Rethinking balanced scorecard (BSC) measures: formative versus reflective measurement models

2017 ◽  
Vol 66 (1) ◽  
pp. 92-110 ◽  
Author(s):  
Sungbum Park ◽  
Heeseok Lee ◽  
Seong Wook Chae
Keyword(s):  
Balanced Scorecard ◽  
Latent Variables ◽  
Structural Equation ◽  
Model Comparison ◽  
Empirical Studies ◽  
Equation Modeling ◽  
Content Type ◽  
Formative Measurement ◽  
Measurement Models ◽  
Formative Indicators

Purpose Most empirical balanced scorecard (BSC) studies have shown a tendency to wrongly employ reflective indicators instead of the more theoretically suitable formative indicators. However, formative indicators are difficult to apply due to the lack of statistical software support and a standardized model testing method. The paper aims to discuss these issues. Design/methodology/approach This study empirically compares the reflective and formative measurement method with standardized model comparison criteria. After collecting 217 valid questionnaires from companies in South Korea, the authors applied a structural equation modeling technique to analyze the data. Findings The result shows that the formative measure provides greater validity for the corporate performance measurement using BSC. Further, this study shows the indicators’ relative influence on each BSC perspectives using the formative measure. Practical implications This study proved the usefulness of the formative measure analysis method and suggested its practical use, focusing on the indicators most useful in developing corporate strategies. In addition, the authors showed that formative indicators could be used in the corporate environment by overcoming the limitations of conventional studies that were confined to causal relationships with latent variables. Originality/value This study may be the pioneering work that compares formative and reflective indicators simultaneously, addressing the usefulness of formative measurement and its application validity in the existing empirical studies using reflective measurements.

scholarly journals HTMT2–an improved criterion for assessing discriminant validity in structural equation modeling

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ellen Roemer ◽  
Florian Schuberth ◽  
Jörg Henseler
Keyword(s):  
Structural Equation Modeling ◽  
Latent Variables ◽  
Structural Equation ◽  
Discriminant Validity ◽  
Empirical Studies ◽  
Geometric Mean ◽  
Equation Modeling ◽  
Content Type ◽  
Measurement Models ◽  
Loading Patterns

PurposeOne popular method to assess discriminant validity in structural equation modeling is the heterotrait-monotrait ratio of correlations (HTMT). However, the HTMT assumes tau-equivalent measurement models, which are unlikely to hold for most empirical studies. To relax this assumption, the authors modify the original HTMT and introduce a new consistent measure for congeneric measurement models: the HTMT2.Design/methodology/approachThe HTMT2 is designed in analogy to the HTMT but relies on the geometric mean instead of the arithmetic mean. A Monte Carlo simulation compares the performance of the HTMT and the HTMT2. In the simulation, several design factors are varied such as loading patterns, sample sizes and inter-construct correlations in order to compare the estimation bias of the two criteria.FindingsThe HTMT2 provides less biased estimations of the correlations among the latent variables compared to the HTMT, in particular if indicators loading patterns are heterogeneous. Consequently, the HTMT2 should be preferred over the HTMT to assess discriminant validity in case of congeneric measurement models.Research limitations/implicationsHowever, the HTMT2 can only be determined if all correlations between involved observable variables are positive.Originality/valueThis paper introduces the HTMT2 as an improved version of the traditional HTMT. Compared to other approaches assessing discriminant validity, the HTMT2 provides two advantages: (1) the ease of its computation, since HTMT2 is only based on the indicator correlations, and (2) the relaxed assumption of tau-equivalence. The authors highly recommend the HTMT2 criterion over the traditional HTMT for assessing discriminant validity in empirical studies.

