Exploratory Analysis Method Research Articles

The turnover intention of internal controllers of Vietnamese commercial banks in the context of COVID-19

Internal control plays an important role in managing the risks of banking system activities. Controllers are always under pressure from control activities due to the bank’s diverse activities. The resignation of internal controllers is relatively common in commercial banks. It is also a matter of concern for the banking and finance industry, which coordinates economic resources for the country, especially when the internal control period occurs again with the pandemic. The study aims to explore the turnover intention of internal controllers in the context of COVID-19 in Vietnamese commercial banks. The study uses the convenience sampling method to collect data from 339 respondents who are working or worked as internal controllers in commercial banks. The study was surveyed in 2023. The study uses quantitative methods for exploratory factor analysis. Ordinary least squares process the data to test the hypotheses. Some factors affect the turnover intention of internal controllers, such as occupational awareness, employment conditions, office environment, and career opportunities, in the context of COVID-19. The result is a useful resource for researchers to comprehensively understand issues related to the turnover intention of internal controllers in the banking industry. The study supports managers of commercial banks in planning the strategic objectives of human resource stabilization for the stable growth of the banking system.

Model of dimensions and variables of corporate social responsibility updated through structural equations.

Corporate social responsibility (CSR) is a constantly evolving concept that reflects changes in society and the expectations of stakeholders in a process that leads companies to adapt to respond to new challenges and demands. Similarly, the theory and practice of CSR have moved from regulatory compliance to a more holistic approach that requires more sophisticated models that allow for a deeper understanding. Following the fact that companies now have access to a greater amount of information related to their social and environmental performance, as well as comparative data from other organizations, which is why it is necessary to have a management tool that allows collecting, process, and generating more accurate and meaningful metrics that more effectively reflect a company's impact on society. Consequently, the present work aims to identify a system of variables and dimensions representative of the management of organizations that allows the validation of a generic model of corporate social responsibility determined through factorial and structural modeling capable of reflecting more accurate and up-to-date dimensions and metrics of model variables and dimensions. To carry out the study, a sample of 667 middle and senior managers from medium and large companies in Guayas, Ecuador, were randomly contacted in their respective business contexts by trained interviewers. The data processing was carried out in stages. First, the exploratory factorial analysis method of the items was applied to form relevant factors. Then, the dimensions' structural modeling was formulated and ratified through the pertinent goodness-of-fit indices. The results determined a system of correlated factors whose items present estimators of commonality and high and significant factorial loads, excluding variables that did not exceed the sensitization criteria applied. Finally, a model made up of 15 factors and 66 variables ratified using the comparative adjustment indices, the chi-square likelihood ratio, and the mean square error of approximation is introduced, confirming the proposed corporate social responsibility model.

Rural Industrial Integration and New Urbanization in China: Coupling Coordination, Spatial–Temporal Differentiation, and Driving Factors

Understanding the coupling coordination status between rural industrial integration (RII) and new urbanization (NU) is critical for the Chinese government to optimize policies that promote the synergetic and sustainable development of RII and NU. Based on constructing evaluation index systems, this paper uses the entropy value method, coupling coordination degree model, exploratory spatial analysis method, gravity center model, and geographical detector model to reveal the characteristics of the spatial–temporal differentiation of the coupling coordination and its driving factors in China. The results show that: (1) The regional differences in the coupling coordination degree between RII and NU are obvious, and the coupling coordination degree of China’s three economic regions are all in an increasing trend, but the mean values in the central and western regions are always below the national average. (2) The coupling coordination degree has significant spatial agglomeration characteristics, but the regional differences are gradually decreasing. The whole country is still dominated by the low–low agglomeration, and the provinces with the high–high agglomeration are mainly located in the eastern region. (3) The gravity center of the coupling coordination degree has moved in both the east–west and north–south directions from 2011 to 2021, but the movement trend in the north–south direction is more obvious. (4) The economic development level, industrial structure, transportation conditions, government support capacity, financial support level, and agricultural mechanization level are important factors driving the spatial–temporal variation, and their interactions will enhance the differentiation. The results can provide a theoretical basis and decision-making reference for relevant government departments in China to promote the sustainable development of RII and NU.

