Use Of Partial Least Squares Research Articles

Predicting Molecular Weight Characteristics of Reductively Depolymerized Lignins by ATR-FTIR and Chemometrics.

Recent scientific advances in the valorization of lignin, through e.g., (partial-)catalytic depolymerization, require equally state-of-the-art approaches for the analysis of the obtained depolymerized lignins (DLs) or lignin bio-oils. The use of chemometrics in combination with infrared (IR) spectroscopy is one avenue to provide rapid access to pertinent lignin parameters, such as molecular weight (MW) characteristics, which typically require analysis via time-consuming size-exclusion methods, or diffusion-ordered NMR spectroscopy. Importantly, MW serves as a marker for the degree of depolymerization (or recondensation) that the lignin has undergone, and thus probing this parameter is essential for the optimization of depolymerization conditions to achieve DLs with desired properties. Here, we show that our ATR-IR-based chemometrics approach used previously for technical lignin analysis can be extended to analyze these more processed, lignin-derived samples as well. Remarkably, also at this lower end of the MW scale, the use of partial least-squares (PLS) regression models well-predicted the MW parameters for a sample set of 57 depolymerized lignins, with relative errors of 9.9-11.2%. Furthermore, principal component analysis (PCA) showed good correspondence with features in the regression vectors for each of the biomass classes (hardwood, herbaceous/grass, and softwood) obtained from PLS-discriminant analysis (PLS-DA). Overall, we show that the IR spectra of DLs are still amenable to chemometric analysis and specifically to rapid, predictive characterization of their MW, circumventing the time-consuming, tedious, and not generally accessible methods typically employed.

THE INFLUENCE OF TRANSFORMATIONAL LEADERSHIP AND WORK ENVIRONMENT ON EMPLOYEE PERFORMANCE MEDIATED BY WORK STRESS STUDY ON EMPLOYEES OF BANK BRI KC MALANG KAWI

In the contemporary landscape of globalization, the heightened competitiveness within the banking industry emerges as a pivotal determinant influencing a firm's attainment of its objectives. To thrive in this fiercely competitive environment, human resources emerge as a paramount factor with the potential to drive all facets of organizational operations. Hence, it becomes imperative for the banking sector to nurture a workforce that demonstrates outstanding performance in the execution of company activities. The primary objective of this research is to examine the impact of transformational leadership and the work environment on employee performance, mediated by the variable of work stress. The study population encompasses all employees of Bank KC Malang Kawi, totaling 116 individuals. The research sample consists of the entire population, encompassing all employees at Bank BRI KC Malang Kawi. Data collection methods employed in this study encompass questionnaires and documentation. The data analysis method involves the use of Partial Least Squares (PLS). The findings of this research demonstrate that both transformational leadership and the work environment exert an influence on employee performance. Additionally, work stress is identified as a partial mediator between transformational leadership and the work environment in relation to employee performance.

Detection and quantification of antiviral drug tenofovir using silver nanoparticles and surface enhanced Raman spectroscopy (SERS) with spatially resolved hotspot selection

This study introduces a convenient and ultra-sensitive method of detection and quantification of the antiviral drug, tenofovir (TFV), by surface-enhanced Raman spectroscopy (SERS). Novel spatially resolved instrumentation for spectral acquisition and subsequent statistical analysis for hot spot selection was developed for convenient quantification of TFV in an aqueous matrix. Methods of statistical analysis include the use of partial least squares (PLS) regression vector analysis and spectral ranking by quality indices computed using CHAOS theory. Hydroxylamine-reduced Ag colloidal nanoparticles evaporated to dryness on an aluminum well-plate were used as the SERS substrate. To our knowledge, quantification of TFV down to 25 ng/mL by SERS, comprising clinically relevant concentrations, has not been previously reported. Furthermore, in this work we propose a novel method of quantification of aqueous TFV standards by SERS using statistical treatment of data by PLS and CHAOS theory. Based on these data, we propose future studies to develop a method of TFV detection and quantification in biological samples, beneficial to clinicians for rapid assessment of drug adherence during the treatment and prevention of viral diseases.

