Partial Least-squares Technique Research Articles

Raman laser intensity and sample clarification on biochemical monitoring over Zika-VLP upstream stages

In the current biopharmaceutical scenario, constant bioprocess monitoring is crucial for the quality and integrity of final products. Thus, process analytical techniques, such as those based on Raman spectroscopy, have been used as multiparameter tracking methods in pharma bioprocesses, which can be combined with chemometric tools, like Partial Least Squares (PLS) and Artificial Neural Networks (ANN). In some cases, applying spectra pre-processing techniques before modeling can improve the accuracy of chemometric model fittings to observed values. One of the biological applications of these techniques could have as a target the virus-like particles (VLP), a vaccine production platform for viral diseases. A disease that has drawn attention in recent years is Zika, with large-scale production sometimes challenging without an appropriate monitoring approach. This work aimed to define global models for Zika VLP upstream production monitoring with Raman considering different laser intensities (200 mW and 495 mW), sample clarification (with or without cells), spectra pre-processing approaches, and PLS and ANN modeling techniques. Six experiments were performed in a benchtop bioreactor to collect the Raman spectral and biochemical datasets for modeling calibration. The best models generated presented a mean absolute error and mean relative error respectively of 3.46 × 105 cell/mL and 35 % for viable cell density (Xv); 4.1 % and 5 % for cell viability (CV); 0.245 g/L and 3 % for glucose (Glc); 0.006 g/L and 18 % for lactate (Lac); 0.115 g/L and 26 % for glutamine (Gln); 0.132 g/L and 18 % for glutamate (Glu); 0.0029 g/L and 3 % for ammonium (NH4+); and 0.0103 g/L and 2 % for potassium (K+). Sample without conditioning (with cells) improved the models' adequacy, except for Glutamine. ANN better predicted CV, Gln, Glu, and K+, while Xv, Glc, Lac, and NH4+ presented no statistical difference between the chemometric tools. For most of the assessed experimental parameters, there was no statistical need for spectra pre-filtering, for which the models based on the raw spectra were selected as the best ones. Laser intensity impacts quality model predictions in some parameters, Xv, Gln, and K+ had a better performance with 200 mW of intensity (for PLS, ANN, and ANN, respectively), for CV the 495 mW laser intensity was better (for PLS), and for the other biochemical variables, the use of 200 or 495 mW did not impact model fitting adequacy.

Real-time chlorophyll-a forecasting using machine learning framework with dimension reduction and hyperspectral data

Since water is an essential resource in various fields, it requires constant monitoring. Chlorophyll-a concentration is a crucial indicator of water quality and can be used to monitor water quality. In this study, we developed methods to forecast chlorophyll-a concentrations in real-time using hyperspectral data on IoT platform and various machine learning algorithms. Compared to regular cameras that record information only in the three broad color bands of red, green, and blue, the hyperspectral images of drinking water sources record the data in dozens or even hundreds of distinct small wavelength bands, providing each pixel in an image with a full spectrum. Different machine learning algorithms have been developed using hyperspectral data and field observations of water quality and weather conditions. Previous studies have predicted chlorophyll concentrations using either partial least squares (PLS), which is a dimensionality reduction method, or machine learning. In contrast, our study employed the PLS technique as a preprocessing step to diminish the dimensionality of the hyperspectral data, followed by the application of the machine learning techniques with optimized hyperparameters to improve the precision of the predictions, thereby introducing a real-time mechanism for chlorophyll-a prediction. Consequently, a machine learning algorithm with R2 values of 0.9 or above and sufficiently small RMSE was developed for real-time chlorophyll-a forecasting. Real-time chlorophyll-a forecasting using LightGBM has the best performance, with a mean R2 of 0.963 and a mean RMSE of 2.679. This paper is expected to have applications in algal bloom early detection on monitoring systems.

