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Over 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.

Key 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.

PLS 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.

The findings strongly suggest that researchers abandon the use of PLS in typical marketing studies.

This 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.

This 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.

This study aims to examine the role of an overall model fit assessment in the context of partial least squares path modeling (PLS-PM). In doing so, it will explain when it is important to assess the overall model fit and provides ways of assessing the fit of composite models. Moreover, it will resolve major concerns about model fit assessment that have been raised in the literature on PLS-PM.

This paper explains when and how to assess the fit of PLS path models. Furthermore, it discusses the concerns raised in the PLS-PM literature about the overall model fit assessment and provides concise guidelines on assessing the overall fit of composite models.

This study explains that the model fit assessment is as important for composite models as it is for common factor models. To assess the overall fit of composite models, researchers can use a statistical test and several fit indices known through structural equation modeling (SEM) with latent variables.

Researchers who use PLS-PM to assess composite models that aim to understand the mechanism of an underlying population and draw statistical inferences should take the concept of the overall model fit seriously.

To facilitate the overall fit assessment of composite models, this study presents a two-step procedure adopted from the literature on SEM with latent variables.

This paper clarifies that the necessity to assess model fit is not a question of which estimator will be used (PLS-PM, maximum likelihood, etc). but of the purpose of statistical modeling. Whereas, the model fit assessment is paramount in explanatory modeling, it is not imperative in predictive modeling.

This paper aims to investigate the interplay between managerial assumptions and institutional corporate social responsibility, and determines how such fit affects performance.

The authors developed and tested a model using survey methodology. The authors’ data from 210 hotels located in Qatar and the UAE were analysed using the partial least squares (PLS) approach.

The results reveal that firms with entrepreneurial, political and professional frame of reference (FoR) engage in institutional corporate social responsibility (CSR) practices. In addition, the entrepreneurial and professional FoR enhances the institutional CSR – organisational performance link.

The findings will help managers to determine the effect of their FoR on their adoption of institutional CSR, thereby increasing the effectiveness and efficiency of their CSR strategy. As the study is exploratory in nature, several limitations have been highlighted and discussed.

To the authors’ knowledge, this is one of the few papers that inspect the relationship between managerial assumptions and institutional CSR and establishes their effect on performance.

本论文旨在研究管理假设和企业社会责任的关系并且决定其如何影响企业绩效。

本论文采用问卷采样形式, 位于卡塔尔和阿联酋地区的210家酒店为问卷样本。本论文采用偏最小二乘回归（PLS）来分析数据。

如果企业拥有创业者精神、政治、及专业的参考架构（FoR）, 那么往往会参与到体制性企业社会责任（CSR）的实践。此外, 创业者精神的和专业的FoR促进体制性CSR-组织绩效的关系。

本论文结果帮助经理人判定FoR对于CSR实践的影响, 因而提高了CSR政策的效果和效率。由于本研究是探索性论文, 一些所带来的限制已经在文中提到并强调。

据作者所知, 本论文是仅有的几篇论文中, 研究管理假设和体制性CSR的关系并且确立其对于企业绩效的作用。

管理假设，参考架构，体制性CSR，新兴市场，企业绩效，偏最小二乘回归

研究论文

In the wake of lockdown regulations and limited mobility during the COVID-19 pandemic, dining habits shifted towards usage of food delivery apps to avoid physical interaction. Nonetheless, it is unknown whether the COVID-19 pandemic had an influence on the adoption of food delivery apps. Therefore, this study examined factors influencing the adoption of food delivery apps during the COVID-19 pandemic, as well as the moderating effects of education and age.

Data were collected from 282 food delivery application users in South Africa using a web-based survey. Partial least square structural equation modelling analysis was used to test the hypotheses, while partial least squares multigroup analysis was used to examine the moderating effect of education level and age.

The results indicated that perceived ease of use has a significant impact on perceived usefulness and attitudes, perceived usefulness has an impact on attitudes and continuous intention, attitude influences continuous intention and social pressure and convenience influence attitudes. The perceived COVID-19 threat had no impact on attitudes, and education and age had no significant impact on any relationships. The findings are imperative for restaurants and mobile application designers, as they enable more effective strategic management planning.

This study is the first paper to empirically employ technology acceptance model to analyse the adoption of food delivery applications during the COVID-19 pandemic. Its uniqueness is in examining situational influence associated with the pandemic such as social pressure, perceived COVID-19 threat and convenience.

The purpose of this paper is to identify the factors affecting user acceptance for NFC mobile wallets in both Korean and US markets.

The proposed model extends the UTAUT2 model with new constructs of credibility (CR) and service smartness (SS). This study was analyzed using partial least square structural equation modeling on data collected from 701 college students between the ages of 18 and 29.

The results of this study demonstrate that performance expectancy (PE), effort expectancy (EE), CR, SS and habit (HB) have strong positive relationships with a user’s behavioral intention to use NFC mobile wallets. Comparing the results of the USA and South Korea, there are different results regarding PE and CR.

This study shows that all factors except social influence (SI) have significant positive relationships with the intention to adopt NFC mobile wallets: Among the original UTUAT2 factors, PE, EE and HB are important determinants of NFC mobile wallet adoption and the new constructs, CR and SS, are significant determinants that influence BI. However, the target respondents are limited to college students of South Korea and the USA Thus, caution should be used when applying the results of this study towards less ICT developed countries and towards different age groups.