Use of t‐distributed stochastic neighbour embedding in vibrational spectroscopy

AbstractThe t‐distributed stochastic neighbour embedding algorithm or t‐SNE is a non‐linear dimension reduction method used to visualise multivariate data. It enables a high‐dimensional dataset, such as a set of infrared spectra, to be represented on a single, typically two‐dimensional graph, revealing its global and local structure. t‐SNE is very popular in the machine learning community and has been applied in many fields, generally with the aim of visualising large datasets. In vibrational spectroscopy, t‐SNE is gaining notoriety but principal component analysis (PCA) remains by far the reference method for exploratory analysis and dimension reduction. However, t‐SNE may represent a real aid in the analysis of vibrational spectroscopic datasets. It provides an at‐a‐glance global view of the dataset allowing to distinguish the main factors influencing the spectral signal and the hierarchy between these factors, and gives an indication on the possibility of performing predictive modelling. It can also provide great support in the choice of the pre‐processing, by comparing rapidly different general pre‐processing approaches according to their effect on the variable of interest. Here we propose to illustrate these advantages using different datasets. We also propose an approach based on a synergy between the t‐SNE and PCA methods, allowing respective advantages of each to be exploited.

Research on Governance Mode of Digital Platform Ecosystem from the Perspective of Ecological Niche: Based on Double Case Analysis

In order to comply with the requirements of the times, in view of the problem that the strength of the main enterprises of the digital platform ecosystem is too different, which leads to too large differences in resources. From the perspective of the niche, firstly, this paper integrates the three governance modes of "hierarchical governance", "cross-level governance" and "panoramic comprehensive rational analysis framework", and puts forward the "panoramic joint governance mode from the perspective of niche". Secondly, the two cases of Haier COSMOPlat Ecology and Huawei Smart Car Ecosphere are selected, and the exploratory case analysis and comparative study methods are used to carry out corresponding analyses on the two cases to verify the feasibility of the new governance mode. The study found that the essence of this governance mode is to create more connection points by introducing a resource-sharing platform based on the new generation of information technology, breaking the fault-type hierarchical governance, focusing on solving problems at all levels, and attracting more regulatory bodies to conduct joint governance. Through these, we can expand the niche width of the digital platform ecosystem, then reduce the barriers to resource sharing among the subjects of the digital platform ecosystem. By applying this mode, different forms of digital platform ecosystems can achieve efficient operation.

Innovative non-targeted liquid chromatography fingerprinting approach for authenticating tigernuts under Protected Designation of Origin quality seal.

Tigernut is a typical foodstuff from a specific region of Valencia (Spain) called 'L'Horta Nord', where it is commercialized under a Protected Designation of Origin (PDO) as Chufa de Valencia ('Valencia's tigernut'). PDO-recognized tigernuts present unique characteristics associated with their particular production region. Increasing demand and the associated expansion of its cultivation area has made necessary an exhaustive quality control to check the geographical origin and quality seal. In this work, a new multivariate analytical method capable of authenticating the PDO quality seal of tigernut samples was developed. Tigernut fat fraction was extracted under optimal conditions, applying the methodology of design of experiments. The analytical method combined fingerprinting methodology and chemometric tools to observe the natural grouping of samples using the exploratory analysis method and to develop classification models (partial least squares-discriminatory analysis; PLS-DA) to discriminate between two sample categories: (i) PDO tigernuts; and (ii) NON-PDO tigernuts. The built PLS-DA model demonstrated 100% accuracy, high sensitivity and specificity, revealing that the tigernut fat fraction can be applied to authenticate the PDO quality seal. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Implementation of Marriage Policy and Catin's Attitudes Regarding Marriage Counseling on the Performance of Suscatin Mentors in Realizing Family Marriage Adjustments

