Repeated ANOVA

Repeated ANOVA in SPSS

Procedia Economics and Finance 32 ( 2015 ) 338 – 344

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© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Selection and peer-review under responsibility of Asociatia Grupul Roman de Cercetari in Finante Corporatiste

doi: 10.1016/S2212-5671(15)01402-1

Available online at

Emerging Markets Queries in Finance and Business

Repeated Measures Analysis on Determinant Factors of
Enterprise Value

Gioacasi Diana*

Alexandru Ioan Cuza University, Iasi, Romania


Enterprise value is the result of interaction between financial and nonfinancial factors. Financial factors represent important
resources in production of goods but their contribution on enterprise has decreased with the development of knowledge-
based economy. Acceptance of nonfinancial factors as elements generating future benefits imposed the application of
European politicies concerning nonfinancial reporting for multinationals.
The objective of this article is the variation analysis of the most significant financial and nonfinancial factors of enterprise
value. The analyzed sample consist of 400 european multinationals for the period 2009-2012.
The statistical tool used was SPSS 20 and work method was repeated measures ANOVA. The results showed several
evolution of factors analyzed, providing support for developed of factors that increase enterprise value.

© 2015 Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Selection and peer-review under responsibility of the Emerging Markets Queries in Finance and Business local

Keywords: nonfinancial factors, repeated measures ANOVA, market value, book value

* Corresponding author. Tel.: 0040-745-390-042;
E-mail address:

© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Selection and peer-review under responsibility of Asociatia Grupul Roman de Cercetari in Finante Corporatiste

339 Gioacasi Diana / Procedia Economics and Finance 32 ( 2015 ) 338 – 344

1. Introduction

In the knowledge-based economy, non-financial factors are elements which create value, complementary to
the financial and tangible capital. Today it is widely accepted by investors and managers that multinationals
incorporates inimitable and non-substitutable resources with significant implications on the development of
competitive advantages.

Both the role of multinational corporations in developing and effectively managing non-financial factors but
also the lack of information released to the investors on these resources imposed the application of a European
legislation on non-financial reporting.

2. Review of prior literature

In the knowledge-based economy, the company’s market value is calculated by the following algorithm:
Market value (MV) = Book value (BV) + nonfinancial factors (IC), where MV represents the total value of the
issued shares of the company, being equal to the share price times the number of shares outstanding, BV is the
excess of all assets and debts of an entity on all their debts and IC – assembly of non-financial factors impacting
enterprise results.

The classification of non-financial factors was developed by Stewart (1997) and presents the following
structure: (a) human capital represents all the knowledge and competencies of the employees; (b) structural
capital represents all policies and procedures that support human capital to create economic value and financial
health (Bontis and Serenko, 2009) and (c) relational capital represents all external relationships that contribute
to long-term performance of the company (Ittner, 2008).

Based on classification of Stewart, we selected the most important nonfinancial factors from the perspective
of social responsibility (table 1).

Table 1. Types of non-financial factors

Variable Explanation

Benefits (CB)

The company’s ability to ensure the loyalty and productivity of the workforce through
a fair and correct treatment and develop lasting relationships with employees through
promotion procedures.

Training (TH) Enterprise’s ability to ensure optimal working conditions through professional
development programs and labor protection.

Diversity (DI) Enterprise ability to support workforce diversity and ensure fair and non-
discriminatory treatment.


Product (PR) Entity’s ability to develop, design and effectively manage its impact on civil society
Resource management

Degree of optimization of resources in the production of goods and services as
improving distribution channels and reduce water and energy consumption.

Leadership ethics Entity’s ability to treat his business partners fairly and maintain long-term
collaborative relationships.

Transparency &
reporting (TR)

Entity’s ability to enforce corporate policies aligned with the objectives of
sustainability and conducting a transparent management to the shareholders.

340 Gioacasi Diana / Procedia Economics and Finance 32 ( 2015 ) 338 – 344

Environment policy


Entity’s ability to implement effective policies for reducing the impact of its activities
on the environment.

Energy climate (EC) entity’s ability to develop effective policies and strategies to reduce energy
consumption and alternative environmental technologies


development (CD)

The involvement of local action entity in the form of charity, donations of goods and
services, public health protection activities and social impact management capacity of
production activity

Human rights (HR) Entity’s commitment to respect fundamental human rights, supporting freedom of
association and forced labor exclusion

Board (BD) Entity’s ability to comply with best practice on the management structure,
independently decision -making and the application of best practices regarding the

Source: Own structure after and Sveiby classification (1997)

3. Research methology

The scope of this article is to analyze the influence of time variation on nonfinancial factors in
correspondence with market value and book value by using repeated measurements.

