A Comparison between Two Balanced Scorecards: Optimal vs. Kaplan and Norton Model

Morard, Bernard; Stancu, Alexandru; Jeannette, Christophe

doi:10.7763/joebm.2015.v3.199

Cited by 5 publications

(21 citation statements)

References 10 publications

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“…As Morard et al (2015, p. 303) [2] argue, PLS has "its inherent limitations [among which the most notable is] that it is a limited information technique, designed to maximize prediction, rather than fit." But it shows a potential management use as a statistical analysis, because PLS analysis can make a prediction without a large data sample (Morard and Stancu, 2005) [13].…”

Section: General Overviewmentioning

confidence: 99%

“…Zeta (ζ) is the residual vector, which is uncorrelated to any other vector. The particularity of this model is that there is no loop (Morard et al, 2015) [2].…”

Section: Pls Characteristics and Algorithmmentioning

confidence: 99%

“…Because it combines the statistical methods PLS and PCA into a single tool, PLS-A provides added value compared with other kinds of software on the market. It allows users to "compute the principal component analysis (PCA), estimate the path weighting scheme and, finally, generate bootstrap validation procedure and assess the best model from all possible graphs" (Morard et al 2015, p. 304) [2]. In other words, it computes the number of axes, the latent variables needed to build a new model, and the connections between the axes, as well as allowing the interpretation of the axes.…”

Section: Historymentioning

confidence: 99%

“…Finally, SEM will always be an approximated reality, as it uses mathematical linear relations in the computation (DeVault, 2007) [14]. Working on the development of models in accounting and controlling, Morard et al (2015) [2] add another layer by arguing that any researcher could make collected data fit any generated model if this is "necessary" to complete the study. In other words, depending on the chosen model, the estimation will always be considered correct.…”

Section: General Overviewmentioning

confidence: 99%

“…As PLS is particularly complex in a statistical context, most of the researchers presently using standard statistics like SEM are not interested in this tool with regard to computing data analysis and interpreting the results. Recently, a derivation of PLS, called optimal PLS (Jeannette, 2014;Morard et al, 2015) [1], [2], was developed. Unlike the existing types of PLS analyses, it selects the best graph of all possible graphs that can be generated for given data.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Introducing an Optimal (and a Simpler) Approach to Partial Least Squares Analyses

Simonin¹,

Morard²

2017

IJTEF

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Abstract-The purpose of this study is to show the many possibilities that partial least squares (PLS) analysis offers, as well as its ease of use. This analysis is a useful tool, because it brings an additional point of view to statistical analysis beyond that of structural equation modeling analysis. Here, the authors suggest using a different approach to PLS, called "optimal PLS." It combines principal component analysis and PLS analysis to compute the data; by convergent iterations, this approach produces an optimal model not based on a reference model to best explain a given situation. The study illustrates this approach with two practical applications that create optimal models from the ground up: one in management controlling and the other in marketing. The software, which is used as a computational tool, has an algorithm based on optimal PLS. The study is original, because it chooses two opposing fields of research, namely management controlling (a quantitative discipline) and consumer behavior research (a qualitative discipline), in an attempt to understand when optimal PLS provides reliable results. The authors conclude that the use of PLS is multifaceted, and optimal PLS has a high capacity to explain the actual components, which helps researchers and analysts reach appropriate strategic decisions. With regard to the study's practical implications, the overview and the accompanying explanations will enable academics and analysts to use PLS analysis more easily by means of optimal PLS approach's five steps. They can add PLS and optimal PLS to their list of analytical tools to bring fresh points of view to their research.Index Terms-Partial least squares path modeling, optimal PLS, optimal strategy, marketing research, consumer behavior, management controlling, algorithm, software.

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Section: General Overviewmentioning

confidence: 99%

“…Zeta (ζ) is the residual vector, which is uncorrelated to any other vector. The particularity of this model is that there is no loop (Morard et al, 2015) [2].…”

Section: Pls Characteristics and Algorithmmentioning

confidence: 99%

Section: Historymentioning

confidence: 99%

Section: General Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Introducing an Optimal (and a Simpler) Approach to Partial Least Squares Analyses

Simonin¹,

Morard²

2017

IJTEF

Self Cite

View full text Add to dashboard Cite

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Organizational and Methodological Support of the Strategic Analysis of the Resource Potential of Smart University

Berdnikova,

Igoshina,

Vasilchuk

et al. 2023

Smart Innovation, Systems and Technologies

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Examining the influence of expatriates’ social capital and knowledge-sharing behavior on financial performance

Lee

Pham

2019

IJOA

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Purpose The purpose of this paper is to examine the impact of expatriate’s social capital and knowledge sharing on multinational companies’ (MNCs) financial performance, with a specific focus on the influence of trust, commitment, organizational support and the four elements of balanced scorecard (BSC). Design/methodology/approach A quantitative questionnaire survey was conducted using expatriates of MNCs in Taiwan as the respondents. Findings Trust and organizational support are significant predictors of knowledge sharing and social capital, which further facilitate their influence on learning and growth, customer satisfaction, internal process improvement and financial performance of MNCs. Besides, social capital serves as an accelerate agent to promote the influence of trust on knowledge sharing, and customer satisfaction serves as a catalyst on the influence of learning and growth and internal process on a firms’ financial performance. Practical implications This study provides a clear articulation of the role of knowledge sharing on the financial performance and its moderation effect on the elements of BSC. Trust and organizational support are essential for knowledge sharing and expatriates’ social capital. The roles of social capital and knowledge sharing are critical for expatriates to be success in the overseas market places. Originality/value Since the evidences regarding expatriate performance rarely integrate the variables of social capital, knowledge sharing and BSC into a more comprehensive framework, the results of this study can be an important reference for academicians to do further validation. These results are also critical for practitioners to develop dispatching policies for the expatriates in the oversea market places.

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A Comparison between Two Balanced Scorecards: Optimal vs. Kaplan and Norton Model

Cited by 5 publications

References 10 publications

Introducing an Optimal (and a Simpler) Approach to Partial Least Squares Analyses

Introducing an Optimal (and a Simpler) Approach to Partial Least Squares Analyses

Organizational and Methodological Support of the Strategic Analysis of the Resource Potential of Smart University

Examining the influence of expatriates’ social capital and knowledge-sharing behavior on financial performance

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