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Open Access
Article
Publication date: 13 April 2022

Florian Schuberth, Manuel E. Rademaker and Jörg Henseler

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…

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Abstract

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Practical implications

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.

Originality/value

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.

Details

European Journal of Marketing, vol. 57 no. 6
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 2 September 2020

Florian Schuberth, Manuel Elias Rademaker and Jörg Henseler

The purpose of this study is threefold: (1) to propose partial least squares path modeling (PLS-PM) as a way to estimate models containing composites of composites and to compare…

Abstract

Purpose

The purpose of this study is threefold: (1) to propose partial least squares path modeling (PLS-PM) as a way to estimate models containing composites of composites and to compare the performance of the PLS-PM approaches in this context, (2) to provide and evaluate two testing procedures to assess the overall fit of such models and (3) to introduce user-friendly step-by-step guidelines.

Design/methodology/approach

A simulation is conducted to examine the PLS-PM approaches and the performance of the two proposed testing procedures.

Findings

The simulation results show that the two-stage approach, its combination with the repeated indicators approach and the extended repeated indicators approach perform similarly. However, only the former is Fisher consistent. Moreover, the simulation shows that guidelines neglecting model fit assessment miss an important opportunity to detect misspecified models. Finally, the results show that both testing procedures based on the two-stage approach allow for assessment of the model fit.

Practical implications

Analysts who estimate and assess models containing composites of composites should use the authors’ guidelines, since the majority of existing guidelines neglect model fit assessment and thus omit a crucial step of structural equation modeling.

Originality/value

This study contributes to the understanding of the discussed approaches. Moreover, it highlights the importance of overall model fit assessment and provides insights about testing the fit of models containing composites of composites. Based on these findings, step-by-step guidelines are introduced to estimate and assess models containing composites of composites.

Open Access
Article
Publication date: 17 August 2022

Jörg Henseler and Florian Schuberth

In their paper titled “A Miracle of Measurement or Accidental Constructivism? How PLS Subverts the Realist Search for Truth,” Cadogan and Lee (2022) cast serious doubt on PLS’s…

1980

Abstract

Purpose

In their paper titled “A Miracle of Measurement or Accidental Constructivism? How PLS Subverts the Realist Search for Truth,” Cadogan and Lee (2022) cast serious doubt on PLS’s suitability for scientific studies. The purpose of this commentary is to discuss the claims of Cadogan and Lee, correct some inaccuracies, and derive recommendations for researchers using structural equation models.

Design/methodology/approach

This paper uses scenario analysis to show which estimators are appropriate for reflective measurement models and composite models, and formulates the statistical model that underlies PLS Mode A. It also contrasts two different perspectives: PLS as an estimator for structural equation models vs. PLS-SEM as an overarching framework with a sui generis logic.

Findings

There are different variants of PLS, which include PLS, consistent PLS, PLSe1, PLSe2, proposed ordinal PLS and robust PLS, each of which serves a particular purpose. All of these are appropriate for scientific inquiry if applied properly. It is not PLS that subverts the realist search for truth, but some proponents of a framework called “PLS-SEM.” These proponents redefine the term “reflective measurement,” argue against the assessment of model fit and suggest that researchers could obtain “confirmation” for their model.

Research limitations/implications

Researchers should be more conscious, open and respectful regarding different research paradigms.

Practical implications

Researchers should select a statistical model that adequately represents their theory, not necessarily a common factor model, and formulate their model explicitly. Particularly for instrumentalists, pragmatists and constructivists, the composite model appears promising. Researchers should be concerned about their estimator’s properties, not about whether it is called “PLS.” Further, researchers should critically evaluate their model, not seek confirmation or blindly believe in its value.

Originality/value

This paper critically appraises Cadogan and Lee (2022) and reminds researchers who wish to use structural equation modeling, particularly PLS, for their statistical analysis, of some important scientific principles.

Article
Publication date: 26 November 2020

Wen-Lung Shiau, Xiaodie Pu, Soumya Ray and Charlie C. Chen

142

Abstract

Details

Industrial Management & Data Systems, vol. 120 no. 12
Type: Research Article
ISSN: 0263-5577

Article
Publication date: 6 May 2014

Gholamhossein Mehralian, Jamal A. Nazari, Peyman Akhavan and Hamid Reza Rasekh

This paper aims to explore the relationship between knowledge creation and intellectual capital (IC) through an empirical study in the pharmaceutical industry. In the current…

1043

Abstract

Purpose

This paper aims to explore the relationship between knowledge creation and intellectual capital (IC) through an empirical study in the pharmaceutical industry. In the current economy, knowledge and IC are considered as the most important organizational assets and are the key resources in gaining competitive advantage.

