms provided by organizations on knowledge sharing in the organizational environment.

A quantitative study was developed in which a sample of 268 individuals from civil and military organizations of the Federal Direct Administration was researched. The questionnaire used was composed of the Organizational Learning Mechanism Scale, which was adapted at the time of the present study, in addition to a scale on knowledge sharing, which was developed within the scope of this research. After performing the factorial analysis for both scales, a canonical correlation analysis was performed between the group of variables associated with the learning mechanisms (independent variables) and the group of variables on knowledge sharing (dependent variables).

The results found in the canonical correlation analysis indicate that the learning mechanisms are responsible for explaining 35 per cent of the variance (R² = 0.352) of the group of variables on knowledge sharing.

The findings of this research can help the researched organizations to increase the knowledge management actions, mainly in relation to the actions that favor social interaction among the individuals in the work environment, making possible the exchange of knowledge and experiences in the internal organizational context, and exploring in a positive way actions related to internal acquisition.

The deeper knowledge about the relationship between organizational actions promoted by top management and knowledge support decision-making in the organizational environment regarding contextual factors that influence social interaction between individuals. In relation to the sharing of knowledge, a high correlation of knowledge absorption and reproduction aspects with the knowledge sharing phenomenon was perceived, so that the possibility of organizations thinking in ways that provide the individual with formal and informal environments can be foreseen.

The main contributions of this research are to measure the intensity of the relationship between learning mechanisms and knowledge sharing; and to test the predictive effect of learning mechanisms on knowledge sharing. Regarding the methodological aspects, it was opportune to approach the phenomenon through a little used lens in the context of administration research: the analysis of canonical correlation, which represents another look at the influence of the actions of the top management and the interaction of individuals. The discussions and the data analysis carried out in this research allow us to envisage significant contributions of this work to the analysis and theoretical refinement of the study of the variables treated.