Is lodging research suffering from methods bias? An assessment of published research during 1990-2016

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Faizan Ali ◽  
Mehmet Ali Koseoglu ◽  
Fevzi Okumus ◽  
Eka Diraksa Putra ◽  
Mehmet Yildiz ◽  
...  
Keyword(s):  
Structural Equation ◽  
Quantitative Methods ◽  
Empirical Studies ◽  
Secondary Data ◽  
Equation Modeling ◽  
Content Type ◽  
Data Collection And Analysis ◽  
Hospitality And Tourism ◽  
Method Bias ◽  
Published Research

Purpose The study aims to investigate if lodging research suffers from a method bias by comprehensively reviewing the research methodology used in lodging related research articles. Design/methodology/approach In all, 2,647 published papers in 16 leading hospitality and tourism published between 1990 and 2016 are analyzed using bibliometric technique. Findings In all, 69% of the empirical studies in lodging research across 26 years period used quantitative methods, with an increasing reliance on regression-based analysis and structural equation modeling, a disturbing plunging trend in methods diversity. Findings also suggest an increasing trend of using secondary data. Research limitations/implications Based on the findings of this study, theoretical and practical implications for hospitality and tourism researchers are provided. Originality/value This is the first study that reviewed a large corpus of published research (2,647 papers in 16 hospitality and tourism journals from the last 27 years) to highlight (a) methodology used, (b) methods employed and (c) data collection and analysis procedures.

scholarly journals Critical factors that impact purchase online of new telecom convergent services in the Mexican market

2017 ◽  
Vol 7 (14) ◽  
Author(s):  
Rolando Zubirán Shetler ◽  
Jesús Fabian López Pérez
Keyword(s):  
Electronic Commerce ◽  
Technology Acceptance ◽  
Latent Variables ◽  
Diffusion Of Innovations ◽  
Structural Equation ◽  
Empirical Studies ◽  
The United States ◽  
Structural Equations ◽  
Equation Modeling ◽  
Critical Factors

Key words: Diffusion of innovations, electronic commerce, structural equations, Smart-PLS, technology acceptanceAbstract. The following article analyzes the principal factors that have an impact in the adoption of new telecom convergent services, through electronic commerce, that have been explored and studied primarily in developed markets such as the United States and that have been deemed as critical factors in the development and growth of online electronic transactions. Specifically, factors and latent variables of this study derive from the models of Technology Acceptance (Davis, 1989) and Diffusion of Innovations (Rogers, 2003). A summary of past empirical studies is provided deriving from the aforementioned theoretical models followed by results of an exploratory field study comprising of 253 valid observations randomly selected from within the population of urban internet users in Mexico. The methodology used to determine the causal relationship between variables (Betas) was factor analysis (Principal Components) and structural equation modeling, specifically Smart-PLS. The study determined that perceived utility and trust variables are statistically relevant and significant in determining purchase online of new telecom convergent services and the development of electronic commerce in the Mexican Market.Palabras clave: Aceptación de la tecnología, comercio electrónico, difusión de las innovaciones, ecuaciones estructurales, Smart-PLS.Resumen. Este artículo analiza los principales factores que influyen en la adopción de los nuevos servicios convergentes de telecomunicaciones, a traves del comercio electrónico, que han sido explorados y estudiados principalmente en mercados desarrollados como el de Estados Unidos y que han sido confirmados como factores críticos en el desarrollo y el crecimiento de las transacciones electrónicas en linea. Específicamente, los factores y variables latentes en este estudio se derivan de los modelos de Aceptación de la Tecnología (Davis, 1989) y la Difusión de las Innovaciones (Rogers, 2003). Se presenta un resumen de los antecedentes de estudios empíricos derivados de los mencionados modelos teóricos, seguido de los resultados de un estudio exploratorio de campo que comprende 253 observaciones válidas seleccionadas en forma aleatoria dentro de la población de usuarios urbanos de Internet en México. La metodología utilizada para determinar las relaciones causales entre las variables (Betas) fue análisis factorial (Componentes Principales) y el modelo de ecuaciones estructurales, específicamente Smart-PLS. El estudio determina que las variables percepción de utilidad y confianza son estadísticamente relevantes y significativas en la determinación de compra en línea de nuevos servicios convergentes de telecomunicaciones y en el desarrollo del comercio electrónico en el Mercado Mexicano.