This research aims to investigate the impact of marriage policies and the attitudes of prospective brides and grooms towards marriage counseling on the performance of pre-marital counselors in achieving marital adjustments within Garut Regency. Employing an exploratory analysis method, the study focused on the leaders of the Marriage Advice, Development, and Preservation Agency in Garut Regency, including the Chairperson and Vice-Chairpersons, totaling 86 individuals, utilizing a census sampling technique.
 Data collection encompassed questionnaires, interviews, observations, and documentary research. Statistical path analysis was the chosen technique to address the research hypotheses. The primary hypothesis testing revealed that the implementation of marriage policies and the attitudes of prospective brides and grooms influenced pre-marital counselor performance in achieving adjustments by 12.79%, with the remaining 87.21% attributed to other factors. Further sub-hypothesis testing demonstrated that marriage policies and prospective brides' and grooms' attitudes toward marriage counseling accounted for 25.43%, while other factors constituted 74.57%. Intriguingly, the implementation of marriage policies and attitudes toward marriage counseling did not significantly impact marital adjustments (path coefficient of 0.0364). Pre-marital counselor performance also had limited effects on marital adjustments (path coefficient of 0.1526). Moreover, there was a positive correlation between the implementation of marriage policies and the attitudes of prospective brides and grooms toward marriage counseling (partial correlation coefficient of 0.6783). The research identified key issues, such as suboptimal policy implementation, lack of awareness and motivation among prospective brides and grooms, ineffective interagency collaboration, and a shortage of skilled staff among pre-marital counselors. In light of these findings, it is recommended to improve policy implementation, enhance interagency cooperation, and increase awareness among prospective brides and grooms regarding the significance of pre-marital counseling for successful marriages. These measures are essential for addressing the prevalent marital issues and lack of warmth and affection in young couples' family lives in Garut Regency.

Step-by-Step Approach to Build Multiple Reaction Monitoring (MRM) Profiling Instrument Acquisition Methods for Class-based Lipid Exploratory Analysis by Mass Spectrometry.

Multiple reaction monitoring (MRM) profiling is a strategy for the exploratory analysis of small molecules and lipids by direct sample injection, ie, without the use of chromatographic separation. It is based on instrument methods that comprise a list of ion transitions (MRMs), in which the precursor ion is the expected ionized m/z of the lipid at its species level, ie, the description of lipid class and number of carbon and double bonds in the fatty acid chain(s), and the product ion is a fragment expected for the lipid class or for the fatty acid neutral loss. The Lipid Maps database is expanding constantly, and therefore the MRM-profiling methods associated with this database need to be continuously updated. Here, we provide a comprehensive overview and the key references for the MRM-profiling methodology and workflow, followed by a step-by-step approach to build MRM-profiling instrument acquisition methods for class-based lipid exploratory analysis based on the Lipid Maps database. The detailed workflow includes (1) importing the list of lipids from the database; (2) for a given class, combining isomeric lipids described at full structural level into 1 entry to obtain the neutral mass at species level; (3) attributing the standard Lipid Maps abbreviated nomenclature for the lipid at its species level; (4) predicting the ionized precursor ions; and (5) adding the expected product ion. We also describe how to simulate the precursor ion for the suspect screening of modified lipids using lipid oxidation and their expected product ions as an example. After determining the MRMs, information about collision energy, dwell time, and other instrument parameters are added to finalize the acquisition method. As an example of final method output, we describe the format for Agilent MassHunter v.B.06 and provide the parameters in which optimization can be performed by lipid class using one or more lipid standards.

Exploratory Analysis of the Gene Expression Matrix Based on Dual Conditional Dimensionality Reduction.

One of the major goals in gene expression data analysis is to explore and discover groups of genes and groups of biological conditions with meaningful relationships. While this problem can be addressed by algorithms, their results require an analysis within context, since they may be affected by many side processes -such as tissue differentiation- that could hinder the target goal. Visual analytics-based methods for exploratory analysis of the gene expression matrix (GEM) are essential in biomedical research since they allow us to frame the analysis within the user's knowledge domain. In this paper, we present a visual analytics approach to discover relevant connections between genes and samples based on linking a reordered GEM heatmap and dual 2D projections of its rows and columns, which can be recomputed conditioned by subsets of genes and/or samples selected by the user during the analysis. We demonstrate the capability of our approach to discover relevant knowledge in three case studies involving two cancer types plus normal tissue from the TCGA database.

