René Pellissier

Assisted by Hester Nienaber, Nadine Lernhard, Filip Hamman and Zama Mkhize

Department of Business Management

University of South Africa

Pretoria , South Africa

Keywords: South Afric...

René Pellissier

Assisted by Hester Nienaber, Nadine Lernhard, Filip Hamman and Zama Mkhize

Department of Business Management

University of South Africa

Pretoria , South Africa

Keywords: South African management research practices, management journals, research problem, research design, research ontologies, content analysis

ABSTRACT
In the management sciences, there are different approaches to research.  These depend upon the specific research questions and objectives and their impact upon the findings.  At post graduate level, the supervisor and the student need to be au fait with the full spectrum of research strategies and be able to link the appropriate design to the specific research question and objectives. More than that, qualitative and quantitative methods are viewed as opposites rather than strategies on  continuum.  This limits the research and its value and allows for the predisposition of the supervisor to influence the student’s work. In the past, it was believed that certain specialisations/functional areas in the management sciences use specific research strategies rather than employ the full spectrum available. This paper provides an objective view of the research strategies employed by matching these strategies to the field of specialisation and to the planned outcomes from the research.

This article looks at the five accredited management journals in South African during the period 2006/2007 in order to determine the link between the research objectives and the research design employed. The journal articles were studied using proportional stratified random sampling, the research design and strategies and the conclusion.  A model as presented by Scandura and Williams (2000) was selected to use.  However the model was not sensitive enough with respect to the vast range of inaccuracies picked up by the review team.  The model was thus reworked using a content analysis approach in conjunction with theory building and modelling. The reworked research metric was then used to study a total of 120 of the 208 articles over the time period under review. The stratification allows for possible differences between the journals and trends thus developed. From these findings it seems that the current review process is not as strict as we believe and/or the reviewers are either not strict enough or not strong enough in all areas of research design and research methodologies in order to see the gaps in the articles. Also the formats of the review forms and the time constraints we face may influence the important function of the review process.  Despite these, accredited outputs play an important role in funding and academic promotions.  These aspects should be more intensely investigated and, to this, it is our aim to continue with this study and also to compare the local contribution to their international bedfellows. 

The value of the research on the research practices in the management sciences lies in its objective view of the strategies in use in the management journals of note and will thus enable the supervisor and the post graduate student to select the appropriate design from the broad range of possibilities rather than to stereotype method and specialisation. On a micro level, the research enhances research in the management sciences, whilst on the macro level; this adds value to the socio economic development of the country.


INTRODUCTION

This article researches research practices in the field of management in South Africa.  Management scientists and researchers are particularly guilty of research outputs in a domain that begs for expansion because of its relevance and value added to society. It is thus appropriate to investigate the publications accepted by South African (accredited) management journals and match these to the pertinent research problems/hypotheses/questions investigated by the researchers in the various fields in the management domain. Academic journal accreditation is undertaken by the Department of Education (DoE) and involves a rigorous process of review.  Accredited journals have to follow a strict blind peer review process linked to the specific house style and specialisation or focus of the journal.  Accepted articles are subsidised by the DoE based on an internal and external review system.

It is common knowledge that academics are not participating sufficiently in (accredited) research articles. There are many reasons for this phenomenon.  For instance, increasing administrative and academic workloads (based on student number increases and academic number decreases), a lack of research support and, most importantly, a lack of understanding of research fundamentals specifically in the field of management research.  (This is a focal point of this article.) However, these do not negate the demand for (subsidisable) research outputs.

In researching research practices in the field of management, this article will thus investigate the research problem, the research design, the research domain and the research outcomes and cross tabulate these with respect to their interdependencies. The following questions arise: Is it possible that a specific field in the management sciences relate to specific research design? Is it possible that the choice of technique could influence the outcome of the research?  To what extent is the current body literature in the management sciences informed by inappropriate research design and subsequent outcomes? Design choices may, to some extent, impact upon the conclusion drawn and it is thus of extreme importance that the appropriate design is perfectly matched to the research problem and the specific domain in which the research is undertaken.  One immediate benefit from this research is the identification of specific training and development that need to be undertaken to increase research outputs in terms of quality (research value to the body literature) and quantity (research value to the researcher and his/her affiliation). Another beneficial aspect is the development of a conceptual framework for matching research design against the research problem and the research field, and the subsequent deeper understanding of the positivist and phenomenologist designs.  To this end, an in-depth analysis of quantitative and qualitative strategies seems logical and the development of the conceptual framework should provide an understanding of the critical aspects involved in management research. 

Given the importance of management research in terms of the developmental aspects for society and theory, and the growing importance of publication for the sake of accredited outputs, the strategies and design techniques specifically relevant to the field of management theory and applications need to be investigated. Previous research (Scandura & Williams, 2007; Beaty, Nkomo & Kriek, 2006; Hitt, Beamish, Jackson & Mathieu, 2007; Matzler & Renzl, 2005) seemed to focus on limited aspects of management research whereas our preliminary research work indicated a lack of structure, lack of planning and logic and little linkage between the research problem, the research design and the research outcomes.  The Beaty, et al. research (2006) stresses the need for the building of management theory in the South African context, whereas generally formulations are still done in the US or Western Europe.  The sample under investigation was a selection of DoE accredited management journals between 1994 and 2004. Using an archival review technique, they used the Mendenhall, Beaty and Oddou (1993) classification consisting of qualitative, quantitative, conceptual or joint research. Their survey found that quantitative research designs were the most prevalent (54%) and joint research designs the least (3%). We were unsure whether their results followed from a random sample which would invalidate the Chi-Square results offered. Their research could not link the research problem, research domain, research levels or research outcomes.

This leads us to our research objectives:  The primary research objective is: To determine possible interdependencies between the research problem (in management research) and the research design and to develop a conceptual framework to review management research in terms of quality and value added to the body literature.  The secondary research objectives are to: Investigate the interdependencies between the research ontologies, strategies, levels, domains, analysis techniques and the purposes of the research.  The research employs a cross-sectional study of a randomly selected sample of the five accredited general management journals in South Africa over the period 2006/2007. The research follows on a previous study undertaken by Scandura and Williams (2007) in which they researched practices, trends and implications in research methodologies in management. The research will follow a content analysis approach used on a random sample of all articles published in the domain of management research in South Africa. Specific hypotheses can then be investigated based on these outcomes.

RESEARCH THEORIES

This article investigates the implementation of research fundamentals and we thus need to put research itself in context. There are numerous definitions for research. Kerlinger (1986:6) writes that (scientific) research is ‘the systematic, controlled, empirical, and critical investigation of natural phenomena guided by theory and hypotheses about the presumed relations among such phenomena. Leedy and Omrod (2005:19) concur: [scientific] ‘research is the systematic process of collecting and analysing information to increase our understanding of the phenomenon being studied.’ It is the function of the researcher to contribute to the understanding of the phenomenon and to communicate that understanding to others. Research is systematic (which implies the use of thorough and rigorous planning and procedures), controlled (which implies objectivity and consistency in the sense that results should be replicable by other researchers under the same conditions and in the same way), empirical (which implies that the research is grounded in reality), critical and analytical (which implies a probing process to identify problems and exacting methods to arrive at their solutions), logical (which implies arguments and conclusions that follow rationally from the evidence obtained) and theoretical and conceptual (which implies a grounding in conceptual and theoretical structures that direct the research). Our investigation will therefore have to explore the systematic process of research, review the critical and analytical aspects involved and the theoretical and conceptual aspects as well as the structures that direct the research in the management research conducted. In the planning phase, the research problem is matched to an appropriate research strategy that leads to a specific analysis framework and required outputs. These outputs are then assessed for quality and its contribution using rigorous peer review systems and happen through publication in accredited journals or some other formal review process. There are specific outcomes to be measured against. The broad aims of scientific research are typically accepted to be the understanding, explanation, prediction and control of natural phenomena.

Most research can be categorised as belonging to one of the following categories (Rosenthal and Rosnow, 1991:3): Pure research (leading to theoretical development whether there are practical output or not), applied research (intended to solve a specific problem and of which the common form is evaluation of a particular course of action) and action research (where the main focus is that the research itself must lead to change). Researchers in the social sciences use a continuum of ontological approaches to ensure viability and integrity of their work. These range from the purely quantitative and traditional approach to the qualitative interpretive approach depending on our perceptions of reality.  Pope and Mays (1995:42) provide another perspective: ‘[research is] an overstated dichotomy between quantitative and qualitative social science’, whilst Hussey and Hussey (1997) maintain that all research falls within a band of possibilities (positivist to phenomenologist) which will allow combinations form both on a continuum. 

According to Babbie and Mouton (2001), the research design relates to the planning of scientific inquiry -that is, designing a strategy for finding something out. This entails specifying ‘what’, ‘why’ and ‘how’ the researcher needs to find out. They differentiate research designs on the basis of (i) ‘empirical’ (e.g. survey, experiments, secondary data analysis, observation, case study) vs. ‘non-empirical’; (ii) primary data vs. secondary data; and (iii) numerical vs. textual data sources. Furthermore, they refer to the research paradigm that can be quantitative (gain understanding by explaining human behaviour) as opposed to qualitative (gain understanding by describing human behaviour). Their use of the term ‘research paradigm’ corresponds to that of Shah and Gorley (2006). Research methodology is defined as the methods, tools, techniques and procedures employed in the process of implementing the research design (Babbie & Mouton, 2001). Bryman and Bell (2007) are of the opinion that research designs refer to different frameworks, such as experiments, survey, cohort studies, case studies and comparative designs, used for collecting and analysing data. They use the term ‘research strategy’ to indicate a general orientation to conduct research, which can be either quantitative or qualitative in nature. Neuman (2006) uses the phrase ‘strategies for designing a study’ and points out that there are differences between a qualitative and quantitative style of doing research, which have different design issues that need to be considered. He further differentiates between the deductive and inductive reasoning approach to research, which aids in planning data collection and analysis.

RESEARCH DESIGN

The primary research design in this research is content analysis in order to determine the presence of certain words or concepts within the publications under review. Content analysis requires manageable categories (for instance, themes, sentences or phrases) to be examined.  The research is based on the categories presented by Scandura and Williams (2007).  In their study, Scandura and Williams compared the strategies employed in management research in two periods: 1995-97 and 1985-87. These authors used the following framework to review research methodology practices and trends in management research.

Table 1: Review framework for research methodology practices and trends in management research
Category
    Options
Primary research strategy    Quantitative, qualitative

Research strategies    Formal theories/literature reviews, sample surveys, laboratory experiments, experimental simulations, field studies (using primary/secondary data), field experiments, judgment tasks, computer simulations
Substantive content domains    Leadership, careers; international management; strategic management
policy/strategy,
organisation theory, organisational behaviour, HRM , research methods
Levels of analysis    Individual, group, organisational

Time frame of study (Internal validity)    Cross sectional, longitudinal
Economic sector from which sample drawn
(internal validity)    Private sector, non-governmental, public sector, governmental;
Non for profit, governmental & non governmental; Mixed; Not reported;
Student subjects
Occupation of subjects
(external validity)    Professional, Managerial, Manufacturing, Healthcare, Education, Blue collar, White collar, Technical, Students, Mixed
Nature of the construct validation (if any)
(construct validity)    Confirmatory factor analysis; Exploratory factor analysis; Discriminant analysis; Convergent/predictive validity; Convergent validity reports
    Nature of the construct validation (if any)
Other reliability measures (if any)
Primary data type    Qualitative; quantitative
Data source    Single; multiple
Primary data analysis    ANOVA (MANOVA, MANCOVA)
Linear regression analyses (Simple, multiple, hierarchical)
Correlation techniques
Meta analysis
Linear techniques for categorical dependent variables
Computer simulation (e.g. Monte Carlo simulation)
Source: Scandura and Williams (2007)

Hofstede (1996) posits that research traditions and publication patterns are mainly attributed to cultural differences and the nationality of the author.  He uses the example of what an organisation is to illustrate this point (in the French tradition it is ‘power’, in the German one it is ‘order’, in the American it is ‘the market; and in the Nordic countries it is ‘equality’). Matzler and Renzl (2005) concluded that German researchers focused more on theory development, publishing a very high number of purely conceptual articles, whereas the American approach is more empirical.  According to them, American and European researchers frequently collaborate on an international and national level.  Beaty, Nkomo and Kriek (2006) selected what they believed to be the six primary research outlets in management in South Africa (South African Journal of Business Management, South African Journal of Labour relations, South African Journal of Industrial Psychology, South African Journal of Management Science, Management Dynamics and the Southern African Business Review), selected because of their clear editorial focus in publishing South African management-related manuscripts. They pointed out that South African management research also appears in international journals whose primary focus is publishing research from non-South African populations. These authors studied the belief that qualitative research always precedes quantitative research in order for the subject field to mature. They focused their study mainly on the application of qualitative or quantitative research or both.  Their archival approach (1994-2004) reviewed all articles in these journals categorising them as qualitative, quantitative, conceptual or joint research.  They concluded that most management research followed quantitative approach, followed by a conceptual approach, then qualitative and then a joint approach.  They concluded their study using tests for independence which of course is not appropriate as there is not evidence of a random sample (in their design it seems that either the population as a whole was used or the sample taken from the population is purposive not random, both cases exclude any inference).  It was not clear how the design was constructed.  However, the tallies obtained do seem indicative of their conclusion. 