scholarly journals ASSESSING THE FACTORS CAUSING PROJECT COMPLETION DELAYS IN THE CONSTRUCTION SECTOR OF OMAN USING SEM-PLS

2020 ◽  
Vol 8 (3) ◽  
pp. 900-912 ◽  
Author(s):  
Iman Suleiman Al Maktoumi ◽  
Firdouse Rahman Khan ◽  
Ahmed Rashid Suwied Al Maktoumi
Keyword(s):  
Structural Equation ◽  
Construction Projects ◽  
Goodness Of Fit ◽  
Raw Materials ◽  
Equation Modeling ◽  
Related Factors ◽  
Formative Measurement ◽  
Project Completion ◽  
Measurement Models ◽  
Process Allocation

Purpose: The objectives of the study were to investigate the causes of the delays to analyze the factors causing the construction delay in Oman and to investigate the effects of such delays. Design/methodology/approach: To carry out this study 210 samples were collected through a well-defined questionnaire from the construction stakeholders viz. the consultants, contractors, and the clients who were selected on a random sampling basis. Smart PLS for Structural Equation Modeling (SEM) technique was used to analyze the data to obtain the formative measurement models, the structured model, and the goodness of fit. Findings: The results of the study reveal that the client-related factors, equipment-related factors, and material related factors have a significant impact on the completion delay in construction projects. The findings of the study also revealed that the Client related factors were – Delay in providing services, Delayed decision-making process, Allocation of insufficient time. Equipment related factors were – Existing low productive equipment, Unskillful Equipment operator, Breakdown of equipment and Outdated equipment; Material related factors were – Delay in supply of raw materials, Non-availability of materials, Change of materials during construction, Non-availability of accessories and Damaged materials. Research limitations/Implications: The present study covers the stakeholders of the construction projects from selected regions only. The future studies can be extended to other projects and other regions as well. Social implications: The study suggested that the clients’ cooperation especially in providing the contractors with the necessary equipment, facilities, and sufficient time will avoid such delays of the construction projects in Oman. Originality/Value: Only very few have examined the completion delay of the construction projects in Oman using SEM-PLS and it is a first-hand study of its kind and the results will be useful to the stakeholders.

Identifying and treating unobserved heterogeneity with FIMIX-PLS

2016 ◽  
Vol 28 (2) ◽  
pp. 208-224 ◽  
Author(s):  
Lucy M. Matthews ◽  
Marko Sarstedt ◽  
Joseph F. Hair ◽  
Christian M. Ringle
Keyword(s):  
Structural Equation ◽  
Latent Class ◽  
Structural Model ◽  
Unobserved Heterogeneity ◽  
Equation Modeling ◽  
Content Type ◽  
Measurement Models ◽  
European Business ◽  
Number Of Segments

Purpose Part I of this article (European Business Review, Volume 28, Issue 1) offered an overview of unobserved heterogeneity in the context of partial least squares structural equation modeling (PLS-SEM), its prevalence and challenges for social sciences researchers. This paper aims to provide an example that explains how to identify and treat unobserved heterogeneity in PLS-SEM by using the finite mixture PLS (FIMIX-PLS) module in the SmartPLS 3 software (Part II). Design/methodology/approach This case study illustrates the application of FIMIX-PLS using a popular corporate reputation model. Findings The case study demonstrates the capability of FIMIX-PLS to identify whether unobserved heterogeneity significantly affects structural model relationships. Furthermore, it shows that FIMIX-PLS is particularly useful for determining the number of segments to extract from the data. Research limitations/implications Since the introduction of FIMIX-PLS, a range of alternative latent class techniques has appeared. These techniques address some of the limitations of the approach relating to, for example, its failure to handle heterogeneity in measurement models, or its distributional assumptions. This research discusses alternative latent class techniques and calls for the joint use of FIMIX-PLS and PLS prediction-oriented segmentation. Originality/value This article is the first to offer researchers, who have not been exposed to the method, an introduction to FIMIX-PLS. Based on a state-of-the-art review of the technique, the paper offers a step-by-step tutorial on how to use FIMIX-PLS by using the SmartPLS 3 software.