Design/methodology/approach

This paper adopts the socialization, externalization, combination and internalization (SECI) model to examine the format of knowledge creation processes (KCP) and uses a model to demonstrate the relationship between KCP and IC and its components in the pharmaceutical industry. A valid instrument was adopted to collect the required data on KCP and and IC dimensions. Structural equation modeling was used to assess the measurement model and to test the research hypotheses using the data collected from 470 completed questionnaires.

Findings

The results supported the research model and revealed that KCP has significant influence on the accumulation of human capital. The performance of human capital manifests significant impact on structural capital and relational capital.

Practical limitations/implications

Given the strong association between KCP and IC, managers should define their own robust operations for knowledge creation to improve their IC accumulation.

Originality/value

This research departs from the earlier research on KCP–IC by adopting the SECI model and a research model that facilitates the exploration of the relationship between KCP and IC dimensions in the pharmaceutical industry. The research results provided strong support for the KCP–IC relationship.

Details

The Learning Organization, vol. 21 no. 4
Type: Research Article
ISSN: 0969-6474

Keywords

Article
Publication date: 27 February 2018

Gholamhossein Mehralian, Jamal A. Nazari and Peivand Ghasemzadeh

Knowledge is a key success factor in achieving competitive advantage in the current fast-paced and uncertain economic environment. Several studies in the literature have analyzed…

2242

Abstract

Purpose

Knowledge is a key success factor in achieving competitive advantage in the current fast-paced and uncertain economic environment. Several studies in the literature have analyzed the relationship between knowledge creation (KC) and organizational success; however, the mechanisms by which KC leads to accumulation of intellectual capital (IC) and thereby affects various dimensions of organizational performance are understudied. The purpose of this paper is to examine how KC and IC and their relationship influence key dimensions of organizational performance.

Design/methodology/approach

A research model was developed and tested based on the literature in the areas of KC, IC and organizational performance. This study uses a survey sent to companies in an intensive knowledge-based industry. The balanced scorecard (BSC) approach was used to measure the key dimensions of organizational performance.

Findings

The results from structural equation modeling (SEM) on 470 completed questionnaires received from the pharmaceutical companies in Iran reveal that KC activities lead to the accumulation of organizational IC and IC has a crucial and positive impact on the BSC. Furthermore, the results from the path analysis indicate that IC mediates the effects of KC on the BSC.

Practical implications

The findings of this study contribute to the extant literature on the relationship between knowledge and organizational performance by demonstrating that knowledge and KC lead to performance when organizations utilize KC activities and leverage them to accumulate IC. Once used effectively, IC will result in a better performance in the knowledge-intensive environments.

Originality/value

This is the first study that investigates how KC contributes to firm performance by incorporating the mediating impact of IC on the BSC. The proposed model and results will help organizations to identify the mechanisms through which KC initiatives improve organizational performance.

Details

Journal of Knowledge Management, vol. 22 no. 4
Type: Research Article
ISSN: 1367-3270

Keywords

Article
Publication date: 2 September 2013

Edward S.T. Wang

Although the increase in point-of-purchase decisions heightens the communication potential of food product packaging, empirical research on understanding how visual packaging…

19798

Abstract

Purpose

Although the increase in point-of-purchase decisions heightens the communication potential of food product packaging, empirical research on understanding how visual packaging affects consumers' subsequent product and brand evaluations and perceptions is scant. This study seeks to develop a theoretical model to show the effects of consumer attitudes toward visual food packaging on perceived product quality, product value, and brand preference.

Design/methodology/approach

A self-administered questionnaire developed from the literature was conducted, and 315 undergraduate students participated in the study.

Findings

The empirical results show that attitudes toward visual packaging directly influence consumer-perceived food product quality and brand preference. Perceived food product quality also directly and indirectly (through product value) affects brand preference.

Originality/value

This paper offers directions for understanding the effects of visual packaging on positive consumer product and brand evaluations. Based on the study findings, food firms should emphasize the visual packaging design factors such as color, typeface, logo, graphics, and size to form consumers' positive perceptions and brand preference.

Details

International Journal of Retail & Distribution Management, vol. 41 no. 10
Type: Research Article
ISSN: 0959-0552

Keywords

Article
Publication date: 18 January 2013

Hsin Hsin Chang, Yao‐Chuan Tsai and Che‐Hao Hsu

The aim of this study is to discuss the relationship between e‐procurement and supply chain performance.

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Abstract

Purpose

The aim of this study is to discuss the relationship between e‐procurement and supply chain performance.

Design/methodology/approach

Both interviews with practicing managers and an empirical study were conducted in the current study. Interviews with four practicing managers were conducted to gather the practical insights of the theoretical framework. Empirical data were collected from 108 Taiwanese enterprises.