3.1. Target sample and variables analyzed

The target population is represented by European multinationals which execute non-financial reporting based
on the Global Reporting Initiative requirements.

Table 2. Territorial and sectoral distribution of multinationals

Sectorial distribution % Territorial distribution %

Utilities 5,25 United kingdom 19,75

Telecommunications 10,75 Switzerland 7,25

Technology 7,00 Sweden 9,25

Industrials 14,50 Spain 6,00

Healthcare 9,50 Finland 4,50

Financials 14,25 Netherland 5,50

Energy 7,75 Italy 6,60

Consumer staples 7,50 Germany 12,25

Consumer discretionary 11,75 France 13,75

Basic materials 11,75 Other 15,15

In order to ensure comparability of financial and non-financial data the following conditions were imposed:

availability of data for the entire period under review and financial year to be completed on 31 December.
Based on the restrictions applied, it was selected a sample consisting of 400 European multinationals, including
1600 records for the 2009-2012 period.

341 Gioacasi Diana / Procedia Economics and Finance 32 ( 2015 ) 338 – 344

Sectorial distribution show multinationals concentration in industry, financial and basic materials, this
phenomenon being generated by homogeneous products and the existence of a large number of buyers and
sellers. In the opposite side, we find the sectors of utilities, energy and information technology which present a
small number of sellers, but with a high degree of innovation, specialized products and the use of advanced
technologies. The territorial distribution highlights the location of large corporations in industrialized countries
and supporters of research and development, such as the United Kingdom, France, Germany and Switzerland.

In order to achieve the objectives of the research were selected following variables: market value, book
value and non-financial factors presented in the table 1. Data regarding book value and market value were
taken from the financial statements of the multinational analyzed while non-financial factors were extracted
from the database and shows scores between 0 and 100.

3.2. Method

A repeated one–way ANOVA is testing the differences of mean scores for one dependent variable across

two or more within-group conditions of independent variabile (Mayers, 2013) The aplication of this method
requires the following restrictions: dependent variables must be reasonably normally distributed, every
individual must be present in all conditions, independent variable must be categorical, with at least two
conditions and it need to account for sphericity of within-group variances (Mayers, 2013).

Fisher statistics is being used to test significant differences for the dependent variables generated by
repeated measurements (Jaba, 2013). Total variation (SST) is partitioned into three components: variation
among individuals (SSI), variation among test occasions (SSO) and residual variation (SSRES) (Hinkle,
Wiersma & Jurs, 2003)

Table 3. Anova summary

Source SS df MS F

Individuals SSI n-1 SSI /(n-1)

Occasion SSO K-1 SSO/(K-1) MSo/MSRES

Residual SSRES (K-1)(n-1) SSRES/(K-1)(n-1)

Total SST N-1

Source: Hinkle, Wiersma and Jurs, 2003

Depending on the number of levels of within-subjects factor, it is necessary different interpretation of the

• If the within-subject factor has only two levels, a standard univariate F test is conducted for testing the

differences of mean scores.
• If the within-subject factor has more than two levels, we need to check for sphericity of variances. If this

assumption is violated, the p values associated with the standard within-subjects can not be trusted and we
need to use alternative univariate tests. These tests employ the same calculated F statistic, but its associated
p value potentially differs and an epsilon statistic is calculated based on the sample data to assess the degree
that the sphericity assumptions is violated (Howell, 2007)
Repeated measures ANOVA tests the hypotheses of differences between within-group conditions, but does

not determine which groups are different from the other. In order to identify groups showing significant
differences it is used multiple comparisons by using tests such as Bonferroni, LSD or Sidak.

342 Gioacasi Diana / Procedia Economics and Finance 32 ( 2015 ) 338 – 344

In this study, the statistical analysis was performed by 14 dependent variables and one independent variable.
In the detection of significant differences between groups we used the Bonferroni test and data processing
analysis was performed using SPSS 20.

4. Results

Analysis of non-financial factors based on repeated measurements is useful for making comparisons to the
entity in the same sector of activity or identify those inimitable resource that helps to create added value.

We chose Greenhouse-Geisser test for testing the differences of mean scores for each variable analyzed
because the assumption of sphericity variance was violated. Results of testing significant differences based on
repeated measurements are presented in Table 3. A repeated measures one way ANOVA indicated that there
was a significant difference of mean scores for all the variables analyses.