The Effect of Work Life Balance and Employee Engagement on Employee Performance of PT Duta Jaya Teknik Surabaya

When PT Duta Jaya Teknik Surabaya is unable to meet performance goals, work-life balance and employee engagement play a part in influencing employee performance and the amount of work completed by employees in carrying out their duties or obligations in accordance with applicable standards for each company. The purpose of this study is to ascertain how employee engagement and work-life balance affect employee performance at PT Duta Jaya Teknik Surabaya. Utilizing a quantitative methodology, this investigation. While the analysis method makes use of PLS (Partial Least Square) software and a structural equation modeling (SEM) approach. The 67 responders to a questionnaire who were all working for PT Duta Jaya Teknik Surabaya provided the information used. The findings of this study show that employee engagement and work-life balance both positively affect employees’ performance at PT. Duta Jaya Teknik Surabaya.

Pengaruh Gaya Hidup, Citra Merek, dan Kualitas Produk terhadap Minat Beli Smartphone Iphone


 Competition in the industrial world that is increasingly developing makes companies vying to optimally increase their resources. As well as social changes in Indonesian society towards perusahaan berjuang untuk meningkatkan kualitas sumber daya mereka sementara dunia teknologi dan informasi maju dengan sangat cepat. Bisnis dapat menggunakan segmentasi pasar sebagai salah satu teknik pemasarannya. Dengan penelitian ini, it analyzes related to iPhone smartphone products, which are well-known brands throughout the world so that they are familiar to consumers' minds, but the market share of these brands has decreased. This research was conducted to examine evaluated the external and internal models with Smart PLS 4.0 software to determine the impact of lifestyle, brand image, and product quality on iPhone purchase intentions through the use of Partial Least Square (PLS) Structural Equation Modeling (SEM). The method used to collect data is known as proportional stratified random sampling. Respondents were 90 samples of economics and business faculties who know iPhone products. These results indicate that lifestyle, brand image, and product quality can influence the intention to buy an iPhone smartphone
 Keywords: Lifestyle, BrandImage, QualityProduct, PurchaseIntention

Use of Partial Least Squares to define the Characteristics in the Environment of Higher Education Institutions and their Effects on Entrepreneurial Academic Education, a case study: Torreon, Mexico

Because university incubators have a favorable effect on student’s entrepreneurial intents, Higher Education Institutions (HEIs) are essential to the delivery of entrepreneurship education. By analyzing the perceptions of students who received master diploma in management-business fields in Torreon, Mexico in 2021, the aim of the research is to identify the internal and external aspects of the HEI environment and their impact on entrepreneurial education using Partial Least Squares methodology with the help of the SmartPLS software, 156 responses from the statistical tool provided 120 responses. Three of the original hypotheses were confirmed, while four variables—two associated with HEI ecosystem external factors and two with entrepreneurial education elements—had to be removed since they were not accepted. The findings will lead to a better comprehension of the elements influencing master students' entrepreneurial perspective to create stronger relationship with elements of the HEI ecosystem.

Model of Key Factors in the Sustainable Growth of Small and Medium-Sized Enterprises Belonging to the First Nations