How Entrepreneurial Competence and Leadership Style Affect Business Performance

This research is based on the importance of entrepreneurial skills and leadership style in influencing business performance, especially for women entrepreneurs. In the age of globalization and increasingly intense competition, women entrepreneurs must possess sufficient skills and apply efficient leadership styles in order to achieve the best business outcomes. The purpose of this study is to determine the extent to which entrepreneurial skills and leadership styles impact the business performance of women entrepreneurs. This study involved women entrepreneurs in Bekasi district with 100 respondents randomly selected as the research sample. Information was collected using a questionnaire and analyzed using the Smart PLS (Partial Least Squares) technique to test the research model and hypotheses. The analysis found that entrepreneurial ability and leadership style have a major impact on firm performance. The entrepreneurial capability has been shown to make a significant contribution to improving operational efficiency and the ability to innovate, while a flexible and inspiring leadership style is able to improve team motivation and performance. It was found that it is important for women entrepreneurs to develop appropriate competencies and leadership styles to support their business success.

The significance of green purchase behaviour: mediating and moderating role of waste management and eco-regulation

This study examines the significance of green purchase behaviour in small and medium-sized enterprises (SMEs) and explores the mediating and moderating roles of waste management and eco-regulation in this context. The theoretical frameworks of resource-based view was utilized to conceptualize the relationships and dynamics between green purchase behaviour, waste management, eco-regulations, and sustainable performance in SMEs. Insights from these theoretical perspectives help in understanding how internal resources, capabilities, external pressures, and institutional factors interact to drive sustainability practices and business outcomes. Using a cross-sectional design, a questionnaire survey was administered to 225 SME owners. Using the Structural Equation Modelling (SEM) technique of Partial Least Squares (PLS), this study empirically analyses the relationships between green purchase behaviour, waste management practices, eco-regulations, and sustainable performance in SMEs. The results confirmed that green purchase behaviour (GPB) positively impacts waste management (WM). Furthermore, WM positively impacts financial performance (FP), social performance (SP) and environmental performance (EP). The results validate the mediating role of WM. The moderating results revealed that eco-regulation (ER) does play a moderating role in proposed relationships. As SMEs worldwide grapple with the imperative to adopt sustainable business practices, this study provides valuable insights and a roadmap for SMEs seeking to navigate the complex landscape of environmental responsibility and social accountability. The findings provide practical guidance for SMEs striving to strike a balance between economic success and environmental stewardship, fostering a holistic approach to sustainability of SMEs.

IDENTIFYING THE INTER-RELATIONSHIPS BETWEEN THE COMPANY'S STRATEGIC SECTORS

To reveal the inter-relationships between the strategic axes of the analyzed company, we used the Balanced Scorecard Analysis (BSC)1 and the Partial Least Squares (PLS) technique. The PLS technique identifies strategic areas (or axes) by grouping performance indicators that have the highest percentage of explaining the variance within the indicator group. We linked the strategic axes with the company's performance sectors, while the PLS model illustrated the interaction between the company's strategic lines as well as the interaction between the company's performance indicators and their respective groups. We started with principal component analysis (PCA) to identify the most important activity sectors for the company (for example, axis 1 = Profitability), to which we associated between 4 and 9 relevant performance indicators and selected those that were most correlated with their respective strategic sectors. We used the PLS technique for principal component analysis to show the correlations between the company's strategic sectors. The intensity of the relationships within the company allowed us to predict potential strategic lines for improving managerial performance. The BSC enabled us to explain the relationship between corporate governance variables and company performance. Within the causal relationships, we provided a logical explanation of how the analyzed business sectors are interconnected.

Moderating effect of subsidy policy on intention to purchase residential rooftop solar panel systems

PurposeThe adoption of residential rooftop solar panel systems (SPS) in India is at a nascent stage. Therefore, this study aimed to examine the factors affecting consumers’ intention to purchase SPS by expanding the theory of planned behavior (TPB) with three environmental psychology factors. The study was targeted at potential users’ intention to purchase SPS, thus it further explored the moderating role of perceived government subsidy policy (PGSP) in determining consumers’ purchase intention of SPS.Design/methodology/approachUsing G*power software, the minimum sample size of 189 was calculated; accordingly, 292 valid responses were gathered from potential users of SPS from three Indian states, namely Rajasthan, Punjab and Haryana, via an online questionnaire survey with the help of purposive sampling method. Structural equation modeling technique of partial least squares was employed to analyze the data.FindingsResults demonstrated that attitude, subjective norms, perceived behavioral control, perceived consumer effectiveness (PCE) and PGSP significantly influence purchase intention of SPS. Green trust and green self-identity did not influence the purchase intention of SPS. Further, PGSP strengthens the effect of attitude, green trust, PCE on purchase intention of SPS while it weakens the effect of subjective norms on purchase intention of SPS.Originality/valueThis study contributes to the existing literature by integrating green trust, green self-identity, PCE and PGSP into the TPB model to better understand factors affecting consumers’ purchase intention towards SPS in India.