This research is based on the content analysis approach.  Berelson (1952) wrote that content analysis is the manual or automated coding of documents, transcripts, news articles, or even of audio of video media to obtain counts of words, phrases, or word-phrase clusters for purposes of statistical analysis. The researcher creates a ‘dictionary’ that clusters words and phrases into conceptual categories for purposes of counting. While generally focusing on the analysis of printed text and transcripts, DuRant et al. (1997) believe it applicable to any form of communication.  Berelson (1952) listed the main applications of content analysis: To describe trends in content over time, to describe the relative focus of attention for a set of topics, to compare international differences in content, to compare group differences in content, to compare individual differences in communication style, to trace conceptual development in intellectual history, to compare actual content with intended content, to name a few.  Krippendorf (2004) identifies five key processes inherent to content analysis: Unitizing: The researcher must establish the unit of analysis (word, meaning, sentence, paragraph, article, news clip, document, etc.). Sampling: usually the universe of interest is too large to study the content of all units of analysis, and instead units must be sampled. Sampling involves counting, which may require the researcher to develop thesauruses (so different terms with like meanings will be counted under the same construct) and expert systems or other rule engines (so the proper contextual valence is assigned to each counted construct). Reducing: content data must be reduced in complexity usually by employing conventional summary statistical measures. Coding and statistical analysis is covered by Hodson (1999). Inferring: contextual phenomena must be analyzed to provide the context for findings.  Narrating: conclusions in the content analytic tradition are usually communicated using narrative traditions and discursive conventions.

Brown (1969:21) wrote that content analysis is ‘at times, a scholarly discipline should examine itself.’ While Buboltz, Miller & Williams, 1999 and Hill, Nutt, & Jackson, 1994) believe that content analyses of journal articles provide an excellent avenue to review the state of affairs.  Content analysis as a review process can include the examination of the content of articles published in a journal across a specific time period (e.g. Buboltz et al., 1999; Nilsson et al., 2001; Pelsma & Cesari, 1989) or focuses on specific content areas, such as psychotherapy process (Hill, et al., 1994), school consultation (Alpert & Yammer, 1983), or racial/ethnic minority research (Perez, Constantine, & Gerard, 2000; Ponterotto, 1988).There are two broad types of content analyses: conceptual analysis and relational analysis. In the first, the existence and frequency of concepts (word or phrases) are established, whilst in the second, the relationships between the concepts are investigated.  The research design employed in this paper is summarised in the table below.

Table 2: Research design followed in this paper
Domain     Management sciences

Purpose    To establish the research dimensions of management research articles published in DoE accredited South African management journals and to determine whether  these articles comply with the requirements of being ‘scientific’
Epistemology    Phenomenological

Strategy     Theoretical/Conceptual

Sample     Proportional stratified random sampling

Analytical technique    Pilot study
Descriptive statistics
Chi-square tests for homogeneity
Multinomial logistic regression

Time frame    Cross sectional

Level    Organisational


Because journal articles tend to mirror the values and interests of authors, journal editors, and the field at large, content analyses offer insight into the values that drive scholarly activities during a certain period.  Nilsson, Love, Taylor and Slusher (2001) used content analysis to study the areas that received the most attention were academic/career, multicultural issues, symptoms/disorders, and counseling process in 1991 to 2001.  

RESEARCH METHOD

The research was undertaken in distinct phases. During the initiation phase, relevant literature was studied and the research introduced to the editors of the journals selected for the study. Thereafter the actual work took place in three stages (pilot study, redesign of framework and review of journals).

Initialisation
A team consisting of five researchers (reviewers) was formed to undertake the project. The five management research journals accredited by the DoE, were selected for the study. The research project was introduced to the editors of the selected management journals through a letter sent by electronic mail.  In a structured questionnaire, the editors were requested to provide information in terms of starting date, number of copies per year, number of copies published, number of submissions per issue, acceptance rate, reasons for non-acceptance, editorial policy, academic affiliation, cost per issue, price per issue, website address, ISSN number, scope of journal, date of accreditation, ratio of local to international content, and full text online. This initial phase allowed validation of the management journals in terms of accreditation, purpose and scope of journal and editorial policy (see Table 5).

Content analysis according to the identified themes (stages 1-3)
The project team conducted a thorough literature review into management research practices and the extant body theory.  The research population is taken as the total number of articles published in the five management journals during 2006/2007.  In the time period under investigation (2006/2007), there were a total number of 208 articles published.  The main thrust of the research was then undertaken in three progressive stages:  In stage one a pilot study was conducted using ten randomly selected articles from the research population. The sample results were used to make changes to the selected framework according to the diversity of the responses and the problems incurred with the framework limitations. In stage two, the Scandura and Williams (2007) framework was revised a according to the outcomes from the pilot study to the research framework that will follow all the stages of research.  This lead to the review framework for research practices in management publications in South Africa. In stage three, the four independent reviewers and the independent judge (acting as arbitrator), studied a random sample of 120 articles (using the five journals as strata), and reached agreement on the content analysis outcomes according to the proposed review framework. These stages will be discussed below.  All papers were read and marked independently according to the following scheme:
+     =    Did not say – we interpreted to be relevant
               =    Analytical technique not fit for sample
*     =    Domain not specified explicitly
              =       To be confirmed at meeting with arbiter
 √     =       Agreement at meeting with four reviewers
√ √     =       Agreed upon at meeting with arbiter.

Stage 1: A pilot study of ten articles randomly selected from the population was undertaken and reviewed using the Scandura and Williams framework and to assist the four independent reviewers to understand the framework and identify problem areas.  This sample size is small because of the time taken to review the original round of articles. The result of the pilot study was unexpected as we realised that in most of the articles, the purpose, method, sampling and analytical technique were in conflict. The following is a brief list of inaccuracies found that lead to the revision of the framework (see Tables 4a and 4b): Purpose not clearly stated (hence it is not clear whether the design and methodology were in accordance with the purpose), population not mentioned, sampling procedure and technique not specified, domain not specified (e.g. I.T; Marketing; HR etc), in minority of cases authors mention the time frame e.g. cross sectional survey, in a limited number of cases authors mention that the study is quantitative/qualitative, in a few cases we question the explicitly mentioned option as the ‘content’ does not correspond to the option, in a number of cases the authors indicate that the purpose is to test for relationships (as such probability sampling is required to do inferential statistics) and though they use non-probability sampling (such as purposive or convenience sampling) and, if they do not explicitly state, it is implied that they generalise their findings. Only one case highlighted that a convenience sample was used and non-parametric statistics, but the findings were not generalised since a non-probability sample was used, prohibiting generalizations, the titles of the articles and the content did not correspond, the title and hypotheses tested did not correspond, the analytical technique applied did not achieve the required outcomes and authors used populations but employed inferential statistics.

The implication of these observations was that, either these articles were flawed and as such unreliable and invalid, rendering their contributions void, or that the framework used was not appropriate to determine the trends and linkages. It soon became apparent that the selected framework did not allow for a clear and unambiguous problem statement, research objectives, the clarity of the research design or process followed, the sampling design as matched to the objectives and/or the analytical techniques employed, or the conclusions drawn. In some instances the panel agreed that the research findings and conclusions had little bearing on the preceding objectives, designs or analytical techniques used. The framework by Scandura and Williams was thus expanded to include a detailed methodology review and issues of validity and reliability.  This framework was revised through a number of iterations until the panel felt that the research framework was now identifying all the dimensions of good research identified through the literature study.  These dimensions were identified as: research strategy, research domain, and research level and research technique.

Stage 2: The population was stratified according to the five management journals under investigation.  The second phase used proportional random selection of the 208 articles spread over the five journals (strata).  This was done as the initial investigation showed differences in terms of house style, purpose and themes, numbers of articles, acceptance rate, price per copy and distribution. The stratification allowed for the differences between the journals and also achieves a higher level of significance for the same sample size if done without stratification. Proportional random sampling was used as numbers of articles differed between the journals (see Table 3). In the proportional allocation the percentage of articles selected per stratum remain the same although the numbers of articles may be different between journals (58% of the population).

Table 3: Proportional stratification sampling scheme
Number of accredited articles published in 2006/2007 per journal    JOURNAL 1    JOURNAL 2    JOURNAL 3    JOURNAL 4    JOURNAL 5    TOTALS
Total in journals (Ni)    32    35    14    46    81    208 (N = ∑Ni)
Total in sample (ni)    18    20    8    27    47    120 (n = ∑ni)
% selected per journal    56.3    57.1    57.1    58.7    58.0    57.7

The sample size of n=120 was chosen and proportional random allocation employed using a random number generator. The 120 articles were grouped into the five heterogeneous groups based on the size of the population.  Thus the sample sizes of n1=18, n2=20, n3=8, n4=27 and n5=47, correspond proportionally to the sizes of the subpopulations (N1=32, N2=35, N3=14, N4=46 and N5=81).  All over, the sampling used around 58% of the population elements after the population had been grouped into units that belong (i.e. the specifics of the research journal, its style and requirements). 

Stage 3: Four independent reviewers reviewed the 120 articles in the random sample according to the following scheme: each reviewer read seven articles per week (totalling 120 after 18 weeks), reached consensus every week. The group then presented findings (specifically disagreements) weekly to the fifth reviewer as arbiter for finality and agreement. In all cases, clear consensus was reached by the panel of five.  The selected articles were reviewed by the panel according to the amended framework as research framework. The research framework is presented in Tables 4a and 4b.  The outcomes of the agreed upon reviews were captured onto the data sheet summarised in Annexure A.

RESEARCH FRAMEWORK

Neuendorf (2002) listed the following as not acceptable issues in research publications:  inadequate methods or explanation of methods; limited or misused data; inadequate theory; inappropriate journal; presentation and style; unacknowledged bias (ideological, author dominance, selective data to fit a favoured theory); inadequate knowledge, limited analysis; inadequate discussion and dubious ethics.  Following on the definition and process of research (Leedy & Omrod, 2005), the categories of research (Rosenthal & Rosnow, 1991), the research design (Babbie & Mouton, 2001), the issue of research paradigm and research methods (Shah & Gorley, 2006; Babbie & Mouton, 2001; Bryman & Bell, 2007 and Neuman (2006), the review framework of Scandura & Willams (2007) was expanded to make provision for an unambiguous research framework that can incorporate all aspects of the research as identified by the reviewers in the pilot study, and not only the research methods alone as per Scandura (2007).  Some of the comments provided by the four reviewers on the nature of the analytical techniques were: ‘The authors made use of a ‘hedonic pricing model’, a technique used exclusively in Econometrics. The authors made use of ‘Seasonal unit root tests’, ‘Cointegration analysis’ and ‘Granger causality’, again techniques used in the subject of Econometrics. Therefore I thought we need to make provision for these ‘domain-specific’ techniques. Descriptive statistics is also used in the article, but it’s only to show averages, not for the purpose of coming to the main conclusion. It also has occurred in a lot of the other articles. Shouldn’t we distinguish between ‘purposeful’ techniques and ‘side-issue/additional/supportive’ techniques?’

All articles selected were reviewed by the panel according to the following research framework criterion list:


Table 4a: Research framework for review of management research articles
ELEMENTS IN MANAGEMENT RESEARCH    Mark the most appropriate with an X

1. Ontology   
a.    Positivism   
b.    Phenomenology   
c.    Both   
2. Research Strategy                       
a.    Sample survey/interview           
b.    Laboratory experiment                   
c.    Secondary data/literature review/archive   
d.    Observation study   
e.    Action research   
f.    Grounded theory               
g.    Experimental simulation               
h.    Experiment, field study   
i.    Grounded theory   
j.    Computer simulation       
3.  Research level
   
a.    Individual   
b.    Group/team       
c.    Organisation   
d.    Industry   
e.    Country   
f.    Geographic region   
4.  Research domain                           
AE =     Agricultural Economics           
AU =     Auditing                       
BE =     Business Education   
E =     Entrepreneurship/Innovation   
EC =     Economics   
Macro-economics   
Micro-economics   
EM =     Environmental Management   
FM =     Financial Management   
GBM = General Business Management   
HRM = Human Resource Management   
TC =    Telecommunications       
LM =     Logistics Management   
M =     Marketing   
PAM =     Public Administration and Management   
QM =     Quality Management   
R =    Research   
SBM =     Strategic Management   
TM=    Tourism Management (including ecotourism)   
TECH=    Technology (web-based; mobile; browser)   
5.  Analytical technique (see Table 4b)   
6.  Purpose of research   
a.    Descriptive research   
b.    Exploratory causal research   
7.  Time frame   
a.    Cross-sectional   
b.    Longitudinal    
c.    Triangulation   