This study provides multiple practical contributions. First, this study emphasizes HB as the strongest factor for adopting NFC mobile wallets in both South Korea and the USA Second, this study also highlights the importance of SS. Third, this study reveals that SI is not associated with the adoption of NFC mobile wallets. Fourth, nationality differences between the USA and South Korea account for the differences in consumer behaviors.

This study has two main contributions: First, this study introduces a modified UTAUT2 model with two new variables (CR and SS) useful for NFC mobile wallets. Second, this study compares the results of partial least square structured equation models (PLS-SEM) of the two nationality groups, South Korea and the USA

Partial least squares structural equation modeling (PLS-SEM) has become an established social sciences multivariate analysis technique. Since quality management researchers also increasingly using PLS-SEM, this growing interest calls for guidance.

Based on established guidelines for applying PLS-SEM and evaluating the results, this research reviews 107 articles applying the method and published in eight leading quality management journals.

The use of PLS-SEM in quality management often only draws on limited information and analysis results. The discipline would benefit from the method's more comprehensive use by following established guidelines. Specifically, the use of predictive model assessment and more advanced PLS-SEM analyses harbors the potential to provide more detailed findings and conclusions when applying the method.

This research provides first insights into PLS-SEM's use in quality management. Future research should identify the key areas and the core quality management models that best support the method's capabilities and researchers' goals.

The results of this analysis guide researchers who use the PLS-SEM method for their quality management studies.

This is the first article to systematically review the use of PLS-SEM in the quality management discipline.

This paper aims to investigate the relationships amongst career patterns, neutrality of the state civil apparatus, and organizational performance of the local government in South Konawe District, Southeast Sulawesi Province in Indonesia.

Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate the relationships between variables through direct and indirect influence testing.

The findings reveal that career patterns influence neutrality and organizational performance. Neutrality of the state civil apparatus in politics mediates career patterns and local government organizational performance. The findings indicate that, first, promotions most significantly influence the organization’s neutrality and performance. Second, demotions have the least influence on the organization’s robustness and performance.

This paper is among the first to examine the relationships amongst career patterns, neutrality, and organizational performance. Recommendations are provided to improve neutrality and organizational performance, that is, the need to increase promotions and reduce demotions.

Structural equation modeling (SEM) has been widely used to examine complex research models in international business and marketing research. While the covariance-based SEM (CB-SEM) approach is dominant, the authors argue that the field’s dynamic nature and the sometimes early stage of theory development more often require a partial least squares SEM (PLS-SEM) approach. The purpose of this paper is to critically review the application of SEM techniques in the field.

The authors searched six journals with an international business (and marketing) focus (Management International Review, Journal of International Business Studies, Journal of International Management, International Marketing Review, Journal of World Business, International Business Review) from 1990 to 2013. The authors reviewed all articles that apply SEM, analyzed their research objectives and methodology choices, and assessed whether the PLS-SEM papers followed the best practices outlined in the past.

Of the articles, 379 utilized CB-SEM and 45 PLS-SEM. The reasons for using PLS-SEM referred largely to sampling and data measurement issues and did not sufficiently build on the procedure’s benefits that stem from its design for predictive and exploratory purposes. Thus, the procedure’s key benefits, which might be fruitful for the theorizing process, are not being fully exploited. Furthermore, authors need to better follow best practices to truly advance theory building.

The authors examined a subset of journals in the field and did not include general management journals that publish international business and marketing-related studies. Fur-thermore, the authors found only limited use of PLS-SEM in the journals the authors considered relevant to the study.

The study contributes to the literature by providing researchers seeking to adopt SEM as an analytical method with practical guidelines for making better choices concerning an appropriate SEM approach. Furthermore, based on a systematic review of current practices in the international business and marketing literature, the authors identify critical challenges in the selection and use of SEM procedures and offer concrete recommendations for better practice.

The purpose of this paper is to analyze marketability constructed from market share and concentration and to test its effect on the profitability and the mediation effects of profit‒loss sharing under stewardship theory.

This research employs data of financial statements published by ten sharia commercial banks listed in the Indonesia Financial Services Authority during the period 2011–2016. The data are analyzed into path analysis model using multiple mediators.

The result reveals that sharia banks’ marketability in Indonesia tends to be low. Based on the test of significance through Partial Least Square, it is found that marketability has a positive effect on the level of profitability, indicating that market share and concentration of sharia banks positively lead the change on the level of Return on Asset and Return on Equity. This paper further identifies the mediation effects emerged through mudharabah and musharakah. The results point out that mudharabah has a partial effect and musharakah has a competitive effect on the relationship between market share and profitability.

This paper can be a decision-maker for Central Bank and Financial Services Authority for encouraging sharia banks to enhance the power market through the mode of finances with profit‒loss sharing.

The growth of sharia banks is currently becoming highlight of the literature of sharia banks. This paper provides insights into stewardship theory that sharia banking management provides the concept of the alignment of interest.

Partial least squares (PLS) path modeling is a variance-based structural equation modeling (SEM) technique that is widely applied in business and social sciences. Its ability to model composites and factors makes it a formidable statistical tool for new technology research. Recent reviews, discussions, and developments have led to substantial changes in the understanding and use of PLS. The paper aims to discuss these issues.

This paper aggregates new insights and offers a fresh look at PLS path modeling. It presents new developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations.

PLS path modeling is the method of choice if a SEM contains both factors and composites. Novel tests of exact fit make a confirmatory use of PLS path modeling possible.

This paper provides updated guidelines of how to use PLS and how to report and interpret its results.