An Adaptive Partial Least-Squares Regression Approach for Classifying Chicken Egg Fertility by Hyperspectral Imaging.

Partial least-squares (PLS) regression is a well known chemometric method used for predictive modelling, especially in the presence of many variables. Although PLS was not initially developed as a technique for classification tasks, scientists have reportedly used this approach successfully for discrimination purposes. Whereas some non-supervised learning approaches, including, but not limited to, PCA and k-means clustering, do well in identifying/understanding grouping and clustering patterns in multidimensional data, they are limited when the end target is discrimination, making PLS a preferable alternative. Hyperspectral imaging data on a total of 672 fertilized chicken eggs, consisting of 336 white eggs and 336 brown eggs, were used in this study. Hyperspectral images in the NIR region of the 900-1700 nm wavelength range were captured prior to incubation on day 0 and on days 1-4 after incubation. Eggs were candled on incubation day 5 and broken out on day 10 to confirm fertility. While a total number of 312 and 314 eggs were found to be fertile in the brown and white egg batches, respectively, the total number of non-fertile eggs in the same set of batches was 23 and 21, respectively. Spectral information was extracted from a segmented region of interest (ROI) of each hyperspectral image and spectral transmission characteristics were obtained by averaging the spectral information. A moving-thresholding technique was implemented for discrimination based on PLS regression results on the calibration set. With true positive rates (TPRs) of up to 100% obtained at selected threshold values of between 0.50 and 0.85 and on different days of incubation, the results indicate that the proposed PLS technique can accurately discriminate between fertile and non-fertile eggs. The adaptive PLS approach was, thereby, presented as suitable for handling hyperspectral imaging-based chicken egg fertility data.

Evaluation of the Determining Factors of the Intention to Use, Satisfaction and Recommendation of Mobile Wallets Adapted to the Utaut2 Model in the Peruvian Context

The massive adoption of mobile wallets in the context of COVID-19 forced retailers to implement it in their businesses. Therefore, it is necessary to assess the determinants of mobile wallet adoption and recommendations among merchants in northern Peru. Objective: To conduct an empirical evaluation to test the research hypotheses gathered during the literature review process. Based on the UTAUT2 model, the partial least-squares technique was used to test the hypotheses. Method: This study relied on a quantitative approach with a nonexperimental design, and a sample of 466 merchants was selected through nonprobabilistic sampling. Results: Eight of the nine hypotheses were confirmed: Perceived utility (?=0.219???), attitude (?=0.57?), perceived risk (?=?0.219???), and satisfaction (?=0.515???) are the main factors influencing the adoption and recommendations of mobile wallets with standardized beta coefficients of considerable magnitude (?***). Conclusion: This study confirms the importance of perceived usefulness, attitude, perceived risk, and satisfaction in driving the adoption and recommendation of mobile wallets among merchants in northern Peru. This information may be useful for merchants wishing to implement mobile wallet services and to increase their customer base. The results of this empirical assessment highlight the need for merchants to focus on improving the perceived usefulness and satisfaction of their mobile wallet services as well as minimizing the perceived risks associated with their use.
 