Consumer response to private label brands’ negative publicity: a relational effect on retailer’s store image

2017 ◽  
Vol 26 (2) ◽  
pp. 204-222 ◽  
Author(s):  
Hanna Gendel-Guterman ◽  
Shalom Levy
Keyword(s):  
Structural Equation ◽  
Empirical Studies ◽  
Product Category ◽  
Private Label ◽  
Equation Modeling ◽  
Store Image ◽  
Content Type ◽  
Negative Publicity ◽  
Image Context ◽  
Potential Damage

Purpose This study aims to examine the effect of private label brand (PLB) products’ negative publicity (NP) events on PLB general image and retailer’s store image, because of the suggested interdependency between retailer’s store image and PLB image. Design/methodology/approach Three empirical studies were conducted to test the NP effect – Studies 1 and 2, respectively; and test the occurrence of moderate and extreme NP events regarding the functional PLB product category. Study 3 replicates prior studies conducted on the hedonic product category. In these studies, participants were randomly assigned to treatment and control groups. The studies use factor analysis methods following t-tests and paths analyses, using structural equation modeling (SEM). Findings Findings show that both moderate and extreme NP have an influence on the PLB’s image dimensions. These effects “spilled over” to the entire range of PLB products, regardless of the category of the damaged product. Regarding retailer’s store image, the effect of NP was retained in the product-related image context and did not exceed that of the store-related image. However, in relation to functional products, when NP is very extreme, the effect on PLB image exceeds that of retailer’s store image. Practical implications Retailers should invest more efforts in their PLB product selection, quality maintenance and supervision to eliminate potential damage from events related to their PLB products. Originality/value The originality of this study is in the association of two streams of research: NP effects and the relationship between PLB image and retailer’s store image.

A structural equation model for big data adoption in the healthcare supply chain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dindayal Agrawal ◽  
Jitender Madaan
Keyword(s):  
Factor Analysis ◽  
Big Data ◽  
Supply Chain ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Model ◽  
Equation Modeling ◽  
Data Governance ◽  
Social Perspective ◽  
Content Type

PurposeThe purpose of this study is to examine the barriers to the implementation of big data (BD) in the healthcare supply chain (HSC).Design/methodology/approachFirst, the barriers concerning BD adoption in the HSC were found by conducting a detailed literature survey and with the expert's opinion. Then the exploratory factor analysis (EFA) was employed to categorize the barriers. The obtained results are verified using the confirmatory factor analysis (CFA). Structural equation modeling (SEM) analysis gives the path diagram representing the interrelationship between latent variables and observed variables.FindingsThe segregation of 13 barriers into three categories, namely “data governance perspective,” “technological and expertise perspective,” and “organizational and social perspective,” is performed using EFA. Three hypotheses are tested, and all are accepted. It can be concluded that the “data governance perspective” is positively related to “technological and expertise perspective” and “organizational and social perspective” factors. Also, the “technological and expertise perspective” is positively related to “organizational and social perspective.”Research limitations/implicationsIn literature, very few studies have been performed on finding the barriers to BD adoption in the HSC. The systematic methodology and statistical verification applied in this study empowers the healthcare organizations and policymakers in further decision-making.Originality/valueThis paper is first of its kind to adopt an approach to classify barriers to BD implementation in the HSC into three distinct perspectives.

Barriers to radical innovation in research institutions in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jianhua Yang ◽  
Rafif Al-Sayed
Keyword(s):  
Theoretical Model ◽  
Latent Variables ◽  
Structural Equation ◽  
Business Models ◽  
Research Collaboration ◽  
Statistical Significance ◽  
Radical Innovation ◽  
Equation Modeling ◽  
Research Institutions ◽  
Content Type