Table 4b: Research framework for the review of analytical techniques

TYPE OF ANALYTICAL TECHNIQUE    SAMPLE    EXPLANATION AND/OR EXAMPLES
1. Comparison of means    Probability    E.g. ANOVA, ANCOVA, MANOVA, MANCOVA, T-tests.
2. Regression analysis    Probability    Any type of linear or logistic regression.
3. Correlation analysis    Probability    Any type of correlation.
4.  Nonparametric analysis    Probability /
Non-Probability    Any type of nonparametric statistical technique.
   Used in the case of small samples where no assumptions can be made  
   about the underlying distribution of the data
E.g. Sign test, Wilcoxon signed rank test, Wilcoxon rank sum test, Spearman’s rank correlation coefficient, Kolmogorov-Smirnov test, Mann-Whitney test, Kruskal-Wallis test, Friedman test.
5.  Descriptive statistics    Probability /
Non-Probability    Measures of location: Arithmetic mean, Geometric mean, Median, Mode, Quantiles.
Measures of spread: Range, Interquartile range, Quartile deviation, Standard deviation, Variance.
Measures of symmetry and kurtosis: Pearson coefficient of skewness,Filip Hammann Bowley’s coefficient of skewness, Coefficient of kurtosis.
Exploratory data analysis: Stem-and-leaf display, Box-and whisker plot.
6.  Analysis of contingency tables    Probability    E.g. Linear models, Log-linear analysis, Chi-Square independence test, Chi-Square goodness-of-fit test (large samples), McNemar’s test.
7. Factor-analytic and clustering techniques    Probability    E.g. Exploratory Factor Analysis (EFA), Principal Component Analysis (PCA), Cluster Analysis, Multidimensional Scaling, Discriminant Analysis, Correspondence Analysis.
8. Structural equation modelling (SEM) and path-analytic techniques    Probability    LISREL (Linear Structural Relationships), Path Analysis.
   Software package: AMOS
9. Time-dependent techniques    Probability    Techniques for analysing data at different points in time or over a   specified time period
E.g. Time-series analysis, Survival Analysis, Change-point Analysis, Sensitivity Analysis.
10. Computer simulation    Probability    E.g. Monte Carlo simulation, Linear programming.
11. Quality control techniques    Probability    E.g. Total Quality Management (TQM), Process Capability Analysis.
   Control charts: Run charts, Pareto charts, Attributes control charts, CUSUM charts.
12. Validity – and reliability tests a    Probability /
Non-Probability    Types of validity: Internal, External, Ecological, Population, Construct, Intentional, Representation, Content, Face, Observation, Criterion (Concurrent, Predictive), Convergent, Discriminant, Social, Nomological, Statistical conclusion validity.
Types of reliability: Inter-Rater/Inter-Observer, Test-Retest, Parallel-Forms, Internal Consistency.
Internal consistency measures: Cronbach's Alpha, Average Inter-item Correlation, Average Item-total Correlation, Split-Half Reliability.
13. Meta Analysis b    Probability    Meta-analysis is a statistical technique for summarising and reviewing previous quantitative research. Selected parts of the reported results of primary studies are entered into a database, and this "meta-data" is "meta-analyzed", in similar ways to working with other data by using descriptive and then inferential statistics to test certain hypotheses. The robustness of the main findings can be explored using sensitivity analysis.
E.g. Mantel Haenszel analysis, Peto analysis.
14.  Subject-related techniques    Probability/ Non-Probability    Techniques used exclusively in specific subjects
E.g. Boisot's I-space model in Knowledge Management, Logistics Cost Model (LCM) in Logistics Management, Johansen Multivariate Co-integration in Econometrics
15. Qualitative techniques    Probability/ Non-Probability    Techniques used in qualitative research
E.g. Content analysis, Matrix analysis, Conceptual framework
16.  Other inferential statistics    Probability    Techniques which do not fall under numbers 1 to 16 above
E.g. Confidence intervals, Estimation methods

RELIABILITY AND VALIDITY OF THE RESEARCH

The design of this research allowed for reliability of the results.  The four reviewers had to separately read the articles in the sample, complete the revised framework (see Tables 4a and 4b) and take the necessary steps to agree on the final resolution.  The coders re-examined any coding disagreement and arrived at a final consensus coding (100% agreement) which provided the data for this analysis. They met weekly with the arbitrator (reviewer five) to ensure overall consensus. Agreement was only achieved when all reviewers agreed.

The categories and items in our research framework were drawn from previous literature in management research and refine the Scandura and Williams’s framework. We did experience some problems with the large number of domain categories and the then small sample drawn that resulted in small cell frequencies.  The problem with too few coding categories is that it potentially increases the likelihood of random agreement in coding decisions and subsequently results in an overestimation of reliability (Milne and Adler, 1999). Similarly, higher numbers of items in the instrument increase the complexity (Beattie and Thomson, 2007) and may potentially increase coding variance. 

EMPIRICAL RESULTS

Table 5 summarises the results of the initial surveys sent to the editors of the journals to introduce the project.  In the instances where the editors did not provide information, these were extracted from the websites or from the hard copies of the journals provided. 

Table 5:  Initiation phase: Results of the surveys conducted with the editors
Name of Journal    Number copies/year    Number of copies published    Number of submissions/issue    Acceptance rate    Cost/issue
(ZAR)    Price/issue (ZAR)
Journal 1    4    20    4    0.275    15000    100
Journal 2                                                        4    800    6    .    14000    64
Journal 3    .    .    13    0.6    0    0
Journal 4    3    23    8    .    0    0
Journal 5                                                   4    500    11    0.6    20000    60

Tables 6 and 7 summarise the empirical findings in the sample encountered by the reviewers.

Table 6: General comments made by reviewers
ISSUE IDENTIFIED    FREQUENCY

Purpose not stated    26
No indication of primary research strategy (quantitative/qualitative)    37
No indication of sampling design    11
Contradictions with regards to non probability or probability sampling techniques    13
Inappropriate use of inferential techniques (for instance factor analysis)   
Invalid analytical technique used for chosen sampling method  (I added this but might have to be re-worded)    13
Incorrect research level (for instance indicate organisational but use industry or country setting)    Almost all the articles did not mention the level they used so we wrote what we thought was the correct level.
Unclear domain    13

The reviewers further observed that:
•    The domain was only specified in a number of cases while the readers had to interpret the remainder.
•    In 20 out of a possible 68 cases it was stated that the study was qualitative in nature, while the readers had to infer from the information provided that another 48 cases were qualitative in nature.
•    In 15 out of a possible 71 articles, the authors stated that the study was quantitative in nature, while the readers came to the conclusion that an additional 56 articles could have been quantitative in nature, given the information provided by the authors.
•    Only in one of the 120 cases the readers had to interpret the strategy, while the 119 other articles stated clearly the strategy (e.g. survey etc).
•    All authors clearly stated the analytical techniques used to analyse the data. These techniques were in line with the purpose of the study, but in a few cases these techniques were not appropriate to the sampling technique. This was especially applicable to research with a causal purpose that used a non-probability sampling technique.
•    None of the authors specified the level of the inquiry such as individual, organisation, industry or country. Readers had to infer this from the information provided.
•    Purpose not explicitly stated as exploratory, descriptive, causal or a combination.
•    Only 34 authors stated the time frame of the study as either cross sectional or longitudinal, while the readers had to infer in 86 cases based on the information provided in the article.
Furthermore, we found that sampling seemed the dimension that posed the major challenge.  This was especially true in cases where authors stated that the purpose of the study is causal. In 27 of the 44 articles with a causal purpose, the authors used a non-probability sample instead of a probability sample. The analytical techniques required to determine causality (e.g. comparison of means, regression analysis, correlation analysis, analysis of contingency tables, factor analysis and clustering techniques, structural equation modelling and path analytical techniques; time dependent analysis) required specific statistical assumptions that were neither stated nor adhered to (see Table 7).

Table 7: Dimensions of research encountered by the reviewers

JOURNAL    DOMAIN    QL    QN    STRATEGY    ANALYTICAL TECHNIQUE    LEVEL    PURPOSE    TIME FRAME    SAMPLE
    Unsure    48/68    56/71    1    0    120    60?unsure    86    28 (44)
1    18/18    10/11    9/11    1/18    0    18/18    13/18    15/18    7/18;7/9
2    13/21    8/15    1/8    0    0    20/21    0    7/21    6/21; 6/6
3    8/8    7/7    1/1    0    0    8    1    5/8    1/1
4    UNSURE 11/36    9/14    18/21    0    0    ?3    ?14/21    18/21    4/36; 4/8 causal
5    Unsure 13    18/21    27/30    0    0    ?    32    41/46    10; 10/20


We subsequently looked at the research dimensions favoured by the journals. Table 8 contains a host of information that needs further examination. Only the dimensions critical to the validity and reliability (i.e. purpose, nature, strategy, sample) of the research are addressed. Firstly, the purpose of any published research needs to be noted as the purpose is the pivot of any article.  Journals 1 and 5 favoured articles with a causal purpose, while journal 2 favoured articles with an exploratory purpose, journal 3 descriptive, and journal 4 published an equal number of articles with an exploratory, descriptive and causal purpose. The research design follows the research purpose.  According to the literature (see for example Cresswell (2003), Neuman (2006)) research with an exploratory and/or descriptive purpose is qualitative in nature, while research with a causal purpose is quantitative in nature. Journals 2 and 3 favoured research that is qualitative in nature, while journals 4 and 5 favoured research that is quantitative in nature. Journal 1 published equal number of quantitative/qualitative research. Given that Journals 1 and 5 favoured Causal research, there should be a general tendency towards probability sampling (which is then not the case).   

Table 8: Summary of research dimensions favoured by the DoE accredited management journals

Dimension    JOURNAL

    1    2    3    4    5
Domain    HRM/IOP/OD; Marketing    Spread    HRM/IOP/OD    HRM/IOP/OD    Eco
Approach    Equal qn/ql    qn    ql    qn    ql
Strategy    Survey or survey combined with other    Survey or survey combined with other    Conceptual    Survey or survey combined with other    Survey or survey combined with other
Analytical technique    Statistical
Inference?    Descriptive stats    Descriptive stats; Conceptual    Stats/inference    Statistical/inference
Level                   
Purpose    Causal    Exploratory    Descriptive    Combination    Causal
Time frame    CS    CS    CS    CS    CS
Sample    Non-probability    Non-probability    Not applicable    Non-probability    Non-probability
Qn = quantitative; ql = qualitative; CS = cross sectional



QUANTITATIVE DATA ANALYSIS
 The recorded findings were captured on a data sheets (Annexure A) and analysed using SPSS (Statistical Package for the Social Sciences), release 16.0.1.   The data were obtained through a stratified random sampling technique which allows us to do inferential statistics. 

Firstly, the Chi-square test for homogeneity was used to test whether the five journals differed with regard to each of the research variables (domain, qualitative/quantitative, strategy, analytical technique, level, purpose, timeframe and sample), on the 5% level of significance. A separate test was conducted for each variable in question. For all variables, except the timeframe of the study, some of the categories had to be merged to increase the expected cell frequencies (see annexure B). As a general rule, all expected frequencies should be at least five. But only eight articles were sampled from the Journal of Contemporary Management, causing very low observed (and expected cell) frequencies in the third column of the cross-tabulation tables. Therefore, to be more lenient, expected frequencies >2 were accepted. The expected cell frequencies < 2 are highlighted (see annexure B), in most cases this is only a very small percentage. Table 7 summarizes the results obtained for each of the eight research variables.

Table 9:  Summary of the results from the Chi-square test for homogeneity
RESEARCH VARIABLE    PEARSON
CHI-SQUARE
STATISTIC    P-VALUE    CONCLUSION
Domain    49.4519    2.802 × 10-5    The five journals differ with regard
to the research domain.
Qualitative/Quantitative    12.4586    0.1319    The five journals do not differ with regard
to whether the study is qualitative or
quantitative (QL/QN).
Strategy    17.9343    0.1177    The five journals do not differ with regard
to the research strategy.
Analytical technique    26.3317    0.7488    The five journals do not differ with regard
 to the analytical technique.
Level    25.2822    0.0135    The five journals differ with regard
to the research level.
Purpose    11.3151    0.5021    The five journals do not differ with regard
to the purpose of the research.
Timeframe    0.0131    1.0000    The five journals do not differ with regard
to the timeframe of the study.
Sample    13.5229    0.3322    The five journals do not differ with regard
to the sampling method used.

As can be seen from Table 9, it was found that the five journals showed homogeneity in terms of the research strategy, analytical technique, purpose of the study, timeframe of the study and the sampling method used. However, homogeneity between the five journals could not be confirmed in terms of the research domain and the research level.

Secondly, multinomial logistic regression was used to determine if one, or more, of the research variables are influenced by the other variables. That is, to identify potential response variables and its associated predictor variables, and then analysing the relationship between them.  As an initial intuitive guess, it was thought that the sample type could be influenced by the purpose of the study, the research strategy and whether the study is qualitative or quantitative in nature (QL/QN). Therefore, the sample type was identified as response variable with associated predictor variables being the purpose, strategy and QL/QN. The non-probability sample type was chosen as reference category, since it occurred the most.

The likelihood ratio test (Chi-square statistic = 51.085, p-value = 0.001) indicated that the framework is significant at the 5% level of significance, leading to rejection of the null hypothesis that all population regression coefficients, except the constant, are zero. Thus, at least one population regression coefficient is non-zero. The deviance goodness-of-fit test (Chi-square statistic = 95.953, p-value = 0.482) showed that the overall model fit is adequate. According to the likelihood ratio test for the individual model parameters, the research strategy (Chi-square statistic = 26.765, p-value = 0.002), as an independent variable, contributed significantly to the framework at the 5% level of significance. However, QL/QN (Chi-square statistic = 3.795, p-value = 0.704) did not make a significant impact, while the purpose of the study (Chi-square statistic = 15.958, p-value = 0.068) was found to be significant at the 10% level of significance.

Only three of the estimated regression coefficients were found to be significant at the 5% level of significance:  For the ‘population or N/A’ sample type, the ‘survey/interview’ (Wald statistic = 9.759, p-value = 0.002) and ‘mixed’ (Wald statistic = 4.342, p-value = 0.037) categories of the predictor variable ‘strategy’ and, for the ‘mixed/unsure’ sample type, the ‘survey/interview’ (Wald statistic = 3.928, p-value = 0.047) category of the predictor variable ‘strategy’.