 Received: 11 September 2023 / Accepted: 23 December 2023 / Published: 5 January 2024

Analyzing the Mechanisms by Which Digital Platforms Influence Family-School Partnerships among Parents of Young Children

This research delved into the correlation between digital platforms and the dynamics of family-school collaboration within the context of parents with young children in Taiwan. It also examined the roles of parental involvement, teacher-child interactions, and online communication in this model. In the context of Taiwan, a research endeavor was undertaken to elucidate the viewpoints of parents with preschool-age children concerning digital platforms and their associated determinants. A Chinese-translated questionnaire included five latent factors: digital platforms, parental involvement, teacher-child interactions, online communication, and family-school partnerships. Employing a partial least-squares technique, we conducted an in-depth examination of the survey data, focusing on the evaluation of questionnaire latent factor reliability and validity within the measurement model. Subsequently, a path analysis was conducted to examine the hypothesized assumptions in the structural model. The findings indicated significant positive effects, with digital platforms enhancing parental involvement, teacher-child interactions, and online communication, ultimately leading to stronger family-school partnerships. Statistical analyses using a robust dataset consistently confirmed the significance of these associations.

Antecedents Effect of Green Business Strategy on Business Performance in Creative SME (Fashion) in Bantul Regency

This study aims to assess the performance of creative SME (fashion) firms geared toward the environment. This study focuses on creative SME (fashion) that are implementing green business strategies. To test the hypothesis, the researcher use SEM (Structural Equation Modeling) based on the PLS (Partial Least Squares) technique. The researchers gathered information by delivering questionnaires to 94 creative SME (fashion) in Bantul Regency. Researchers delivered questionnaires to creative SME (fashion) spread throughout many sub-districts and hubs of natural batik artisans as well as organic leather craftsmen in Bantul Regency. The results of this research show that the green business strategy can positively and significantly mediate the association between environmental orientation and business performance. Despite the fact that the results of assessing the association between environmental orientation and business performance of creative SME (fashion) in Bantul Regency are unfavorable and insignificant. Nonetheless, creative SME (fashion) in Bantul Regency must remain optimistic about developing their environmentally friendly because SME can employ inventions and knowledge to enhance and create products, environmentally friendly processes to meet potential markets, and environmentally friendly customer needs. They will be advantageous in a more environmentally friendly industrial period in the future

Effects of Social Connection on Dual Attitudes and Continuance Intentions of Using Social Media

Prior studies that specifically investigate the effects of social connections on the continuous adoption of social media applications (SMAs) are scarce. Based on the social contagion theory (SCT) and dual-attitude perspective, this study develops and validates a research model that explains the staged influences of social connection factors (i.e., pre- and post-usage cohesion and structural equivalence) on users’ explicit attitude, intention to use, implicit attitudes and continuance intention regarding the use of the SMAs. Survey data collected from both pre-usage and post-usage stages of 302 SMA users were examined using the technique of partial least squares to validate the research model. The results indicate that pre-usage cohesion and structural equivalence are significant antecedents of SMA users’ explicit attitude and intention to use. Additionally, these factors, along with post-usage cohesion and structural equivalence, significantly influence SMA users’ implicit attitude and continuance intention. In summary, by adopting the SCT and dual-attitude perspective, this study is among the first group of studies that examine whether social connection factors have influences on people’s adoption of SMAs at both pre-usage and post-usage stages. Implications for theory and for practices are discussed subsequently.

Online Impulsive Buying Behavior Using Partial Least Squares Algorithm

Impulsive purchasing is one of many fascinating subjects to investigate in e-commerce research. Online buying facilitates purchases and provides impulsive buyers with a venue to meet their demands. Impulse buying occurs when a client feels a sudden, overpowering need to make a purchase, which is a common practice among online shoppers. Therefore, the study’s purpose is to apply the partial least square (PLS) algorithm to investigate the factors driving online impulsive buying behavior (OIBB). Besides, in this research, the stimulus organism response (SOR) model was used as the research’s guiding theory; with the stimulus such as visual appeal and price attributes, the organism comprising perceived enjoyment and perceived usefulness, and response as OIBB. In addition, a non-probability sampling method was employed to collect data from 313 customers who shared their online impulsive purchase experiences through a Google Forms online survey. The collected data was analyzed using the PLS technique to assess the reliability, convergent validity, and discriminant validity of the variables, as well as test the proposed hypotheses. The findings reveal that visual appeal and price attributes were positive connections to perceived enjoyment and perceived usefulness. Likewise, perceived enjoyment and perceived usefulness also impacted positively OIBB. Additionally, the findings disclosed that visual appeal and price attributes also were associated positively with OIBB.