The search for better living conditions, hand in hand with economic development, is a desire shared by all peoples; the First Nations are no exception. In this sense, entrepreneurship is one of the ways to improve incomes and quality of life, both in industrialized and developing societies, which is considered a potential strategy for economic development. This exploratory research presents a model that explains, through causal relationships, the growth of Small and Medium-sized Enterprises (SMEs) belonging to the First Nations, based on the results coming from the analysis conducted within one of the most important First Nations in the Americas, the Mapuche people, located in South America (mainly Argentina and Chile). The framework was developed from interviews with entrepreneurs and owners of Mapuche SMEs, along with an exhaustive analysis carried out through the use of Partial Least Squares (PLS). The owners were consulted about their attitude towards variables that generate accelerated growth in entrepreneurship in different contexts around the world. Subsequently, a model of inter-relationships was generated that sought to explain which variables are determining factors in the growth of SMEs belonging to the First Nations. Through a process of evaluation and depuration, the model proposed here was arrived at, concluding that Constant Training and Commitment to Growth are the most relevant factors in the growth of these companies. Both of these factors are supported by Long-Term Customer Relationships, Differentiation by Quality, Business Skills, and Business Structure, with a special focus on sustainable development.

Ecological and Socio-Economic Factors on the Rate of Participation and Sustainable Forest Management

This research was conducted to examine the effect of ecological, social and economic factors on the rate of partcipation of local communities on sustainable forest management. This research also want to examine the effect of ecological, social and economi factors on the forest sustainability and exploring the mediating role of rate of partcipation of local communities to increase the sustainability level of forest management. In this study, social forestry is examined from a comprehensive viewpoint that includes economic, societal, and ecological factors in order to illustrate the factors that influence local community participation in sustainable forest management in Riau, Indonesia. The use of Partial Least Square- Structural Equation Modeling (PLS-SEM) with SmartPLS software has revealed that both ecological and socio-economic factors determine the level of local community participation in sustainable forest management. The results have the potential to serve as a point of reference in the advancement of environmental science and environmental sociology, along with providing theoretical understanding about customary forests and local communities. Additionally, the practical implications of the findings can guide the sustainable development of forest resources. Ultimately, these findings are expected to yield optimal solutions for local communities in their efforts to manage customary forests sustainably.

Rejoinder: fractures in the edifice of PLS

PurposeThis study aims to provide a response to the commentary by Yuan on the paper “Marketing or Methodology” in this issue of EJM.Design/methodology/approachConceptual argument and statistical discussion.FindingsThe authors find that some of Yuan’s arguments are incorrect, or unclear. Further, rather than contradicting the authors’ conclusions, the material provided by Yuan in his commentary actually provides additional reasons to avoid partial least squares (PLS) in marketing research. As such, Yuan’s commentary is best understood as additional evidence speaking against the use of PLS in real-world research.Research limitations/implicationsThis rejoinder, coupled with Yuan’s comment, continues to support the strong implication that researchers should avoid using PLS in marketing and related research.Practical implicationsMarketing researchers should avoid using PLS in their work.Originality/valueThis rejoinder supports the earlier conclusions of “Marketing or Methodology,” with additional argumentation and evidence.

The determinants of internal audit quality

PurposeThis study aims to understand the behavior of internal auditors towards quality and analyze if some organizational and individual factors influence internal audit quality.Design/methodology/approachThe sample is constituted by Portuguese internal auditors, and the methodology includes the use of partial least squares – structuring equation model (PLS-SEM) to test the hypothesis under study.FindingsThe results show that there is a negative relationship between reduced audit quality practices (RAQP) and organizational commitment and independence. The results found that time pressure positively affect RAQP. There is no evidence that perceived organizational support (POS) and risk profile are determinants of RAQP.Originality/valueThis work contributes by extending the literature about the determinants of internal audit quality, but also to the practice by understanding the factors that influence the behavior of internal auditors and by making recommendations that allow an improvement of the quality of internal auditing.

The effects of analytical and holistic reasoning perspective on innovation and business performance, a study of state own, FDI and private company in Vietnam

This study examines the effects of analytical and holistic reasoning perspective on innovation and business performance in state owned, FDI, and private companies in Vietnam. The study was conducted on 382 companies. Data are analyzed through the use of partial least squares (PLS). The study results indicate that analytical and holistic reasoning perspective was a significant determinant of innovation and business performance. Furthermore, the analytical and holistic reasoning perspectivge impacted business performance both directly and indirectly. Thus, this study confirms the significance of an integrated approach to understanding the impacts of both direct and indirect effects of analytic and holistic reasoning perspectives on innovation and business performance in Vietnam. In addition, this study will contribute to the literature and in practice. It will help the policy maker to make good innovation and get high performance in the future. The limitations of the study will also be discussed.