Table 10: Parameter estimates as obtained from multinomial logistic regression

SAMPLE TYPE      PREDICTOR VARIABLE    CATEGORIES OF
PREDICTOR VARIABLE    ESTIMATED
REGRESSION
COEFFICIENT    ODDS RATIO    P-VALUE
Probability    Strategy
    Survey/Interview    -0.180    0.835    0.903
        Conceptual/Theory/
Grounded theory    -0.336    0.715    0.861
        Mixed    0.403    1.496    0.791
    QL/QN    Qualitative    -0.191    0.826    0.803
        Quantitative    0.166    1.180    0.813
    Purpose    Descriptive    0.175    1.191    0.898
        Exploratory    0.795    2.213    0.506
        Causal    1.905    6.717    0.113
Population or N/A    Strategy    Survey/Interview    -3.644    0.026    0.002
        Conceptual/Theory/
Grounded theory    -1.191    0.304    0.382
        Mixed    -2.463    0.085    0.037
    QL/QN    Qualitative    0.350    1.419    0.620
        Quantitative    0.039    1.040    0.959
    Purpose    Descriptive    -0.243    0.784    0.771
        Exploratory    -0.701    0.496    0.371
        Causal    -1.324    0.266    0.152
Mixed/Unsure    Strategy    Survey/Interview    -2.412    0.090    0.047
        Conceptual/Theory/
Grounded theory    -1.855    0.156    0.274
        Mixed    -1.661    0.190    0.185
    QL/QN    Qualitative    -0.319    0.727    0.697
        Quantitative    0.643    1.901    0.404
    Purpose    Descriptive    -0.604    0.546    0.532
        Exploratory    -0.520    0.595    0.542
        Causal    -0.977    0.376    0.305

From Table 10 it can b

Pellisier R paper for GMJ an exploration of research practices in ther management sciences.doc

Daniel F. Ofori

University of Ghana Business School

                 &

Evans Sokro

University of Ghana Business School

G...

Daniel F. Ofori

University of Ghana Business School

                 &

Evans Sokro

University of Ghana Business School

Ghana

Keywords: core values, value-driven culture, corporate performance, organizations, Ghana, vision and mission statement

Examining the Impact of Organisational Values on Corporate Performance in Selected Ghanaian Firms.
Abstract
Purpose: One of the hallmarks of leading-edge organisations is the strict adherence to their core values. Organisational values are seen as the constant passionate beliefs that drive the behaviour of its people. All organisations have values, whether formally articulated or not. The companies that are classified as high performers are assumed to have a strong value-driven culture and their core values guide the decisions and actions of organisational members. In light of the above, this study sought to identify the values espoused by selected Ghanaian organisations, how the values are lived out, and the factors that hinder firms in the process of living out their core values.
Methodology: This study uses a hybrid of quantitative and qualitative research methodologies. It used a cross-sectional survey technique as well as critical instance case study approach.
Findings: Ghanaian firms espoused values such as Focus on quality, Customer first, Team work, Being innovative, Flexibility, and Trust. In living their core values, firms often integrated these into their company’s vision and mission statement, communicated them to organisational members, and ensured that behaviours of members are value congruent. However, the study also found that employee attitudes, organisational communication gap, lack of motivation, and favouritism on the part of management are some of the factors that hinder firms as they desire to live out their core values.
Research limitations/implications: Only 7 organisations were selected from 4 sectors of the Ghanaian economy based on their willingness to take part in the study. Future research might expand the sample size to test and validate the findings of this study and also investigate the role of managerial values in the formulation of organisational values. Also, a study of this kind could consider only senior managers and middle level managers as respondents to avoid the tendency whereby other respondents like junior staff struggle to grasp the meaning of the concept or the topic of interest.
Originality/value: A maiden research work to identify the core values of Ghanaian firms and how these values are lived out. It will be of great interest to managers at all levels of the organisation, organisational members and other stakeholders who are interested in good returns to their investment.
Keywords: Core values, Corporate performance, Organisations, Ghana.
Paper type:  Research paper
Introduction and Problem Statement
The fundamental purposes of any business firm are to make profit, expand operations, and gain competitive advantage in the marketplace. In pursuance of these objectives, enterprise managers need to take certain actions in order to compete more effectively and meet the needs of stakeholders. As a result, managers over the last few years have been directing their attention towards cultivating core organisational values since these are the fundamentals of ethical standards on how to relate with employees, customers, vendors, and competitors. Aldag and Kuzuhara (2002) emphasise that the sharing of values is key to successful performance.

In the drive to achieve a competitive edge, much is being made of the central role of core cultural values in shaping organisational attitudes and employee behaviour. “Integrity”, “customer service”, “excellence”, and similar values have become the clichés of annual reports of shareholders around the world (Osborne, 1996). Core organisational values are a set of beliefs that specify universal expectations and preferred modes of behaviour in a company. They point the way to purposeful action and approved behaviour. They are important because a firm’s underlying values and beliefs define the organisation’s philosophy for achieving success. They reflect a person’s underlying beliefs of what should be or should not be. Values are often consciously articulated, both in conversation and in a company’s mission statement or annual reports (Debrah and Quick, 2006). These values serve as the fundamental laws and principles through which the organisation is governed. Simply put, values are powerful tools for directing behaviours and guidelines for decision making and policy implementation in any organisational setting. Businesses have shown increasing interest in values over recent years as a result of the significant role played by organisations’ values in influencing the overall performance of firms to the delight of the various stakeholders (Debra and Quick 2006). Hence, if organisations in Ghana are to realise their objectives and be successful, there is the need for them to consider their core values and how these values are lived out within the organisation.

Organisational values can work for an organization by creating an environment that is conducive to performance improvement and the management of change. It can work against the organisation by erecting barriers that prevent the attainment of goals. The impact of values can include conveying a sense of identity and unity of purpose to organisational members, facilitating the generation of commitment and shaping behaviour by providing guidance on what is expected. The values of an organisation may only be recognized at the top level, or shared so that the enterprise could be described as value-driven. Statements describing general principles may support them.

Bronwyn (2004) contends that organisational values are a lever for change, as they underpin the culture needed to enable organisations to achieve key goals. In other words, an organisation’s performance is greatly influenced by its cultural values. Therefore useful lessons can be learnt from studying the differences in the corporate performance of different firms within the same country as well as efforts to transform moribund organisations that do not either have core values to guide their operations or live out their espoused values. Puplampu (2004) found that core organisational values and how these values are lived out greatly shape the behaviour of organisational members, set the scene for performance standards and drive managerial thinking, leading to competitive edge and higher performance of firms. Barrett (2005) adds that, when organizations unite around a shared set of values, they become more flexible, less hierarchical, less bureaucratic, and develop an enhanced capacity for collective action.

Notwithstanding the importance of organisational values in the success of firms, very little work has been done in this area by both academics and practitioners in Ghana and other African countries. It appears also that, little work has been done on diving into the factors that hinder firms as they live out their espoused values. Perhaps, this is because, firms may have their espoused values, but whether these values are their enacted values or not is difficult to ascertain. In Ghana, there is anecdotal evidence that some firms are regarded as ‘leading’ in their fields, whilst others are regarded as the ‘best’ in their areas of operation. This can be seen in the plethora of awards organised by various industry associations like the Advertising Association of Ghana, the Ghana Banking Awards, the Transport Awards, etc. There are also nationally constituted awards like the Ghana Club 100 and the Millennium Awards, among others which seek to recognize company excellence. Some companies have become serial award winners based on the specific criteria set out by organizers.

The importance of the relationship between organisational values and corporate performance, coupled with the dearth of such information in the Ghanaian context has provided the impetus to undertake this study. It seeks to explore the phenomenon of the role of values on corporate performance within a developing country, specifically, in the African context.

 Objectives of the study
The general aim of the study is to investigate the impact of organisational values on corporate performance. The specific objectives are to:
•    Identify the core values espoused by Ghanaian organisations.
•    Evaluate how Ghanaian companies live out their espoused values. 
•    Examine the factors that impede the operationalisation of firms’ core values.
•    Find out if there is significant difference in organiational values and performance by type of ownership.

The Significance of the Study
This study, among other things, intends to bring to light the existing core values of Ghanaian firms and how these values are operationalised to the attainment of organisational goals. Secondly, it would serve as a vital instrument to analyse and examine the importance of organisational values on corporate performance in Ghanaian firms. It would also draw the attention of corporate managers to the need to create values for their respective organisations and also ensure that organisational members live by these values in order to enhance organisation success. Finally, it is also expected that the findings would assist managers of moribund organisations and institutions to revive and rejuvenate their organisations through the creation of core values which will guide the decisions and actions of organisational members, and act as a fillip for improved performance.






Literature Review
Organisational values are often embedded within the definitions of organisational culture, hence a review of organisational culture will be undertaken to discover the origins of organisational values (Cooke & Rosseau, 1998; Hofstede, Neuijen, Ohaju & Sanders, 1990). Part of the difficulty in understanding organisational values is due to its elusive nature. Culture permeates the entire organisation and provides its distinctive character. Most of the internal characteristics of an organisation evolve as a reflection of its culture and vice-versa (Goodman, Zammuto & Gifford, 2001).  A well-cited definition of organisational culture is “the enduring assumptions, values and beliefs that are shared by members of an organisation, that operate unconsciously, and that define in a basic ‘taken for granted fashion’ an organisation’s view of itself and its environment” (Schein, 1990). These beliefs and expectations serve as a normative order that influence how actors within the organisation perceive, think, feel and behave (O’Reilly, 1989). Corporate culture has been described as a pattern of shared values and beliefs that enable employees to understand the way an organisation functions, hence providing them with norms of behaviour in the firm (Deshpande and Webster, 1989). Organisational culture is the social glue that binds members of the organisation together through shared values, symbolic devices, and social ideals (Schein, 1990).

A common way by which organisational culture can be operationalised is through values (Chatman, 1989; O’Reilly et al., 1991). Interestingly, the concept of organisational values has no single and widely accepted definition. Indeed, it often appears that researchers feel compelled to coin their own definitions, which range from the very broad to highly specific ones to suit their work. For example values may be defined as enduring beliefs that a specific mode of conduct or end state of existence is personally or socially preferable to an opposite or converse mode of conduct or end state of existence (Debra and Quick, 2006). Values give us a sense of right and wrong, good and bad.

Values are the behaviours particularly valued in an organisation, the principles of the way things are done around here, underpinning the culture (Schein, 1994, cited in Bronwyn, 2004). According to Aldag and Kuzuhara (2002) organisational values are deep-seated, personal standards that influence our moral judgments, responses to others, and commitment to personal and organisational goals. Values let employees know how they are expected to behave and what actions are acceptable. For example, Procter & Gamble has core values of leadership, integrity, trust, passion for winning, and ownership, and it works to communicate these values and instill them in employees (Peters and Waterman, 1982). Collins and Porras (1994) note that core values are the organisation’s essential and enduring tenets: timeless, guiding principles requiring no external justification, with intrinsic value to the organisation’s members. Organisations decide for themselves what values they hold as core, without compromise. For example, some organisations hold values such as wholesomeness, happiness and imagination; others value excellence and respect for the individual. Other examples of values includes Team work, Co-operation, Customers first, Respect for others, Integrity, Being accountable, Being positive, Being open, Being innovative,  Focusing on quality and Trust. Values are held inviolable forever, regardless of what changes around us (Bronwyn, 2004).

Dolan and Garcia (2002) contend that values are not usually transmitted through formal written procedures. They are more often diffused by softer means, specifically: rituals, symbols, oral transmission of company legends and myths, company language code, communication, and rewards. McShane & Glinow (2003) say values are stable, long-lasting beliefs about what is important in a variety of situations. They are evaluative standards that help us define what is right or wrong, or good or bad, in the world. Values do not just represent what we want; they state what we ought to do – socially desirable ways to achieve those needs. Values dictate our priorities, our preferences and actions.

Notwithstanding the varied concepts on values, Dose (1997) states that, most value theorists agree that values are standards or criteria for choosing goals or guiding action, and are relatively stable over time, developing through the influences of culture, society and personality. For the purpose of this study, organisational values are viewed as the pivot around which organisational life revolves. They act as catalysts for managerial thinking and a navigator of employee behaviour. They are the guiding principles for conduct in organisations. It is the values that rule, but not the whims and caprices of management or individuals in the firm.


Organisational Values and Firm Performance
The external environment for organisations is changing (Child & Mc Grath, 2001).  This requires learning about how to collaborate, how to have more trusting and open communications, how to deal with dependency in relationships, how to gain commitment of subordinates, and how to design organisations with flexible boundaries (Schein, 1996).  Due to the increased uncertainty within the environment, especially from more discerning customers, firms are expected to produce an improved quality performance with a more professional, flexible and focused workforce. Values such as trust, creativity and honesty have become of equal importance than traditional economic concepts such as efficiency or return on investment (Dolan & Garcia, 2002).

All organisations have values, whether formally articulated or not.  The policies and practices of the company signal what is valued and important. However, as noted, by O’Reilly, Chatman and Caldwell (1991), what senior managers say they will do and what they actually do is often ambiguous and perhaps contradictory. Thus, regardless of what the mission statement or senior management espouses, employees will come to understand, through their own experience, how the company operates and what the company’s values are.