Entrepreneurship education and entrepreneurship intention: perceived desirability and perceived feasibility mediation

The impact of entrepreneurial education on entrepreneurial interests, entrepreneurial education on entrepreneurial interests through the mediation of perceived desirability, and entrepreneurial education on entrepreneurial interests through the mediation of perceived feasibility are all examined in this study. Students in their final year at Khairun University's Faculty of Economics and Business made up the samples. The survey approach was used to gather the data. SEM (Structural Equation Modeling) employing the PLS (Partial Least Square) technique and the SmartPLS tool version 3.0 was the data analysis model used in this investigation. The findings indicate that entrepreneurship education influences entrepreneurial intentions through the mediation of perceived desirability, entrepreneurship education affects perceived desirability, entrepreneurship education influences perceived feasibility, perceived desirability of entrepreneurial intentions, perceived feasibility of entrepreneurial intentions, and education entrepreneurship influences. Future research suggestions are also given.

The financial performance of private hospitals in Saudi Arabia: An investigation into the role of internal control and financial accountability.

The aim of this study was to examine the relationship between internal control, financial accountability, and financial performance in the private healthcare sector in the Kingdom of Saudi Arabia (KSA) through a questionnaire survey of 78 private hospitals. Drawing on agency theory, the study utilized structural equation modelling with partial least-squares technique to test multiple hypotheses. Results indicate a significant positive relationship between internal control and financial performance, with financial accountability acting as a mediator. Additionally, financial accountability was found to have a direct positive effect on financial performance. These findings provide new evidence for improving financial performance in private hospitals in the KSA through the implementation of internal control and financial accountability measures. Further research could examine additional factors that may impact financial performance in the healthcare sector.

Reconstruction of Meteorological Records by Methods Based on Dimension Reduction of the Predictor Dataset

The reconstruction or prediction of meteorological records through the Analog Ensemble (AnEn) method is very efficient when the number of predictor time series is small. Thus, in order to take advantage of the richness and diversity of information contained in a large number of predictors, it is necessary to reduce their dimensions. This study presents methods to accomplish such reduction, allowing the use of a high number of predictor variables. In particular, the techniques of Principal Component Analysis (PCA) and Partial Least Squares (PLS) are used to reduce the dimension of the predictor dataset without loss of essential information. The combination of the AnEn and PLS techniques results in a very efficient hybrid method (PLSAnEn) for reconstructing or forecasting unstable meteorological variables, such as wind speed. This hybrid method is computationally demanding but its performance can be improved via parallelization or the introduction of variants in which all possible analogs are previously clustered. The multivariate linear regression methods used on the new variables resulting from the PCA or PLS techniques also proved to be efficient, especially for the prediction of meteorological variables without local oscillations, such as the pressure.

Pengaruh Kepercayaan Merek, Country of Origin, dan Desain Produk pada Minat Beli Mobil

This study aims to determine the effect of brand trust, country of origin and product design on purschase intention in Mitsubishi Xpander. Respondents in this study were people who had never bought a Mitsubishi Xpander, but already knew about the product. The population in this study is not clearly known. The sampling technique used is the Hair et al technique where the indicator is multiplied by 5 to 10. The number of samples in this study was 119 samples. The data analysis method used is PLS (Partial Least Square) technique through the SmartPLS statistical software, with the research instrument being a questionnaire. The results showed that Brand Trust, Country Of Origin, and Product Design had a positive and significant effect on Purchase Intention in Mitsubishi Xpander.

Rapid Determination of the Total Petroleum Hydrocarbon Content of Soils by Handheld Fourier Transform Near-Infrared Spectroscopy.