Findings

The paper found that partner relationships, information sharing, and supply chain integration can represent the processes through which e‐procurement contributes to supply chain performance. Supply chain integration has the highest standardized total effect on supply chain performance.

Research limitations/implications

Future studies could more systematically analyze the relationships among e‐procurement, supply chain integration and supply chain performance. Cross‐level analysis is also worthy of investigation when considering the influence of technology‐usage characteristics.

Practical implications

Compared to partner relationships and information sharing, supply chain integration has more influences on supply chain performance. Therefore, this study suggests that a joint‐learning practice can be implemented for properly managing supply chains (e.g. know‐how collaboration, mutual competency creation).

Originality/value

This paper contributes to the literature by proposing and testing the influences of partner relationships, information sharing, and supply chain integration. This allows a strategic viewpoint when implementing e‐procurement systems intended to improve supply chain performance.

Details

Supply Chain Management: An International Journal, vol. 18 no. 1
Type: Research Article
ISSN: 1359-8546

Keywords

Article
Publication date: 8 April 2014

Yamen Koubaa, Rym Srarfi Tabbane and Rim Chaabouni Jallouli

– The purpose of this paper is to assess the use of structural equation modeling in one specific field of marketing research, the image research.

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Abstract

Purpose

The purpose of this paper is to assess the use of structural equation modeling in one specific field of marketing research, the image research.

Design/methodology/approach

A meta-analysis of a sample of image marketing works using structural equation modeling (SEM). The period of investigation is limited to the last five years to test for possible positive return of previous assessments of SEM use on the current SEM application.

Findings

Following this work, three major conclusions emerged: the study of homogenous samples of SEM models is required to get to accurate assessment of using the technique; SEM application is getting better probably due to learning from SEM reviews; and the reliance on a conjoint assessment of the various SEM issues is necessary to avoid parsimonious assessments. This study has provided a concise and refreshed view on the use of SEM in one marketing field, the image research.

Research limitations/implications

47 SEM papers and 99 models along five years were examined through this research. Although the authors reviewed four of the most consulted databases in marketing, the authors might miss several interesting works not available in these databases during the investigation. It is interesting to add on the works reviewed in this study and to re-conduct the analysis. The objective is not to doubt the consistency of SEM image research but to provide writers and readers with tools that enable them to produce better quality SEM research. Moreover, the quantitative analysis could be larger. Future research can consider computing other statistics. Finally, in the standards of most of marketing journals, this paper is a bit long. But as suggested by Babin et al., journal editors should allow more space to SEM-based reviews as the nature of the discussion requires lengthening.

Practical implications

Mastering the statistical tool in marketing research is as important as mastering the conceptual tool. Statistical learning and/or cooperation with statisticians is recommended.

Originality/value

A multi-criteria review of works from one specific field in marketing research and across a recent period of time allowing for the test of possible positive return from previous reviews of SEM use on the quality of the current publications of SEM papers.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 26 no. 2
Type: Research Article
ISSN: 1355-5855

Keywords

Article
Publication date: 10 August 2012

Jee Young Seong and Amy L. Kristof‐Brown

This study seeks to investigate the multidimensionality person‐group (PG) fit. It first aims to examine values‐based, personality‐based, and KSA‐based fit as distinct PG fit…

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Abstract

Purpose

This study seeks to investigate the multidimensionality person‐group (PG) fit. It first aims to examine values‐based, personality‐based, and KSA‐based fit as distinct PG fit dimensions. It then also aims to examine fit as an aggregate construct (each dimension combines to form a latent PG fit construct), and as a superordinate construct (an overarching assessment of compatibility drives the individual fit dimensions). It also aims to propose that the distinct dimensions or the overall perception predict commitment to team, employee voice, and knowledge sharing, resulting in a final outcome of employee task performance.

Design/methodology/approach

Data were collected using longitudinal survey methodology from three different sources (793 employees, their supervisors and the Human Resources department) in a manufacturing firm in Korea. The various models were evaluated using structural equation modeling.

Findings

The distinct dimensions model, in which values‐based fit predicted commitment to the team, personality‐based fit predicted voice behaviors, and KSA‐based fit predicted knowledge sharing, was mostly supported. Each of these intermediary factors predicted supervisors' ratings of individual task performance. Although each dimension had unique impact on the outcomes, results suggested that a superordinate PG construct might be driving the more specific fit assessments. The aggregate model was not supported.

Originality/value

This study is the first to show how different dimensions of PG fit may differentially influence affect and behavior, to predict task performance. It also shows the first evidence for PG fit as a superordinate multidimensional construct. Results provide a basis for new knowledge regarding the multi‐faceted relationship between fit perceptions and outcomes.

Details

Journal of Managerial Psychology, vol. 27 no. 6
Type: Research Article
ISSN: 0268-3946

Keywords

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