This means that espoused values are not always the values that are enacted. The values that are lived out in organisations are sometimes different from the desired values.  The living expression of current, real values in the organisation emanate from the encouragement of desired behaviour by different individuals and groups within the organisation hence organisational members tend to behave in acceptable ways. Peters and Waterman (1982) popularized the concept of the ‘strong culture’ characterised by employees sharing the espoused values of top management. The notion of shared values or value congruence is posited as central to the pursuit of corporate ‘excellence’, signifying the alignment of employees in the achievement of corporate goals. Therefore, the guiding aim of corporate ‘culturism’ (Willmott, 1993) is to ‘win the hearts and minds of employees’ or to define their purpose by managing what they think and feel not just how they behave. Shared values are regarded in the practitioner literature as fundamental to this idea of a strong unitary culture (Murphy & Mc Kenzie, 2002).

Attempts to explain the sustained superior financial performance of firms like IBM, Hewlett Packard and Proctor and Gamble have focused on managerial values and beliefs embodied in these firms’ organisational culture (Deal & Kennedy, 1982; Peters and Waterman, 1982; Tichy, 1983). Explanations suggest that firms with sustained superior performance typically are characterised by a strong set of core managerial values that define the ways the firms conduct business. When core values (about how to treat employees, customers and suppliers) that foster innovativeness and flexibility in firms are linked with management control, it leads to sustained superior financial performance (Barney, 1986). A firm’s values and how it promotes and publicises those values can also affect how workers feel about their jobs and themselves. A study of 180 managers looked at their employers’ effectiveness in communicating concern for employees’ welfare. Managers in organisations that consistently communicated concern for workers well-being and that focused on treating employees fairly reported feeling better about themselves and their role in the organisation (McAllister & Bigley, 2002). This implies that organisational values could significantly affect organisational performance.

Kaliprasad (2006) claims that the quest to becoming a high-performing organisation from an internal systems point of view, is simply a question of better understanding of people. From this, it could be said that if staff members do not buy into the visions, missions, shared values and actions of management, performance as well as the organisation as a whole is likely to suffer. Hyde and Williamson (2000) emphasis that clear organisational values can be a vital team motivator, the key to converting a humdrum business to an outstandingly successful one, and can make the difference between a hard grind project floundering in an atmosphere of distrust, and a smoothly run project delivered on time and on budget. Reid et al., (2001) contend that successful companies place a great deal of emphasis on organisational values.

Development of Hypotheses
Various researchers, including Loughling and Barlin (2001), have argued that our values, beliefs and attitudes significantly influence our behaviour.  It is therefore not surprising that Puplampu (2004) affirms that corporate values seem congruent with what organisations actually do, and this contributes significantly to organisational performance.  Consequently, firms tend to engage in activities that reflect, or are at least consistent with, their values (Ranson et al., 1980).  Thus a firm’s values may influence the behaviour of organisational members leading to superior performance.  Again, a survey of 1,498 American managers suggested that greater congruence between individual and organisational values can enhance personal fulfillments and organisational effectiveness (Posner, and Schmidt, 1992).

From Norburn et al’s (1990) perspective, a business is considered to possess a high level of marketing effectiveness if it has a close association with customers, is driven by a common set of values within the organisation and demonstrates an external orientation to its markets. In other studies, Dearlove and Coomber (1999) indicate that values-led companies outperform other companies.  For example, growth in revenue was four times faster; rate of job creation was seven times higher; growth in stock price was twelve times faster; and profit performance was 75% higher. Furthermore, another study, cited by Dearlove and Coomber (1999), found significant lower turnover among 1,000 US graduates when the employing company espoused values like respect and teamwork (Sullivan, Sullivan, and Buffton, 2002). In this context, it is posited that the formulation of corporate values and ensuring that these desired values are enacted are eventually the key to gaining a competitive edge.

Given the strong links which have been established between organisational values and corporate performance (Dearlove and Coomber 1999), we contend that organisations living their espoused values stand a greater possibility of chance achieving higher performance. The literature suggests that organisational performance is depended not only on the aims of the organisation, but also on the process for achieving such aims. Content and variables in a dynamic strategy need to be supported by the internal process and cohesion of the organisation. The relationship between internal drivers and organisational performance highlights the importance of values as an internal variable. Based on the foregoing discourse, it is meaningful to formulate these hypotheses:
•    The core values of organisations ensure the achievement of higher performance.
•    In successful organisations, managerial behaviour is consistent with espoused values.
•    In successful organisations, employee behaviour is consistent with espoused values.



Theoretical Framework
The theoretical framework of this study is derived from the works of Collins and Porras (1994) and the European Foundation for Quality Management Excellence Model (2000). Collins and Porras (1994) use convincing examples of values derived from the personal convictions of Robert W. Johnson Junior (Johnson & Johnson); George Merck II (Merck); Thomas J. Watson Junior (IBM); and David Packard and Bob Hewlett (Hewlett-Packard) – all founders or leaders at one time or another of their respective companies. These values include team work, co-operation, customer first, respect for others, integrity, being accountable, being positive, being open, being innovative, focusing on quality, and trust. The values are considered as an organisational legacy, whereby generations of leaders preside over the values; inheriting the company’s values from their predecessor, acting as custodians and stewards throughout their period of tenure, and passing them onto their successor.

In identifying the core values of Ghanaian firms, a list of the values mentioned above were provided. The respondents were asked to rank these values by numbering from 1 – 6 depending on how important these values are to their respective organisations.

In addition, the “European Foundation for Quality Management” (EFQM) Excellence model (2000) was used to measure the performance of the organisations studied. The EFQM Excellence Model (2000) provides a holistic way of ensuring long-term success. The model is a diagnostic tool for self-assessment of the current health of an organisation – through self-assessment the organisation is better able to balance its priorities, allocate resources and generate realistic business plans (Neely, 1998; Oakland, 1999). Private sector organisations have been more successful with the EFQM model than the public sector organisations (Pupius and Brusoni, 2000).



 


Research Methodology
This study uses a hybrid of quantitative and qualitative research methodologies and analysis. Harrigan (1983) note that hybrid methodologies are characterised by multiple data sources, and that such studies need a carefully structured sample design.  This confirms to Patton’s (1988) claim for a post-positivist view of research. The post-positivist approach is about using the approach which the researcher deems most appropriate for his/her study, each method being adopted at the appropriate stage of the study.

The case study is one of several ways of doing social science research. Flyvbjerg (2006) argues that, rather than using large samples and following rigid protocol to examine a limited number of variables, case study methods involve an in-depth, longitudinal examination of a single instance or event: a case. They provide a systematic way of looking at events, collecting data, analysing information, and reporting results. As a result, the researcher sharpened his/her understanding of why the instance happened as it did, and what might become important to look at more extensively in future research. Case studies lend themselves to both generating and testing hypotheses.

Yin (2002) also suggests that case study should be defined as a research strategy, an empirical inquiry that investigates a phenomenon within its real-life context. Case study research means single and multiple case studies, can include quantitative evidence, relies on multiple sources of evidence and benefits from the prior development of theoretical prepositions. He notes that case studies should not be confused with qualitative research, and points out that they can be based on any mix of quantitative and qualitative evidence. Lamnek (2005) further adds that the case study is a research approach, situated between concrete data taking techniques and methodological paradigms.   The study was therefore conducted using critical instance case study method. Besides, it also used elements of the cross-sectional survey approach. Cross-sectional research involves the measurement of all variable(s) for all cases within a narrow time span so that the measurements may be viewed as contemporaneous. Essentially, data are collected at only one point in time (Creswell, 1998). In cross-sectional studies, variables of interest in a sample of subjects are assayed once and the relationships between them are determined.
Population
There are many organisations operating in Ghana which are all considered ideal for this study. Hence the population of the study is Ghanaian firms: whether public, private or joint. Initially, the researchers intended to use the organisations listed in the Ghana Club 100 (GC100) so as to compare their performances based on their positions in the GC100 ranking. However, some of the organisations randomly selected at first declined to participate in the study. Hence, the researchers were compelled to purposively select 7 organisations from four sectors based on their willingness to participate in the study.  The sectors include Manufacturing (Phyto Riker Pharmaceuticals and Kasapreko), Financial (uniBank, Vanguard Assurance, and Internal Revenue Service), Telecommunication (Ghana Telecom, now Vodafone), and General Services (Jospong Printing Press). 

Sampling
The sample for the study consisted of senior managers, line managers, supervisors and the workforce. The simple random selection procedure was adopted in selecting organizational members to respond to the questionnaire. However, this procedure was not applied in the selection of the human resource managers and the administrative managers included in the study. They were purposively selected based on their job description in the various organisations since they play a vital role in the day to day administration of the firm; being responsible for the creation and improvement of organizational culture and values, and also ensuring that the organisation achieves its vision. In all, 122 (85.7%) respondents out of a total number of 140 responded to the questionnaire from the 7 firms in which the study was carried out. A total number of 14 senior management staff, 64 middle level managers, and 44 junior staff responded to the questionnaire.

Procedure
The study required a thorough review of literature to address the relationship between the variables of interest and to provide a context relevant setting for the study. For the determination of core values of Ghanaian firms, the researchers sought for company hand books, brochures, and company profiles.  In addition, other research instruments like questionnaire and personal interviews were relied upon.

Data Collection
The researchers conducted personal interviews for 2 senior managers in each of the organisations studied. The questionnaire on the other hand, was employed for the rest of the respondents because, it effectively eliminates interviewer biases and controls for inhibitions people usually have in talking openly about issues of great concern in their organisations. This instrument consisted of both open-ended and structured items, and was divided into six sections. Data was collected between January and March 2008.

Method of Data Analysis
The study used some aspects of the grounded theory approach (Glaser and Strauss, 1967) to analyse the qualitative data, and for the quantitative data, the non-parametric techniques; Pearson’s product coefficient of correlation and One-way ANOVA were used. In addition, some qualitative responses are presented verbatim in this report. 

Discussion of Empirical Findings
The One Way ANOVA technique was used to determine significant statistical differences in the performance of the organisations studied based on the nature of their operations. The Pearson product moment coefficient of correlation was also used to determine the relationship between the following: (a) organisational values and the overall performance of firms, (b) managerial behaviour and organisational values, and (c) employee behaviour and organisational values. The analysis of data however has not been wholly customized to the individual respondent organisations. Efforts have rather been made to determine the significance and the generality of the results across the organisations covered.

Identification of Core Values
The study showed every organisation has its own set of values depending on the nature of business of the firm as shown in the Table 1 below:
Table 1 Identification of firm’s core values

CORE VALUES    SECTORS
    MANUFACTURING    TELE-
COMMUNICATION    GENERAL
SERVICES    FINANCIAL
Sound people management   
-   
*   
-   
-
Integrity    -    -    -    *
Caring for customers    -    -    -    *
Focus on quality     *    -    *    -
Sensitivity to customers   
-   
*   
-   
-
Flexibility    -    -    -    *
Being innovative     *    *    *    *
Team work     -    -    -    *
Customer First     *    -    *    -
Efficiency     -    *    -    *
Fairness     -    -    -    *

An identification of firm’s core values revealed that the manufacturing companies and those that are in the general services category adhere to values such as focus on quality, customer first, and being innovative. The core values of the telecommunications industry include; efficiency, sensitivity to customers, being innovative and sound people management. The financial institutions on the other hand hold on to the following values; caring for customers, being innovative, teamwork, flexibility, integrity, efficiency, and fairness.

Although two of the values, ‘customer first’ and ‘being innovative’ are dominant in the four sectors studied, it was also found that the values differ with respect to the nature of business of the firm. This goes to strengthen the findings of Collins and Porras (1994) who note that core values are organisations’ essential and enduring tenets: timeless, guiding principles requiring no external justification, with intrinsic value to the organisation’s members. Organisations decide for themselves what values they hold as core, without compromise. Bronwyn (2004) adds that values are held inviolable forever, regardless of what changes around us.

Efforts were also made to rank the personal values of the respondents. In order to determine the ranking of the values of the respondents, a weighted average of the responses were determined. The values were ranked in six (6) levels and the accompanied weights were as follows starting from the highest 0.29, 0.24, 0.19, 0.14, 0.10, and 0.05. The results indicate that, the weighted average score for ‘Focus on quality’ is 0.24, ‘Customer first’ 0.20, ‘Trust’ and ‘Respect for others’ obtained the same score of 0.17, ‘Teamwork’ 0.16, ‘Integrity’ 0.15, ‘Being innovative’ 0.14, ‘Being open’ and ‘Co-operation’ 0.13, ‘Fairness’ and ‘Being accountable’ 0.11, and ‘Politeness’ 0.10. This means, the dominant personal values of the respondents includes; Focus on quality, Customer first, Trust, Respect for others, Teamwork, and Integrity.
 
Comparing the personal values of respondents with the existing values of the organisations, it is quite clear that the organisational values are not radically different from the personal values of the organisational members. This finding is important since it has a bearing on whether the values of the firm can be lived out or not. This is because, it reinforces Debra and Quick’s (2006) suggestion that employees are exposed to multiple value systems: their own, their supervisor’s, the company’s, the customers’ and others’. In most cases, the individual’s greatest allegiance will be to personal values. When the value system conflicts with the behaviour the person feels must be exhibited the person experiences a value conflict.