For successful soil remediation and hydrocarbon exploration operations, determining the total petroleum hydrocarbon (TPH) content of soils is an indispensable process step. This paper reports on the performance of a handheld Fourier transform near-infrared (FT-NIR) spectrometer for rapid and quantitative determination of TPH content of soils from two different sites by diffuse reflection measurements. For rapid decisions for exploration work or environmental site assessment projects, a quick─preferably on-site─determination of TPH content is valuable. Diffuse reflection NIR spectra were recorded from soil samples of two different sites with TPH reference values ranging from 350 to 30,000 ppm, as determined by capillary gas chromatography and flame ionization detection with hydrocarbon fingerprinting C1-C44. However, this paper not only addresses the development of site-specific partial-least squares (PLS) calibrations but also demonstrates the locally-weighted PLS (LW-PLS) technique, which can be used to develop global, site-independent PLS calibrations without significant penalty in calibration performance. As a first step, the diffuse reflection spectra were used to develop conservative, site-specific PLS calibration models with root-mean-square calibration/cross-validation errors (RMSEC/RMSECV) of 1043/1106 and 741/785 ppm TPH, respectively, and the average absolute prediction errors for samples not contained in the calibration set were 451 and 293 ppm for the two sites, respectively. In a further step, significant degradation of the RMSE values of a conservative PLS model based on the NIR spectra of both sites was then compared to the application of the LW-PLS method, with only a slight loss of the prediction accuracy relative to the site-independent models. This study confirms the ability of next-generation portable FT-NIR spectrometers to predict low TPH levels in various soil types through both─soil-specific and site-independent─calibrations, giving these spectrometers the potential to become rapid screening tools in the field.

Effect of Brand Digitalization of E-Mas Transactions: E-Mas Features On The Mobile BSI Maqashid Syariah Framework

This study aims to examine how gold transactions implementation through the e-mas feature on BSI mobile at Bank Syariah Indonesia and find out whether gold transactions through the e-mas feature are in accordance with the concept of sharia maqashid. This research uses qualitative analysis methods that explain gold transactions implementation through the e-mas feature on BSI mobile at Bank Syariah Indonesia and the suitability of gold transactions contained in the e-Mas feature with the concept of sharia maqashid (Dharuriyyah, Hajiyat and Tahsiniyat). The division of dharuriyyah is categorized into 5 basics, such as 1) Protecting religion, 2) Protecting souls, 3) Protecting offspring, 4) Protecting reason and 5) Protecting property. Data collection techniques are literature studies, documentation studies, discussions and intuitive subjective. The results show digital innovation "e-mas BSI Mobile" is in under the concept of sharia maqashid and can help the public to conduct gold transactions at Bank Syariah Indonesia (BSI) and support halal needs based on sharia maqashid.

Analysis of the Factors That Influence Financial Reports in Government of North Sumatera with Implementation of the Government’s Internal Control System as Moderating Variable

This study aims to determine the effect of implementation of government accounting standards (SAP), use of information technology, the role of internal audit, finance administration, and conflict of interest on the quality of local government financial reports in the Government of North Sumatera. In addition, this study also examines whether the implementation of the government’s internal control system (SPIP) can be used as a moderating variable in this research model or not. The type of research conducted is causal-associative research. The location of this research was the OPD in the Government of North Sumatera. The method of data collection in this study was documentation and observation techniques using a questionnaire. The data analysis technique used in this research is the PLS (partial least squares) technique using the analysis tool SmartPLS version 3.0 software, which is run on computer media. The results obtained in this study indicate that the implementation of SAP, the role of internal audit, finance administration, and conflicts of interest have a positive and significant impact on the quality of the local government's financial reports in the Government of North Sumatera. Meanwhile, the use of information technology has had no significant effect on the quality of local government financial reports in the Government of North Sumatera. Meanwhile, other results in this study indicate that the implementation of SPIP is only able to moderate the role of internal audit and finance administration of local government financial reports in the Government of North Sumatera. Keywords: quality, report, financial, spip

The Effect of Brand Awareness, Brand Image and Trust On Consumer Buying Interest

This study is to analyze the effect of brand awareness , brand image and trust on consumer repurchase intention of PT Astra International Isuzu Warung Buncit Branch. The object of this research is Isuzu truck customers who have bought at least 2 times. Determination of sample size using the formula Hair et al., so that the sample used is 150 people. The research method used is quantitative research and the data analysis method used is PLS ( Partial Least Square) technique through SmartPLS 3.2.9 software, using survey method, with research instrument is a questionnaire. This study proves that brand awareness has a negative effect with a value of -0.147 and is not significant on consumer repurchase interest with a T-statistic value of 1.283. Brand image has a positive and significant effect on consumer repurchase interest and trust has a positive and significant effect on consumer repurchase interest..