Marketing or methodology? Exposing the fallacies of PLS with simple demonstrations

PurposeOver the past 20 years, partial least squares (PLS) has become a popular method in marketing research. At the same time, several methodological studies have demonstrated problems with the technique but have had little impact on its use in marketing research practice. This study aims to present some of these criticisms in a reader-friendly way for non-methodologists.Design/methodology/approachKey critiques of PLS are summarized and demonstrated using existing data sets in easily replicated ways. Recommendations are made for assessing whether PLS is a useful method for a given research problem.FindingsPLS is fundamentally just a way of constructing scale scores for regression. PLS provides no clear benefits for marketing researchers and has disadvantages that are features of the original design and cannot be solved within the PLS framework itself. Unweighted sums of item scores provide a more robust way of creating scale scores.Research limitations/implicationsThe findings strongly suggest that researchers abandon the use of PLS in typical marketing studies.Practical implicationsThis paper provides concrete examples and techniques to practicing marketing and social science researchers regarding how to incorporate composites into their work, and how to make decisions regarding such.Originality/valueThis work presents a novel perspective on PLS critiques by showing how researchers can use their own data to assess whether PLS (or another composite method) can provide any advantage over simple sum scores. A composite equivalence index is introduced for this purpose.

Developing a Virtual Flowability Sensor for Monitoring a Pharmaceutical Dry Granulation Line

Current technologies to measure granule flowability involve at-line methods that can take hours to perform. This is problematic for a continuous dry granulation tableting line, where the quality assurance and control of the final tablet products depend on real-time monitoring and control of powder flowability. Hence, a real-time alternative is needed for measuring the flowability of the granular products coming out of the roller compactor, which is the unit operation immediately preceding the tablet press. Since particle analyzers have the potential to take inline measurements of the size and shape of granules, they can potentially serve as real-time flowability sensors, given that the size and shape measurements can be used to reliably predict flowability measurements.This paper reports on the use of Partial Least Squares (PLS) regression to utilize distributions of size and shape measurements in predicting the output of three different types of flowability measurements: rotary drum flow, orifice flow, and tapped density analysis. The prediction performance of PLS had a coefficient of determination ranging from 0.80 to 0.97, which is the best reported performance in the literature. This is attributed to the ability of PLS to handle high collinearity in the datasets and the inclusion of multiple shape characteristics—eccentricity, form factor, and elliptical form factor—into the model. The latter calls for a change in industry perspective, which normally dismisses the importance of shape in favor of size; and the former suggests the use of PLS as a better way to reduce the dimensionality of distribution datasets, instead of the widely used practice of pre-selecting distribution percentiles.

Perilaku Keputusan Pembelian Generasi Y dan Z dalam Penggunaan E-Commerce di Masa Pasca Pandemi

In business during the post-covid-19 pandemic or the implementation of the new normal, many things can influence the behavior of purchasing decisions for a product, which is caused by factors such as: personal, social, cultural, and psychological. This transition period will leave new habits during the pandemic period. Every company must make changes in managing its business, if it wants to survive and win the competition. This study aims to analyze the comparison of changes in the purchasing decision behavior factors of generation Y and Z consumers with the use of e-commerce in the post-pandemic period. The analytical method used is the Structural Equation Modeling (SEM) technique through the use of Partial Least Squares (PLS-SEM). The results of the study stated that the comparison of results between respondents of generation Y and generation Z, there were three factors that had different results or contradictory results, namely perceptions of convenience, E-WOM, and price. Perception of convenience and E-WOM have a significant positive relationship to the purchase decision of generation Y, while price suitability does not affect the decision of generation Y in buying an item. Generation Z in making purchasing decisions really considers the price suitability factor. Meanwhile, E-WOM and perceived convenience are not considered by Generation Z. Positive emotion factors have a significant positive relationship for both Generation Y and Generation Z and perceived usefulness, security, motivation factors have a positive but not significant relationship with e-commerce purchasing decisions. in the post-pandemic

Detection and Quantification of Alprazolam Added to Long Drinks by Near Infrared Spectroscopy and Chemometrics.