Besides, McShane and Glinow (2003) say individuals bring personal values into the organisations which are formed from past experience and interaction with others. Similarly, Weber (1993) maintains that every individual brings a set of personal beliefs and values into the workplace. Personal values and moral reasoning that translates these values into behaviour are important aspects of ethical decision making in organisations. Hence, for organisational members to live out the espoused values of their respective firms, there is the need for value congruence and this will be a source of intrinsic motivation to them.  As emphasised by Begley (2000); McCune (1999); and Fenwick (1999), values foster a common bond and help ensure that organisational members pull in the same direction – irrespective of their individual tasks and ranks. The factors that hinder the operationalisation of a firm’s values as identified include; Individual differences, Employee attitude, Communication gap, Lack of motivation and favouritism.

Hypotheses Explored
Three hypotheses underlie the empirical investigations in this research. The three hypotheses have been tested by the use of Pearson’s product moment coefficient of correlation to determine whether there exists a positive and significant relationship between organisational values and organisational performance. The same correlation was used to test the relationships that exist between managerial behaviour, employee behaviour, and organisational values. These are presented in Table 2 below.

Table 2   Pearson’s Correlation Coefficients Indicators of Organizational Values
 Table availiable in printed version



Hypothesis 1: The core values of organisations ensure the achievement of higher performance.
The results in Table 1   show a correlation coefficient of r = 0.397 for the relationship between core values and performance. The relationship was found to be significant since p < 0.05. This means that there exists a positive and significant relationship between core values and performance. Thus, when core values are emphasized organizational performance increases.  Therefore, at 95% significance level the hypothesis that the core values of firms ensure the achievement of higher performance was supported. This supports Barret’s (2005) work in which he notes that when employees not only share the same core values but also share the same vision, the performance of a company is significantly enhanced. This is because, shared values build trust, and trust is the glue that enhances performance.

Similarly, Reid et al. (2001) have emphasised that successful companies place a great deal of emphasis on organisational values. Since they have a clear and explicit philosophy about how they intend to conduct their business, they also ensure that management pays serious attention to the organisational values themselves, as well as integrating them into the company’s way of doing business.
 
It is reasonable to point out that among the organisations studied, uniBank has the highest association between core values and corporate performance. This might perhaps be the reason for the outstanding performance of uniBank, taking into consideration the numerous awards the company has won from Corporate Initiative Ghana in the Ghana Banking Award ceremonies. For instance, for the Ghana Banking Awards 2006, uniBank won the following awards; Best Bank, Customer Care, Best Bank, Corporate Banking, Best Growing Bank and Third Best Bank, Advisory Services (Daily Graphic, Tuesday May 29, 2007).

Besides, interviews with the Top Management at Kasapreko Company Limited revealed that the company has competitive edge over others in their sector of operation, since it holds on to its core values of satisfying the needs and taste of  customers, and also being innovative in its product design. This was evidenced in the company’s position with reference to the Ghana Club100 ranking. For example, in 2004 Kasapreko was the 2nd most profitable (Return on Equity) company in Ghana, and in 2005 it was the Third Best Manufacturing Company. 

In the light of the above observations, it can be argued that firms that have their values integrated in the company’s culture have the tendency to inspire organisational members into action and ensure the achievement of the future goals of the firm. These values are what drive the thinking of organisational members and determine the behaviours that ought to be rewarded and those that must be eschewed.

Hypothesis 2: In successful organisations, managerial behaviour is consistent with espoused values.
The correlation results indicate that managerial behaviour is greatly influenced by core organisational values. In other words, management holds on to the core values of the firm. A positive and significant high correlation coefficient that is r = 0.885 (p < 0.05) was recorded for the relationship between managerial behaviour and core values. Thus very high managerial behaviours match with core values.  Therefore, at the 95% significance level, the hypothesis that ‘in successful organisations, managerial behaviour is consistent with espoused values’ was supported.

The acceptance of hypothesis 2 is also in line with Barret’s (2005) assertion that, values influence overall behaviour and they inspire people into action. They drive the things we seek to accomplish and describe the things we will not do, the behaviours we reward and those we condemn. He also stressed that, values are the anchors we use to make decisions so we can weather a storm. They keep us aligned with our authentic self. They keep us true to ourselves and the future we want to experience. He went on with his argument that, for an organisation to reap the benefits of a strong set of shared values, the values must be lived by the senior people in the organisation. 

Daft (2001) also suggests that values-based leaders engender a high level of trust and respect from employees, based not only on their stated values but also on courage, determination, and self-sacrifice they demonstrate in upholding those values. In all organisations studied, managerial behaviour is found to be highly associated with organisational values. For example at Ghana Telecom, core values are 94.7% associated with managerial behaviour, 93.6% association was found at Internal Revenue Service, 89.4% at Jospong Printing Press, and 88.9% at Phyto Riker Pharmaceutical. At uniBank, the association between core values and managerial behaviour is 83.5% whilst at Vanguard Assurance, the observed association is 87.2%.

The results further indicate that there is overwhelming support for the view that managerial behaviour must be consistent with core values of organisations if they are to achieve higher performance. This suggests that Ghanaian managers strictly hold on to their organisational values as they argue that it is the core values that dominate their decisions and actions as well as the strategic direction of their respective companies. The researchers are however, inclined to think that managers are well informed about the concept of organisational values and are therefore careful in their responses during the data gathering. For example all the managers interviewed fully agree to the statement that “Leaders in the company are willing to make personal sacrifices for the sake of values”, no manager disagrees with this statement.

Hypothesis 3: In successful organisations, employee behaviour is consistent with organisational values.
The results as shown in Person’s Correlation Coefficient in Table 1 indicate that, employee behaviour was found to be consistent with organisational values. The relationship between employee behaviour and core values was positive and significant (r = .697, p<0.05). Thus, positive employee behaviour corresponded with emphasis on organizational values. Therefore at 0.05 level, the hypothesis that ‘in successful organisations employee behaviour is consistent with organisational values’ is confirmed.

Analysis of Variance (ANOVA)
The One-Way ANOVA was used to test for significant differences, if any between the private, public and joint businesses with respect to the organizational values and performance. The results presented in Table 3 show how the different types of organizations scored on the various organizational values and performance measures.


Organizational Values    Type of Ownership    N    Mean    Standard Deviation
Core Values



    Private
Public
Joint
Total
    54
28
38
120    41.44
39.07
39.53
40.28
    6.94
6.09
7.31
6.90
Employee Behaviour


    Private
Public
Joint
Total    54
28
38
120    7.11
6.71
7.37
7.10    2.01
1.90
1.48
1.83
Managerial Behaviour


    Private
Public
Joint
Total    54
28
38
120    16.56
16.00
15.53
16.10    3.69
4.27
4.05
3.94
Performance


    Private
Public
Joint
Total    54
28
38
120    53.44
51.07
47.95
51.15    10.72
9.58
9.57
10.30

Table 3   Mean and Standard Deviation of Indicators of Organizational Values by Type of Ownership

In Table 3 the mean score on core values was 41.44 for private business, 39.53 for joint businesses and 39.07 for public businesses. Thus private businesses emphasized more on core values than joint and public businesses. For Employee behaviour, the joint businesses (7.37) scored highest, followed by private businesses (7.11) and public institutions (6.71) in that order.  Managerial behaviour was found to be highest among private businesses (16.56) with public institutions (16.00) and joint businesses (15.53) in 2nd and 3rd positions respectively. On performance, private businesses scored highest (53.44), followed by public institutions (51.07) and joint businesses scoring the least (47.95).
Using the One-Way ANOVA to test for the significant differences in the organizational values and performance of the different organizations, the result in Table 4 was obtained.

Table avaliable in printed version

It can be observed that the mean scores on core values obtained by the three different organizations were almost equal, since F = 1.436 df = 2, 117 and p>0.05. This means that the differences in the mean scores on core values obtained by the three different organizations were not significantly different. Therefore at 95% significance level, there were no significant differences in the scores on core values obtained by the three different organizations. On employee behaviour, the mean score obtained by private organizations was highest, followed by joint organizations and then public organizations. However, the differences between their mean score did not differ significantly ( F (2,117) = 1.032, and p>0.05 ). Thus, at 95% significance level, employee behaviour did not differ significantly among the three different organizations. 

The results in Table 4 also show no significant differences in managerial behaviour in the three different organizations ( F (2,117) = 0.772, and p>0.05 ). Thus, even though the mean scores on managerial behaviour obtained by the private organizations was slightly higher than the public and joint organizations, the differences in the scores were not significant. Therefore, at the 0.05 level, the managers in the three organizations displayed almost equal positive behaviours.

The one-way ANOVA results in Table 4 reveal significant differences in organizational performance of the three different organizations ( F (2,117) = 3.300, and p< 0.05 ). The mean scores in Table 4 clearly shows that the private organizations performed better, followed by the public organizations and the joint organizations in that order. Following from the results of ANOVA in Table 4, multiple comparison based on the mean scores was carried out to determine which two organizations differed significantly in their performance. The results are shown in Table 5.



  * The mean difference is significant at the .05 level
Since there was a significant difference in the performance of the three different organizations, post-hoc or multiple comparison test was carried out to determine which two organizations differ in performance. The results indicate that private and public owned companies do not vary in terms of performance p > 0.05. The same result was observed for joint and public businesses. However, the comparison of joint and private owned businesses shows a significant difference in terms of performance. The private organizations performed better than the joint organizations.

Conclusions
Organisational values can facilitate or hinder an organisation’s overall performance.  Comber (1999) indicated that values-led companies outperform other companies.  For example, growth in revenue was four times faster; rate of job creation was seven times higher; growth in stock price was twelve times faster and profit performance was 75% higher.  Kono (1990) has emphasised the point that the culture of a successful firm must be appropriate to, and supportive of that firm’s strategy and that the culture must enshrine values which can help the firm to adapt to environmental change.  When firms are able to swiftly and quickly adapt to changes in their internal and external environment, their performances are greatly enhanced.

The organisations studied are all indigenous Ghanaian firms which are either private, public or jointly owned and their existence have yielded societal dividends in the form of taxes and its administration, employment and economic stability.  All the seven organisations studied espoused certain core values which are either clearly stated and documented or integrated in the vision and mission statement of the organisation.  Some of the organisations have managed to derive the full benefits of the values they espoused which reflected in their performances and this is evidenced in the awards these organisations have received over the years from Ghana Club 100 and Corporate Initiative Ghana as the case of uniBank, Vanguard Assurance and Kasapreko Company limited indicate. 

Recommendations and Suggestions for Future Investigation
Organisations need to articulate and unite around a common set of values which make clear that practices that are responsible are also strategically sound. This is because, the core values of an organisation determines the kind of activity an organisation engages itself in. Firms that have not united around a common set of shared values will struggle over what standards should guide the decisions and actions of its members towards the attainment of the goals and the strategic intent of the organisation.

Second, management should be committed to the agreed values; the values should be demonstrated in their decisions and actions.   Leaders of the organisation should not pay lip service to the values of the firm instead their behaviour should be value congruence.  This is leadership by example and this will encourage employees to also live the values.

Third, management must endeavour to have the core values well documented in the company’s profile, brochures, on the walls of the various offices, conference room, training rooms, and canteen and staff common room in the organisation. It is not enough having the values.  They must be publicised and made known to all the rank and files of the members in the organisation otherwise these espoused values will only remain in the minds of top management alone, and how can the employees hold on to something they are not aware of.   Beside, the values must also be communicated sufficiently to all stakeholders.

Fourth, performance systems must be properly established and an individual whose behaviour is constantly consistent with the values the organisation espouses should be rewarded.  When this is done, the conformists will be motivated to always live the values whilst the non-conformists will be discouraged from the adoption of apathetic attitudes towards the living of the core values. It must be emphasised that rewards, promotions, salary increases and other incentives be based on the performance of the organisational members.

Rigorous research should be conducted into the role of managerial values in the formulation of organisational values. This is because organisational members have their own personal values and in the formulation of organisational values, whose values must be integrated? Finally, a study of this kind could consider only senior managers and middle level managers as respondents to avoid the tendency whereby other respondents like junior staff struggle to grasp the meaning of the concept or the topic of interest.












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Wojciech Nasierowski

Academy of Management(SWSPiZ)

Łódź , Poland

              and

Faculty of Business Administration

University of ...

Wojciech Nasierowski

Academy of Management(SWSPiZ)

Łódź , Poland

              and

Faculty of Business Administration

University of New Brunswick

Fredericton , Canada

Keywords: composite index, innovation, National Innovation System (NIS), European Innovation Scoreboard (EIS), innovation measurement standard, pro-innovative  policies

INTRODUCTION.  WHY ARE INNOVATIONS ESSENTIAL?


Issues related to the enhancement of innovativeness are of pivotal importance when attempting to increase the competitive advantage of enterprises and their distinctive competencies, thus fostering economic efficiency and growth of countries.  Numerous studies (e.g. , [40], [14]) highlight the importance of innovation for economic development and well-being.  The ability of governments, businesses, and individuals to identify, respond to, and most importantly, introduce change, as the bedrock of competitive ability (e.g., [34], [5], [37]).   At a microeconomic level, a practitioner’s viewpoint prevails.  Continuous improvement in technology and business processes are recognized as being vital to economic prosperity, thereby providing a strong incentive to invest in innovation [9, pp.133-140], [19, p.16].  Yet, it still remains unclear whether countries are innovative because they are rich, or rich because they are innovative.  Examination of the National Innovation System (NIS) can be regarded as a starting point to the discussion of innovativeness.  It is widely accepted that results of studies dealing with innovativeness, and in particular with efficiency of pro-innovative programs and NIS, are critical to the formulation of improvement initiatives.  Such endeavours gain even more attention because of globalization, and in particular, the unification of the European Union (EU). 