Characteristics of Spatiotemporal Variations and Driving Factors of Land Use for Rural Tourism in Areas That Eliminated Poverty

This study explores the spatiotemporal characteristics and driving factors of land use for rural tourism in areas that eliminated poverty from 2009 to 2021. It puts forward targeted governance measures to promote the high-quality development of rural tourism, poverty alleviation, and rural revitalization. The analysis is based on exploratory spatial analysis methods and geographical detectors. The results show that (1) the overall level of land use for rural tourism was low but grew very quickly with large regional differences. (2) There was a significant spatial agglomeration in land use for rural tourism land. The spatial distribution of land use for rural tourism landscapes was characterized by two cores and four clusters, while spatial distribution of rural tourism facilities was characterized by one cluster with multiple branches. (3) The driving factors of spatial variations in land use for rural tourism were diverse and dynamic. Dominant factors shifted from natural conditions and geographical location to socioeconomic and tourism resources and regional policy dimensions. Policy should emphasize the development of the rural tourism industry, innovate the diversified “tourism + development” model, enhance the level of land use for rural tourism, broaden avenues for farmers to increase their income, and strengthen residents’ motivation for development.

Causal analysis of nitrogen oxides emissions process in coal-fired power plant with LiNGAM

Coal has been an important energy source worldwide; however, it is the largest source of nitrogen oxide (NOx) emissions because the amount of nitrogen in coal is larger than that of other fossil fuels. Precise control of NOx emissions is required in operations of coal-fired power plants from the viewpoint of air pollution control. Although theoretical analyses of NOx generation from a coal-fired power plant have been conducted, it is difficult to precisely predict NOx generation in an actual plant. NOx generation is affected by various factors, such as furnace design and operating conditions, and there are complicated relationships among them. Thus, it is necessary to identify important operating factors that affect NOx generation in actual coal-fired power plants. A linear non-Gaussian acyclic model (LiNGAM) is an exploratory causal analysis method that identifies a causal ordering of variables and their connection strengths without any prior knowledge of causal relationships among variables. In this study, we analyzed real operation data collected from a coal-fired power plant using LiNGAM to identify factors of NOx generation. The causal relationship between process variables and NOx generation was estimated by means of LiNGAM, and the connectional strengths of the variables on NOx generation were derived. The analysis results agreed with previous reports on NOx generation mechanisms, such as combustion air temperature, steam temperature on a specific side of the furnace, and air flow rate of forced draft fans. In addition, we found the steam flow rate and the furnace pressure as new candidate factors of NOx generation through causal analysis using LiNGAM, which heretofore has not been suggested. Our analysis result should contribute to reducing NOx emissions from coal-fired power plants in the future.

Nhân tố ảnh hưởng đến lòng trung thành của khách hàng mua sắm tại cửa hàng thời trang trực tuyến

Nowadays, the trend of online shopping is common in all industries, especially fashion products. Customer loyalty is always an element that every business wants to build and maintain. Especially in the fashion market where products are constantly being innovated, loyal customers make it easier for businesses to grow. The study was conducted to identify and measure the factors affecting customer loyalty to online fashion stores in the form of providing products directly from businesses to customers (D2C), thereby suggesting implications to improve customer loyalty. Using the method of exploratory factors analysis, and multivariate regression, from 205 valid questionnaires, the results show that there are 6 factors Ease of use, Personalization, Responsiveness, Product Quality, Product Improvement, and Website Design have an impact on Customer Satisfaction. Three factors in order including Satisfaction, Trust, and Switching costs have a direct impact on customer loyalty.

Analysis and Application of Calculations Fiscal Reconciliation on Less Corporate Income Pay at Sip Company

Every company in Indonesia currently has an annual financial report, which aims to find outthe performance of a company, besides that the company's financial statements are also used to report and make calculations in paying taxes, financial statements are prepared based on generally accepted principles, namely Accounting Standards Finance (SAK). The background of this study is the result of observations and experiences of researchers, that to determine the calculation of corporate income tax carried out by the SIP company and to compare the calculation of corporate income tax on financial statements made by companies with the Taxation Law. The research used exploratory descriptive analysis method. The research instrument used in this research is the documentation format SIP company financial statements results the conclusion of this study is the analysis of the company's financial statements, indicating that the calculation and reporting of income tax by the company is not in accordance with the tax law. Companies need to calculate the fiscal reconciliation is the most appropriate means used in determining the amount of income tax payable.