Table 4. ANOVA results

le df Mean Square F Sig. Variable df Mean Square F Sig.

CD 2.146 8968.304 188.139 .000 EC 1.910 5260.010 115.090 .000

HR 2.352 1160.373 26.049 .000 EP 2.260 2160.502 56.890 .000

PR 2.413 17091.091 493.583 .000 RM 2.037 9871.693 224.092 .000

CB 2.177 11415.874 276.734 .000 BR 1.885 7429.559 299.488 .000

DI 1.690 3822.808 42.341 .000 LE 2.054 6030.740 166.060 .000

TH 1.564 9500.217 73.489 .000 TR 1.998 2149.413 42.459 .000

MV 2.034 3388926666 46.083 .000 BV 1.700 171230314.82 6.244464 0.004

Repeated Measures ANOVA allows us to create a hierarchy of non-financial factors in order to identify

those resources with significant implications for creating added value. From this analysis, we can see that
European multinationals do not concentrate on developing a fruitful relationship with the local community
(community development) or on supporting policies to reduce energy consumption (energy climates) because
their attention is focused on the development of specific non-financial factors human capital. These results
confirm that human capital is an essential resource for value creation process as it is a constant source of
creativity and innovation.

Analysis of variance on repeated measurements shapes significantly reduced values of non-financial factors
in 2009 compared to other periods for all variables analyzed. These results are predictable due to management
focus on solving economic difficulties specific to the analyzed period.

In the next period is highlighted an improvement of the recorded values of variables analyzed, showing
interest in non-financial factors as creative resources and sustaining the competitive advantage

In 2010, a significant positive trend compared to the previous period is being observed for human rights,
community development and energy climates, but their failure to maintain on an upward trend suggests that
these values are purely accidental and these factors do not have a significant contribution for European

343 Gioacasi Diana / Procedia Economics and Finance 32 ( 2015 ) 338 – 344

Table 5. Descriptive statistics


2009 2010 2011 2012

Community development 44.96 234 53.86 134 52.66 124 51.85 123

Human rights & Supply chain 53.94 234 57.55 134 56.39 12 55.77 12

Product 43.64 234 53.27 134 56.64 124 55.20 124

Compensation& Benefits 47.65 234 56.05 134 56.99 12 57.07 12

Diversity 54.34 234 58.57 13 59.5212 58.59 13

Training 54.30 234 60.16 134 62.07 124 61.24 123

Energy climate 49.66 234 56.14 134 54.79 124 52.00 123

Environment policy 54.67 234 58.85 134 59.01 14 57.90 13

Resource management 48.71 234 56.26 134 58.18 124 54.83123

Board 51.28 234 54.15 134 57.45 124 58.90 123

Leadership ethics 52.50 234 57.06 134 59.50 12 59.12 12

Transparency &reporting 54.26 23 56.85 134 58.50 124 55.07 23

Market value ($millions) 25773.71 234 28575.93 134 22903.25 124 26984.33 13

Book Value ($ millions) 14578.41 23 13901.43 13424.53 14 14234.02 3

Note: Pairwise comparaison (Bonferroni test) 1-2009; 2-2010; 3-2011; 4-2012

Setting values recorded some non-financial factors from 2011 identifies those resources that help

create competitive advantages for European corporations. Based on this reasoning, we can say that non-
financial factors that contribute significantly to value creation are: the relationship with business partners
(human rights) policy on product quality (product), practices and policies for motivating employees,
(compensation and benefits) discrimination procedures employees (diversity), training (training) and practice
on organizational communication (leadership ethics).


In the new economy, the enterprise value maximization is the main concern of management. The positive
non-financial factors shown by repeated Measures ANOVA method confirm the impact of non-financial factors
on the creation of economic value and development of competitive advantages. The analysis results show that
European multinationals develop policies and strategies in the development of human capital, skills and
abilities of the employees being the most important non-financial resources in creating competitive advantages.


This work was cofinanced from the European Social Fund through Sectoral Operational Programme Human
Resources Development 2007-2013, project number POSDRU/159/1.5/S/142115 „Performance and excellence
in doctoral and postdoctoral research in Romanian economics science domain”.

344 Gioacasi Diana / Procedia Economics and Finance 32 ( 2015 ) 338 – 344


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*** Global Reporting Initiative, available at, accesed on 1 September 2014


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