This paper is organized into the following parts.  First, the role of National Innovation Systems is described along with the limitations of this idea stemming mainly from imprecision of definitions.  Next, constraints imposed by indicators of innovativeness that form composite indexes, and questions regarding methodology of forming them such indexes, are outlined.  Objections regarding the European Innovation Scoreboard are mentioned.  The next section is devoted to suggestions for studies relative to assessment of technical efficiency of innovation systems.  In the last part a summary of the paper is provided.  


NATIONAL INNOVATION SYSTEM (NIS): A MEANS TO ORGANIZE, STIMULATE AND CONTROL PRO-INNOVATIVE ACTIVITIES.


NIS and its Discussion Themes

At the macroeconomic level, questions of innovativeness are discussed from the perspective of National Innovation Systems (NIS), defined as a “network of agents and set policies and insti-tutions that affect the introduction of technology that is new to economy” [10, p.541], are critical for economic betterment (e.g., [12], [18], [33], [37]) and represent an important component of economic performance (e.g., [32], [44]). 

Descriptions of NIS are easily available, yet there is a scarcity of methods to operationalize NIS and its components.  Consequently, interrelationships between various elements that form NIS cannot be fully, quantitatively examined.  The same is true when the impact of the context of operation upon the design of NIS is analysed.  Some frequently used policy themes pertaining to investigation of NIS include (see also [3]), yet are not limited to:
1.    Governmental policies (including promotion of innovation friendly environment) and NIS governance.
2.    Commercialization of public research.  
3.    Development of Human Resource for innovations.
4.    Funding Innovations. 
Generally, these topics are consistent with the Lisbon Strategy [31] that is endorsed as a guide to scientific development of the European Union.   It should be noted, the elements in thematic areas overlap, making reports on NIS at times redundant in terms of information content.  Conclusions from such studies are difficult to quantify, as it is difficult to identify which solutions are correct, efficient and effective within the specific context of operations.  Consequently, the idea of NIS, though very stimulating, is an abstract one, with little possibility of being translated into the language of daily business.






Innovation: Definition Related Dilemmas

One of the problems relevant to research on innovativeness is the difficulty to establish a precise definition of innovations.  There seems to be agreement on considering innovation to be a novelty applied to something that already exists. The disagreement arises as to whether the change should be new to the market in general or only to a particular company (e.g., [48]). The former, denoted for the purposes of this discussion as the Frascati [17] approach suggests that innovation is rooted in notion of novelty in global terms.  These novelties are assessed indirectly by the level of various educational attainment statistics [12], [28], R&D expenditures [12], and patent counts [30] [23].  The latter, the Oslo Manual [38] approach, takes a more micro-economic perspective.  It deals primarily with implementation and adaptation of solutions, and is oriented towards a practitioner’s viewpoint. This approach conceptualizes innovation as an application for commercial purposes. 

Results of literature analysis related to innovations, persistently suggest that even though dis-cussion is about similar phenomena, there is a gap between macro and micro perspectives of innovativeness.  Some differences between macro and micro perspectives are summarized in Table 1.

Table 1.     Differences between ‘macro’ and ‘micro’ perspectives to innovativeness
      MACRO PERSPECTIVE        MICRO PERSPECTIVE

*      inventions (exploration)            innovations (exploitation)
*    composite indexes            fragmented questionnaire type studies
                    with little chances to find a unifying pattern
*    government, theory, efficiency         SME, practice, effectiveness
*    correctness (political, legal)        profit, risk reduction, competitive position
*    laboratories, research centers        technology incubators, daily practice
*    grants, formal contracts            loans, information type feedback
*    formal training programs        informal business meetings
*    setting rules and standards        adopting to conditions
*    WHAT DO COMPANIES WANT?    WHAT CAN FEDs OFFER?



INDICATORS AND INDEXES OF INNOVATIVENESS


Composite indexes are used in a variety of economic performance and policy areas. Such indexes integrate large amounts of information into easily understood formats and can be manipulated to produce desired outcomes.  Despite this, there are several methodological problems regarding the creation of composite indexes [41]. Problems arise when examining the accuracy and reliability of these indexes.  Quandaries regarding missing data, along with the question of index sensitivity to the weighing of indicators and their aggregation are inevitable [20, p. 5].  Composite indexes measure complex, dynamic systems and “many of their properties emerge from interactions among the entities in them” [29, p. 893].  Additional dilemmas become evident with the conceptual dichotomy between allocative efficiency (“Are we doing the right things?”) versus technical efficiency (“Are we doing things the right way?”) and these are investigated.  Moreover, there are ambiguous definitions and the various taxonomies used to measure the consequences of achieved output (e.g., [43]).

Despite these problems, there has been a proliferation of composite indexes (e.g., [2, pp.179-181]. With several notable problems, the need and/or usefulness of such diversity among indexes is questionable.  Despite being created with different intentions, and using varying series’ for calculations, these composite indexes actually produce similar results when ranking countries [36].  This occurs irrespective of whether they intend to measure the level of innovative capability, competitiveness, productivity, level of wealth, or standard of living.
   
It is important to note that several items from the composite indexes that may relate to the notion of innovativeness, deal primarily with inventiveness (e.g., on the Input side - expenditures on R&D and S&E graduates, or on the Output side - patents and trademarks, or “new-products”).  Thus, these indicators lean more towards the Frascati interpretation of innovations (hence inventions) [17, para.21 and 63].  This marks a divergence from innovations as interpreted by Oslo Manual [32, para.131].  Consequently, it is arguable as to whether common composite innovativeness indexes such as European Innovation Scoreboard - EIS [13], World Competitiveness Yearbook - WCY [49], the Growth Competitiveness Report - GCR [29] [30], the Knowledge Assessment Methodology - KAM [28], [6], and Human Development Index – HDI [25] serve the needs of practitioners interested in the improvement of economic prosperity at a “shop floor level” [9], [26], or if they are primarily a policy formulation aid at the macroeconomic level.

Composite indexes typically use a variety of indicators (data series) to measure innovativeness.  In such a way, they indicate which items of economic performance may contribute to the en-hancement of innovativeness.  This may provide policy formulation related suggestions.   This implies an assumption however, that some ‘policies’, as suggested by innovativeness indicators, will produce similar results irrespective of context in various countries.  This may not be a correct assumption.  Indicators used to measure innovativeness overlap causing information redundancy.  From the viewpoint of assessing outcomes, or statistical-type assessments, such a variety may not be needed.  Thus, it is worth verifying whether or not a more simplistic composite index of innovativeness can be formed, and eventually applied to a broader range of countries.

Despite the aforementioned reservations, some researchers and experts claim that there is an extensive body of literature about indicators of innovativeness, and therefore the search for new concepts is fruitless.  Such an opinion is only partly justified.  Indeed there are descriptions, but they do not take several important elements into account:  

1.    How can one consider using some of indicators of innovativeness as undeniable indica-tors of innovativeness, when a precise, unequivocal definition of innovativeness has not yet been agreed upon?  Thus, are these indicators really dealing with innovativeness?  It may be easier and more justified, to use the approach used in some psychological studies: intelligence is the phenomenon measured by IQ tests.  Similarly, innovativeness can be regarded as a construct determined as a result of questionnaire type studies. 

2.    The question of assessment of the level of innovativeness is still not clearly answered.  It is particularly true when we take into account dichotomies between inventiveness and inno-vativeness; definitions that follow Frascati Manual and those that favour suggestions of Oslo Manual; differences between macro and micro approaches to innovativeness: differences be-tween big companies’ and small companies’ perspectives. Paradoxically, despite the fact that these dilemmas are known, when we are approaching the idea of measurement of the level of innovativeness, the consequences of these different perspectives are ignored.  The temptation to create one universal index is human nature.  In reality, one thing can be said about such an index for certain: it is not known what is measured by such an index.

3.    Several indicators of innovativeness that are used, are difficult to be measured and their values are impacted by the context. Therefore, they cannot be used in comparative studies.  For example, Community Innovation Survey (CIS) that is used in EIS model, is EU specific.

4.    In their actual form, indexes of innovativeness (e.g. EISI), and in a broader context, indexes of standard of living (HDI) and competitiveness (WCY, GCR) show some average value of arbitrarily selected inputs and outputs.  After summing up values of inputs and outputs (normally after standardization of their values), an index is provided.  Generally, when the level of inputs is higher, a level of outputs is higher.   Thus, in countries where expenditures on in-novativeness are higher, the value of innovativeness index is higher.  However, it is still only one of the perspectives with which to examine the issue.  According to the rankings by leading indexes, wealthy countries are ones where at the very least, living conditions are relatively high. These countries are more competitive and innovative, etc.  To a large extent, it is a correct conclusion.  It is an important question however, especially for countries that desire joining the league of the wealthy, whether or not resources for innovations are utilized efficiently:  that is, whatever the given level of inputs results in the maximum level of outputs.  Nasiero-wski and Arcelus report [35] indicates that often, wealthy countries invest more in innovations and probably do it in a very appealing manner, but inefficiently.  Quite frequently, countries that are classified as laggards in innovations, do in fact spend less, but do it in efficient ways.  Aspects of technical efficiency for turning inputs into outputs should be one of the main research topics in the area of innovativeness because results of such studies may highlight Best Pro-Innovative Policies (BPIP).   

5.     Additionally, a large number of indicators of innovativeness that “must” be used in the model have the effect that quantitative calculations of efficiency of innovation systems cannot be carried out. Consequently, if one wants to start discussion about technical efficiency of innovation systems, one has to identify a method that would facilitate a reduction of the number of statistical data series.  Certainly it may not cause the model developed on the basis of a reduced number of data series, not to have similar information content as currently used models.  On the contrary, the new model may have more information content.  Additionally, the orientation on meas-urement of technical efficiency will result in processing data according to statistical algorithms (thus reducing bias), and not according to arbitrary decisions based solely on expert knowledge.

6.    One of the reasons for the critique of indexes used for the assessment of efficiency rests in the gap between theory, practice and currently available assessments of reality.  Theory and practice indicate that innovativeness and entrepreneurship form the roots for economic and social development.  The Japanese economy received one of the lowest scores in terms of entrepreneurship [49]. The fact that one of the fastest growing economies in south-east Asia is labelled as non-innovative serves as indirect evidence that the currently used methods for as-sessing levels of innovativeness are questionable. 


EUROPEAN INNOVATION SCOREBOARD (EIS):
THE LEADING, BUT  DISPUTABLE MODEL


The vital role of innovation in boosting national competitiveness is recognized by most nations.  Knowing a nation’s strengths and weaknesses allows a government to institute interventions aimed at fostering and improving their innovation record.  Innovative indicators provides evi-dence of the importance for nations to recognize which aspects of their national environment push the firms to evolve, how to measure the success of the value added in innovative sectors, and how to assess intellectual innovation [12, p.6].

One example of efforts to track national innovation ability is the annual European Innovation Scoreboard (heretofore, EIS) and its associated composite index of innovativeness (European Innovation Scoreboard Index - EISI).  This scoreboard was “developed by the European Com-mission, under the Lisbon Strategy, to evaluate and compare the innovation performance of its Member States” [12, p. 3].  EIS is essentially confined to EU countries, because it uses indicators (data series) that are based on Community Innovation Surveys (CIS). The EIS concept deals mainly with:
1.    Measurement of the level of innovativeness of EU countries and on such a basis,  ranking of countries according to the level of innovativeness.
2.    Setting indicators of innovativeness, showing governmental policies that can support in-novativeness and indirectly, economic growth.

In its assumptions, EIS should also facilitate to make suggestions that determine elements of economic activity and identify areas of social policies that should be supported in order to in-crease the level of innovativeness.  In Europe EIS forms some sort of a framework for the dis-cussion of the issue.   EIS solutions/conclusions have many very strong points and it should be appreciated that it is one of the first comprehensive methods to assess NIS, with many intellec-tually stimulating observations and practical guidelines.   EIS model forms an index – EIS Index (EISI) - that contains drawbacks.  It cannot be used as an instrument to stimulate pro-innovation policies and there are methodological controversies associated with its composition.  Among several objections expressed with respect to EISI, the following should be emphasized:

1.    The first objection deals with the selection of indicators of innovativeness.  For example, EISI uses three patent related data series.  These are highly positively correlated. Consequently, the same idea (concept) is used three times within the same index of innovativeness.  One should also note that it is disputable whether patents indeed measure the level of innovativeness of SME.  Patents are indicators of inventiveness and this is generally the domain of research institutes.  Yet another example: one of the indicators used relates to ICT (Information Communication Technology).  Thus, Poland for example, is one of the leaders in ICT. Such a position does not result from the ease of access or density of access to ICT, but from exceptionally high costs of ICT in Poland; therefore, this indicator is simply misleading.

2.     The second objection originates from the fact that despite the declaration that EISI measures innovations, it actually concentrates on inventiveness.

3.     Furthermore, it is difficult to use EISI as an instrument that impacts the crafting of pro-innovative policies, because the set of used indicators is being changed from one year to the next.  As a consequence, it is impossible to empirically prove that an increase in the level of any one indicator is indeed due to the efficiency of policies utilized.   Longitudinal studies cannot be carried out.  It is also not known which indicators are the most important because they all receive the same weight of importance.

4.     Additionally, keeping in mind that innovativeness evolves within NIS, indicators used in EISI do not allow us to determine which legal/institutional policies are correct. There is no room in EISI to assess the quality of rules, policies or stimulators; the strength of barriers; institutions and their interactions with business and/or their fit to local conditions. These elements may in fact be critical to the efficiency of innovative systems.