BS-SC Model: A Novel Method for Predicting Child Abuse Using Borderline-SMOTE Enabled Stacking Classifier

For a long time, legal entities have developed and used crime prediction methodologies. The techniques are frequently updated based on crime evaluations and responses from scientific communities. There is a need to develop type-based crime prediction methodologies that can be used to address issues at the subgroup level. Child maltreatment is not adequately addressed because children are voiceless. As a result, the possibility of developing a model for predicting child abuse was investigated in this study. Various exploratory analysis methods were used to examine the city of Chicago’s child abuse events. The data set was balanced using the Borderline-SMOTE technique, and then a stacking classifier was employed to ensemble multiple algorithms to predict various types of child abuse. The proposed approach successfully predicted crime types with 93% of accuracy, precision, recall, and F1-Score. The AUC value of the same was 0.989. However, when compared to the Extra Trees model (17.55), which is the second best, the proposed model’s execution time was significantly longer (476.63). We discovered that Machine Learning methods effectively evaluate the demographic and spatial-temporal characteristics of the crimes and predict the occurrences of various subtypes of child abuse. The results indicated that the proposed Borderline-SMOTE enabled Stacking Classifier model (BS-SC Model) would be effective in the real-time child abuse prediction and prevention process.

Targeted Lipidomics Analysis of Adipose and Skeletal Muscle Tissues by Multiple Reaction Monitoring Profiling.

Lipid homeostasis is critical for maintaining normal cellular functions including membrane structural integrity, cell metabolism, and signal transduction. Adipose tissue and skeletal muscle are two major tissues involved in lipid metabolism. Adipose tissue can store excessive lipids in the form of triacylglyceride(TG), which can be hydrolyzed to release free fatty acids (FFAs)under insufficient nutrition states. In the highly energy-demanding skeletal muscle, lipids serve as oxidative substrates for energy production but can cause muscle dysfunction when overloaded. Lipids undergo fascinating cycles of biogenesis and degradation depending on physiological demands, while dysregulation of lipid metabolism has been increasingly recognized as a hallmark of diseases such as obesity and insulin resistance. Thus, it is important to understand the diversity and dynamics of lipid composition in adipose tissue and skeletal muscle. Here, we describe the use of multiple reaction monitoring profiling, based on lipid class and fatty acyl chain specific fragmentation, to explore various classes of lipids in skeletal muscle and adipose tissues. We provide a detailed method for exploratory analysis of acylcarnitine (AC), ceramide (Cer), cholesteryl ester (CE), diacylglyceride (DG), FFA, phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), phosphatidylinositol (PI), phosphatidylserine (PS), sphingomyelin (SM), and TG. Characterization of lipid composition within adipose tissue and skeletal muscle under different physiological situations will provide biomarkers and therapeutic targets for obesity-related diseases.

AGAMA DAN SOLIDARITAS SOSIAL DI ERA INDUSTRI 4.0 DAN MASYARAKAT 5.0

This article aims to examine the phenomenon of religion and social solidarity in digital technology innovation on internet platforms where there are many oblique responses to religion which in the future are considered less attractive and the number of adherents and followers is certain to decrease, especially the millennial generation. Meanwhile, social solidarity that is formed in acts of mutual help and friendship is not directly related to religion, but because these traditions and culture have become the legacy of previous generations. Therefore, it is worth studying in depth in this paper by using a qualitative paradigm approach and exploratory descriptive analysis methods by reviewing related literature. The results found that the existence of Internet technology and other devices makes it easier for religions and their adherents to carry out worship practices by their religious orders, such as online hospitality and helping each other quickly respond through digital networks. Post-secularization religious awareness increased because alienation in the era of disruption made the spiritual void need to be filled with religious values.