In the present work, a fast, relatively cheap, and green analytical strategy to identify and quantify the fraudulent (or voluntary) addition of a drug (alprazolam, the API of Xanax®) to an alcoholic drink of large consumption, namely gin and tonic, was developed using coupling near-infrared spectroscopy (NIR) and chemometrics. The approach used was both qualitative and quantitative as models were built that would allow for highlighting the presence of alprazolam with high accuracy, and to quantify its concentration with, in many cases, an acceptable error. Classification models built using partial least squares discriminant analysis (PLS-DA) allowed for identifying whether a drink was spiked or not with the drug, with a prediction accuracy in the validation phase often higher than 90%. On the other hand, calibration models established through the use of partial least squares (PLS) regression allowed for quantifying the drug added with errors of the order of 2–5 mg/L.

Studying the Effect of Employees’ Environment Awareness as an Intermediate Variable for the Relationship between Institutional Pressures and Intentions of Human Resources for Adoption of Green Information Techniques: An Exploratory Study of Micro-Companie

Purpose: The aim of the present research paper is to study the impact of institutional pressures derived from institutional theory on the intentions of human resources in micro companies to adopt green information technology. Besides, it aims at explaining the reasons why human resources in companies and research sample, are heterogeneous in their adoption of green information technology, even though they are under institutional pressures. Theoretical Framework: The carbon footprint for micro-companies enlarges continuously for due to its an increasing use of information techniques in its all activities. Institutional pressures have increased on micro-companies pushing it toward letting human resources adopt green information techniques for mitigating negative impacts hit environment. Design/Methodology/Approach: The quantitative design was adopted to collect data from employees working in micro-companies’ in southern Iraq for a sample of 181 employees through the questionnaire. The study sample was requested to give an answer to its items in accordance with 7 point Likert scale. As per data statistical analysis, through the use of Partial Least Squares. Findings: that institutional pressures (forced, imitated & standard) collectively impact positively on intents of the study’s sample for adoption of a green information technique. Also, it was found that institutional pressures (forced, imitated & standard) impact positively employees’ environmental awareness. Then diagnosing the role of employees’ environmental awareness as a variable intermediating the relation between institutional pressures and intents for letting human resources adopt a green information technique. Research, Practical & Social implications: Future studies can understandable that green information technology is an open arena for all researchers interested in the environment. Researchers can enter this field by raising study questions and employing and applying its variables to micro companies, or public sector organizations. They can expand the organizational theory by adding other intermediate or interactive variables and their effects on human resources’ intentions to adopt green information technology. Originality/value: Human resources in micro companies play a significant role in shaping the company’s legitimacy in its institutional field. Because micro companies appreciate the commencement time to adopt green information technology, and the place of practice. This requires enriching their knowledge of the challenges facing the environment by developing mandatory and voluntary programs to increase human environmental awareness and to get them engaged and directing their behavior towards this objective.

Business-Civil Society Collaborations in South Korea: A Multi-Stage Pattern Matching Study

In this study, we use an empirical example to demonstrate how a multi-stage pattern matching process can inform and substantiate the construction of partial least squares (PLS) models and the subsequent interpretation of and theorizing from the findings. We document the research process underlying our empirical investigations of business – civil society collaborations in South Korea. The four-step process we outline in this paper can be used to ensure the meaningfulness of the structural model as well as to maximize the use of PLS for theorizing. This methodological advancement is particularly helpful in situations when literature reference points exist, but further contextual information may add nuances to prevalent knowledge. The findings from the qualitative flexible pattern matching part of the study prompted us to conduct a multi-group analysis. The resulting path changes in the base model led to the identification of four partnering strategies for business-CSO collaborations: (1) partnering for visibility; (2) partnering for compliance; (3) partnering for responsibility outsourcing; and (4) partnering for value co-creation.