Purpose This study aims to develop a better understanding of radical innovation performance and proposes a comprehensive and theoretical model of the barriers impeding radical innovation from the perspective of researchers working in research institutions in China. Both quantitative and qualitative techniques were used to test the hypotheses regarding barriers to radical innovation and the model proposed in this research. Design/methodology/approach The data was collected through questionnaires and semi-structured interviews with researchers from different research institutions across several cities in China. Next, the data was analyzed by deploying the structural equation modeling technique and calculating the statistical significance of correlations, regression and path coefficients among the latent variables. Findings The results indicated the major barriers impeding radical innovation in Chinese research institutes. Based on these findings, suggested policies, regulations and business models are put forward that can promote radical innovation in these institutes through increasing research freedom, enhancing organizational flexibility, attracting talented researchers and expanding research collaboration. Originality/value The research proposes a comprehensive and theoretical model of the barriers impeding radical innovation from the perspective of researchers working in research institutions in China.

Unveiling business school interns' satisfaction toward online summer internship program amid COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rashmi Maini ◽  
Sanandi Sachdeva ◽  
Guneet Kaur Mann
Keyword(s):  
Business School ◽  
Structural Equation ◽  
Empirical Studies ◽  
North India ◽  
Equation Modeling ◽  
Successful Implementation ◽  
Cross Sectional ◽  
Content Type ◽  
Global Pandemic ◽  
The University

PurposeThe objective of this research is to explore factors that influence interns' satisfaction (is) toward the e-internship program, an alternate adopted by management institutes in lieu of the regular summer internship amidst the global pandemic, coronavirus disease 2019 (COVID-19).Design/methodology/approachA cross-sectional research design with a self-reported questionnaire was conducted on business school (B-school) interns to rate the factors that contribute to their e-internship satisfaction. Structural equation modeling was used to examine the responses obtained from 203 B-school interns with a diverse demographic background belonging to a government university of North India. Convenience sampling was employed to get valid responses from interested respondents.FindingsResults revealed that although all the four factors under consideration, faculty mentors' preparedness (FMP), industry mentors' preparedness (IMP), interns' readiness toward online internship and interns' Internet efficacy (IIE) are significantly related to IS, industry mentors' role was found to have a major impact on the IS. The study unravels that industry mentors' interaction has a potential role in the successful implementation of e-internships.Research limitations/implicationsThe study has implications for the university as well as the companies to ponder on factors that satisfy interns during the virtual internship and designing an effective internship program by having a collaborative approach.Originality/valueThere is a dearth of empirical studies on internships in general and e-internship in particular, so this study fills the gap and contributes to the existing literature and provides ways to satisfy B-school interns toward e-internship by addressing the key factors.

Trust factors for organic foods: consumer buying behavior

2019 ◽  
Vol 122 (2) ◽  
pp. 414-431 ◽  
Author(s):  
Tsung Hung Lee ◽  
Chung-Jen Fu ◽  
Yin Yuan Chen
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Organic Food ◽  
Equation Modeling ◽  
Small Scale ◽  
Buying Behavior ◽  
Organic Foods ◽  
Behavior Theory ◽  
Content Type ◽  
Trust Factors

Purpose The purpose of this paper is to assess the relationship between trust factors and buying behavior among consumers in the organic food market in Taiwan. Design/methodology/approach The researchers developed a questionnaire using latent variables including the trust factors, utilitarian attitudes, hedonic attitudes, buying behavior and demographic information of consumers of organic foods. Confirmatory factor analysis and the structural equation modeling were conducted using LISREL 8.80 for Windows. Findings The empirical results indicated that health content, locally produced products, organic food labels and price premiums positively and significantly affected utilitarian and hedonic attitudes. Both utilitarian attitudes and hedonic attitudes positively and significantly affected respondents’ buying behavior. A series of theoretical implications were identified. Practical implications The researchers concluded that providing consumers with practical information related to organic food, establishing local production facilities, developing content, standardizing labeling procedures and promoting a new organic certification system for small-scale producers will encourage more consumers to purchase organic food. Originality/value This study first examines the food trust buying behavior of organic foods and related consumption behavior theory questions. It mainly takes the stimulus–organism–response model as the foundation of its approach. Simultaneously, it also conforms to utilitarian behavior theory, and the process by which consumers become better aware of organic foods’ quality.

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