Recall the Impact of the Covid – 19 Virus in Indonesia: Regional Perspective

The Covid-19 virus has brought about fundamental changes to economic activity both on a macro and micro scale. The COVID-19 virus is a global epidemic that affects global, national, and regional economic stability. This article is a type of opinion article, the purpose of this study is to describe and review the state of the Indonesian economy on a regional scale at the time of the Covid-19 outbreak in Indonesia. Research objects include; Malang City, Malang Regency, and Batu City, East Java Province. This type of research is exploratory and data analysis method using descriptive analysis. The sampling method was carried out using a simple random sampling method for groups of farmers, Micro, Small, and Medium Enterprises, informal workers, and the household sector. The types of data used are primary data and secondary data. The results of the study show that each area analyzed tends to have the same results in several indicators, some economic indicators tend to decline during a pandemic, ranging from regional income, and people's purchasing power to the average community rice consumption. The weakening of economic activity at the regional level in Indonesia, began to recover in the year after the "New Normal" regulation, the economy of each region began to improve and people's purchasing power slowly strengthened.

Subtask analysis of process data through a predictive model.

Response process data collected from human-computer interactive items contain detailed information about respondents' behavioural patterns and cognitive processes. Such data are valuable sources for analysing respondents' problem-solving strategies. However, the irregular data format and the complex structure make standard statistical tools difficult to apply. This article develops a computationally efficient method for exploratory analysis of such process data. The new approach segments a lengthy individual process into a sequence of short subprocesses to achieve complexity reduction, easy clustering and meaningful interpretation. Each subprocess is considered a subtask. The segmentation is based on sequential action predictability using a parsimonious predictive model combined with the Shannon entropy. Simulation studies are conducted to assess the performance of the new method. We use a case study of PIAAC 2012 to demonstrate how exploratory analysis for process data can be carried out with the new approach.

Accreditation Model Zakat Management Organization (ZMO) In Indonesia

The rapid and growing Zakat Management Organization or Organisasi Pengelola Zakat (OPZ) in Indonesia every year has increased in line with the high potential of zakat. However, the zakat collection is still low compared to the existing potential. One of the reasons is the lack of public knowledge about zakat, weak capacity, and the regulatory framework of zakat. Therefore, it is necessary to have an assessment to measure OPZ performance from the aspects of legality and institutions, management, finance, and empowerment. The purpose of this study is to provide an OPZ accreditation rating that has not been done before. This research uses qualitative, exploratory, and content analysis methods. The type of data used is primary data obtained through the interview method by sampling data sources, observation, questionnaires, and Focus Group Discussions (FGD), while secondary data is obtained through financial statements in OPZ 2019 and non-financial statements. The results showed that the overall performance of each OPZ was categorized as good. LAZ Al-Azhar received a score of 87.5 (Accreditation A), LAZ IZI with a value of 84.5 (Accreditation A), LAZ BMH with a value of 83.25 (Accreditation A), LAZ DDII with a value of 74.75 (Accreditation B), and LAZ BAMUIS BNI with a value of 69.5 (Accreditation B). The managerial implications of this research are that all zakat stakeholders can follow and adjust existing regulations and governance, as well as active guidelines and socialization from BAZNAS and the Ministry of Religion related to mechanisms and procedures to obtain the legality of LAZ licensing for unlicensed OPZ.

Retribusi Izin Mendirikan Bangunan dan Permasalahannya Studi pada Dinas Penanaman Modal dan Pelayanan Terpadu Satu Pintu Kota Medan

This study aims to determine the process of obtaining a Building Permit (IMB) and the administration of a Regional Levies Determination Letter (SKRD) which is often not paid by the applicant, resulting in a levy receivable at the Medan City Investment and One Stop Service Office. This study uses an exploratory qualitative analysis method. Qualitative data was obtained by means of interviews, observations and documentation studies and the validity and reliability of the data were determined by data triangulation, then the data obtained would be analyzed thematically and interpreted to draw conclusions. The results showed that the processing of the IMB issuance experienced a delay in the processing of files by the IMB technical team so that it had implications for the delay in the issuance of the IMB document. Another consequence that occurs is the loss of potential regional income from IMB retribution due to delays. Receivables due to levies occur because the applicant does not pay the IMB SKRD at the bank according to the stipulated time.
 
 Keywords: Building Permits, processing of regional levy determination letters, accounts receivable