Predicting Soil Properties and Interpreting Vis-NIR Models from across Continental United States.

The United States NRCS has a soil database that has data collected from across the country over the last several decades. This also includes soil spectral scans. This data is available, but it may not be used to its full potential. For this study, pedon, horizon and spectral data was extracted from the database for samples collected from 2011 to 2015. Only sites that had been fully described and horizons that had been analyzed for the full suite of desired properties were used. This resulted in over 14,000 samples that were used for modeling and eight soil properties: soil organic carbon (SOC); total nitrogen (TN); total sulfur (TS); clay; sand; exchangeable calcium (Caex); cation exchange capacity (CEC); and pH. Four chemometric methods were employed for soil property prediction: partial least squares (PLSR); Random Forest (RF); Cubist; and multivariable adaptive regression splines (MARS). The dataset was sufficiently large that only random subsetting was used to create calibration (70%) and validation (30%) sets. SOC, TN, and TS had the strongest prediction results, with an R2 value of over 0.9. Caex, CEC and pH were predicted moderately well. Clay and sand models had slightly lower performance. Of the four methods, Cubist produced the strongest models, while PLSR produced the weakest. This may be due to the complex relationships between soil properties and spectra that PLSR could not capture. The only drawback of Cubist is the difficult interpretability of variable importance. Future research should include the use of environmental variables to improve prediction results. Future work may also avoid the use of PLSR when dealing with large datasets that cover large areas and have high degrees of variability.

The Use of Partial Least Square for Analysis of the Relationship of Family Support on Learning Outcomes and Achievements Through Learning Motivation

Abstract: This study aims to analyze the relationship of family support to learning outcomes and learning achievement through learning motivation so that parents can increase their support for children in the effort to increase their learning motivation. This study uses a quantitative approach with partial least squares (SEM-PLS) analysis. The results showed that the score of the original sample of family support to learning motivation was 0.655, the score of learning motivation to learning outcomes was 0.605, and the score of learning motivation to learning achievement was 0.487. Thus, there is a positive relationship between family support and learning motivation, learning motivation and learning outcomes, and learning motivation and learning achievement. Therefore, to improve learning outcomes, learning achievement and learning motivation of children, parents must provide optimal support in the learning process to improve children's learning motivation.

Development of a Universal Calibration Model for Quantification of Adulteration in Thai Jasmine Rice Using Near-infrared Spectroscopy

In the event the substituent rice variety present in adulterated Thai jasmine rice cannot be identified, the adulterant rice in unknown samples could be inconsistent with that used to establish the calibration model resulting in inaccurate quantitative prediction of the adulteration level. In this research study, near-infrared (NIR) spectroscopy was applied to quantify the adulteration level of Thai jasmine or Khao Dawk Mali 105 (KDML105) rice based on the use of partial least squares (PLS) regression. To cope with the inconsistency between the training and test rice samples, a chemometric technique known as orthogonal projection (OP) was applied to extract variation of the target KDML105 rice, which then was exclusively used for establishing the prediction model. Furthermore, calibration transfer (CT) was used to adjust the NIR spectra of the adulterated samples to comply with the prediction of the calibrated model. The predictive abilities of the developed models were improved resulting in relatively lower root mean square error of prediction (RMSEP) values with higher determination of coefficient (Q2) values. In addition, the combined uses of the preprocessing methods provided a data treatment strategy that yielded a more stable model in the subsequent calibration step with the lowest standard deviation of RMSEP. This development was allowed for the quantitative prediction of the adulterations in the rice without the need for information pertaining to the blended rice.