5.     An important question, which remains unanswered, or a problem that has not been clarified, relates to the following: why do all indicators of innovativeness used by EISI have the same weight of importance?  This implies that the process of identifying the inputs and outputs required in the computation of the index of innovativeness includes the implicit assumption of all countries:
(i) being equally efficient in the transformation of their inputs into outputs
(ii) having the same context of operations.
These assumptions are certainly incorrect.  In practice, it is more probable that an entirely dif-ferent situation occurs: two different countries that use different compositions, or levels of inputs, will gain similar results. Concurrently, the use of the same inputs at the same level and keeping in mind contextual elements, countries will achieve different outputs.  This quandary certainly calls for a more detailed examination, yet at its current stage EIS underlying assumptions are, at minimum, incomplete.

6.     The EIS concept assumes that NIS policies within the European Union should be uniform (similar).  Improvement of innovative activities is impacted by context and should not only be an average determined on the basis of an average within the European Union.  As well, importance of specific means to improve innovativeness is different among countries: for example Poland should invest in ICT (though it is ranked high according to this indicator), to a larger extend than Austria (because it has a stock of accumulated ICT capability).

As it is evident from the above-presented comments, EISI that is constrained a solution in the measurement of innovativeness, has several limitations.  In fact, it can hardly be practically used as an instrument to craft pro-innovative policies and is associated with methodological shortcom-ings.  Therefore, there is a need to identify solutions that will be useful, not only for the purpose of ranking countries from the innovativeness viewpoint (that may be useful from statistical-publication type of perspective), but also that may have practical applications.  Such methods should facilitate identification of indicators of innovativeness, that in turn will allow the creation of a composite index or indexes that will satisfy the following criteria:
1.     Be based on credible and easily available, statistical data series.
2.     Be consistent with contemporary definitions of innovativeness and reflect themes rele-vant to NIS.  It should address aspects of inventiveness as well as innovativeness, and be adequate both for big and small companies.
3.    Facilitate the examination of the technical efficiency of systems that will support inno-vativeness according to the description of the index.
4.    Be an instrument useful to formulate policies/solutions oriented on the enhancement of innovativeness, and an index that facilitates the control of efficiency for such policies.


SUGGESTIONS FOR FURTHER AREAS TO INVESTIGATE INNOVATION SYSTEMS


Linking EIS Index to NIS (“Operationalization” of NIS, the search for Best Pro-Innovation Policies (BPIP), and selection of indicators of innovativeness). 

The list of the key topics used to discuss NIS can be used as a starting point to examine the link between NIS and EISI.  Once the list of such topics is agreed upon, one can isolate key motives within each topic in an attempt to identify:
1.    Typical solutions / policies pertaining to the specific subject in an attempt to identify the Best Pro-Innovation Policies (BPIP); and
2.    Identify indicators (data series) that pertain to the topic (indicators - that represent the phenomenon). 

There is a need to find adequate indicators of levels of innovativeness and means to enhance it.  It is an important theoretical and practical topic.  The discussion about the enhancement of innovativeness is a current one, but has not resulted in practically useful conclusions.  Conse-quently its continuation is warranted because consequences that can be used in practice are very important.  They can indicate which activities and which specifics of economic growth policies will facilitate and increase the effects, keeping in mind available resources.  Results of such studies can pinpoint solutions that brought positive results in other countries (BPIP), and can, following modifications, be transferred to other contexts of operations.

While many indicators of innovativeness are used, it cannot be taken for granted which ones should form a composite index of innovativeness that will comply with the criteria discussed earlier in part 4 of the paper.  Keeping in mind the importance of the issue to social and economic development, the topic should not be neglected.  Thus, it can be suggested that the link between “innovativeness leading themes” to indicators of innovativeness is created.  These leading themes, in fact results of the assessment of the components of NIS, can be ‘somewhat’ quantified.  Even if this is not a measurement, and solely an ‘expert’s’ assessment of the quality of solutions, this will facilitate a more quantitative handling of the associated questions.  An initial attempt to use such an approach is visible in EU Trend Chart reports [3].  Note, the criteria used in the assessments have not been disclosed. 

The selection of indicators of innovativeness can be done on the basis of literature review, whereas the initial and the leading motive can be the set of indicators used in EIS.  There can be two implications of such a line of reasoning:
1.    Indicators that will be used to create an index will have the similar information content as EIS, but will be based on more easily available indicators.  The adequacy of the result can be verified with the use of Spearman Test. 
2.    Setting indexes of innovativeness can be done using two perspectives on innovativeness:
(i)  big enterprises perspective, based on Frascati Manual, that assumes macro-economic perspectives;
(ii)  SME view, which covers improvements at the operational level, and is rooted in concepts described in Oslo Manual.

There are strong correlations between items in EIS index, thus creating redundancies of infor-mation within its contents.  Many elements are counted two or more times.  It may be that the EIS index can be reflected by a simpler set of indicators yielding similar results of ranking the innovativeness of countries).  Therefore:
-     is there a need to use so many indicators as in  EIS (especially those that use data series specific to the EU alone) in order to measure innovativeness?
-    how can a new (modified) index of innovativeness be constructed? - can an analysis of the data suggest an alternate categorization of the indicators, instead of the five pre-determined scales used by the EIS [12].

A  “compression”  indicators used in EISI produces a trade-off between an index as a policy making driver versus index as platforms for ranking purposes.  While keeping in mind the number of “NIS themes” and the number of corresponding sub-topics, one may expect that the number of suggested indicators for innovativeness measurements will be extensive.  In order to reduce the number of indicators (data series) and form a New Innovation Index (NII) a principal-components analysis can be performed on the 26 indicators used by EIS [12].  A similar approach is recommended by Saisana & Tarantola [41, p.12].  The following four-step procedure based upon Hair, et al. [24] can be used, and has already been tested  [47]:
1.    Scan the anti-image correlation matrix and eliminate from the analysis those indicators with a sample adequacy below 0.7.
2.    Repeat the analysis until the Kaiser-Meyer-Olin indicator of sample adequacy reaches 0.8. If the value of such an indicator cannot reach that value, stop, since no statistically significant principal-components analysis can be undertaken.
3.    Extract all factors that explain at least 10% of the variation and/or their eigenvalue is at least 1.
and
4.    Interpret the resulting factors on the basis of the indicators with a factor loading of at least 0.5. 

Once the number of factors has been established, the next step is to compute another measure of the EIS, on the basis of the factor loadings obtained through the principal component analysis. The issue of contention is the weight to assign each factor in computing the overall score for each country.  EIS [12] gives equal weight to each factor, thereby having the average of the factor loadings as the overall country measure from which to obtain the ranks. One of the problems with this approach is the lack of evidence that each item is equally important in the rankings.  A possible solution to this problem is to weigh each factor by the percentage of total variance explained by the said factor.  In this paper, we rank the countries according to both criteria and use the Spearman correlation coefficient to test for the difference between the ranks. The evidence indicates that, with the p-values of the tests less than 10-4, the ranks are not sufficiently affected by the ranking criterion utilized.  Hence, both methods, i.e. with the inputs and outputs together and separately, yield similar rankings.

Technical efficiency on innovation systems: DEA results as a measure of quality of innovation systems

It is reasonably clear from the preceding discussion that the methodological base given in EIS [12] is not free from controversy.  The important observations dealing with the equal weights of inputs and outputs, raises questions of comparability of the efficiency in innovation systems.  This leads to the important issue in this section, which is how to assess the technical efficiency (EFF) of countries in the process of transforming inputs into outputs. From a micro-economic perspective, such issue epitomizes the concept of Paretto-Koopmans efficiency [45], related to the ability of a country to minimize the number of inputs required to produce the maximum possible set of outputs. Hence a country “is fully efficient if and only if it is not possible to improve any input or output without worsening some other input or output.” [8, p.45].

To model such a concept one can use the non-parametric technique of Data Envelopment Analysis (DEA) [15] [16], and in particular [7], [8]), where the countries that fulfill the efficiency definition form a benchmarking frontier against which all others are evaluated. The inputs and outputs of the model are the three factors obtained from each of the two principal component analyses on the EIS 26 indicators described in the previous section.  For the EFF formulations, the paper uses an input orientation, consistent with the belief that countries are in a better position to control the inputs than the outputs. Within this context, EFF relates to the minimization of the resource endowment needed to produce a set of outputs.  Benchmark countries have an EFF of 1.  For the others, EFF is measured in terms of how far the other countries must reduce their input consumption to reach the levels of their efficient counterparts.

Two crucial characteristics of a country’s production process may have an important impact on the efficiency computations. These are, returns to scale (RS) and congestion (CON), two key concepts of production economics (e.g., [7], [8], [47]).

RS deals with the rate of change in the inputs utilized, as compared with the rate of change in the outputs obtained. Constant RS (CRS) occurs when the rate of changes in the inputs equals that of the output. Alternatively, if rates differ from each other, there is evidence of variable returns to scale (VRS). Another RS index used below is that associated with the non-increasing returns to scale (NRS). Generally, it may be assumed that other than optimal RS indicates a lack of economies of scale, and thus, probably also limited synergies stemming from country size.

The second characteristic, congestion, deals with the cost of disposing of unwanted inputs.  The inefficiency arises from the fact that the presence of congestion requires the use of resources for the elimination of the undesirable inputs that would otherwise have gone to generate more outputs.  “Evidence of congestion is present when reductions in one or more inputs can be associated with increases in one or more outputs - or, proceeding in reverse, when increases in one or more inputs can be associated with decreases in one or more outputs - without worsening any other input or output.” [8].  Examples of input congestion appear in Coelli, et al [7] among many others, in cases of government or union-based controls on the use of certain inputs.  The literature employs the terms weak (WD) and strong (SD) disposability to denote whether evidence of congestion exists or not.  It may indicate that inadequate specialization patterns are used in pro-innovative activities, if congestion is different than “1”.

SUMMARY

This report has largely been based on European Innovation Scoreboard 2005 [12], [42].  One of the main trusts of the EIS approach is that indicators included to create an innovativeness index, can be impacted by means or regulations and national innovation policies.  The goal of subsequent EIS Methodology reports is “to further explore different dimensions of innovation and to identify areas that are not covered in the EIS” [4].   This trend may also be rooted in the recommendations of Aho Report [1] that suggests “a 4-pronged strategy focusing on the creation of innovation friendly markets, on strengthening R&D resources, on increasing structural mobility as well as fostering a culture which celebrates innovation”.  In such a manner, there will be somewhat of a departure from an emphasis on innovation inputs (such as R&D expenditures), and innovation outputs (such as patents), more in the direction of capturing aspects related to creation of demand for innovation, and socio-cultural, education, entrepreneurial, and flexible stimulators for implementation of innovations.  Even though, the current “EIS provides considerably better coverage of innovation as a creative activity than innovation as a process of diffusing new technologies and knowledge” [4, p.3], it still exhibits several disadvantages.

Results derived from the EIS [3], [4], reports present only a partial picture of the innovativeness of countries. This data focuses on a country’s ranking, and whether they are leading countries, exhibit average performance, are catching up, or are losing ground.  None of these measures considers specific economic and social conditions of the country.  This paper has attempted to offer insight into whether available funds are spent efficiently by countries, rather than focusing solely on the aforementioned classifications and rankings.  The use of non-parametric techniques can essentially reformulate well established opinions and accepted levels of understanding the problems of innovativeness.
Each composite index captures some information related to economic improvement.  Since items in these indexes are strongly correlated, it should be asked which item acts as a stimuli for the development of the other.  Recommended innovation policies should not be considered as “an average” of responses from different sectors, by companies of different size, which operate within very different economic, political, and social contexts, thus making one of objectives of the EIS approach – “that indicators have policy implications” - difficult to endorse.  It is important that aspects of efficiency are addressed in a way, that permits a better modeling of EU policies, to the sectorial and regional specificity [46]. 
It is at times expected that composite indexes may serve as a guide for policy settings.  However, data series used in composite indexes change almost every year.  Such a practice limits the possibility of identifying whether policy changes have contributed to the improvement of desired operational outcomes, and longitudinal type studies are limited .  

Yet another topic worth exploration deals with elimination of the impact of contextual variables (market factors, culture, accumulated stock of experience, macro-economic structure of the country, developed business links, etc.) upon efficiency of innovation systems.  If the impact of contextual elements upon the level of innovativeness is isolated, a composite index could serve as a starting point to examine the effectiveness of programs oriented on support of innovativeness (i.e., to which extent policies related to innovativeness indeed contribute to social and economic objectives).
Acknowledgements
This research was partly supported by grants from the University of New Brunswick, and the Faculty of Business Administration at the University of New Brunswick. This support is noted and appreciated. 


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Florinel-Frank Cotae

International School of Management

New York , United States

Keywords: multinational enterprise (MNE), leadership, organizational learning, learning organization, internationalization process, sigmoid...

Florinel-Frank Cotae

International School of Management

New York , United States

Keywords: multinational enterprise (MNE), leadership, organizational learning, learning organization, internationalization process, sigmoid

Vipin Gupta

Ros Jaffe Chair Professor of Strategy

Simmons School of Management , Simmons College

Boston , United States

Keywords: global economic crisis, technological and organizational solutions, sustainable bu...

Vipin Gupta

Ros Jaffe Chair Professor of Strategy

Simmons School of Management , Simmons College

Boston , United States

Keywords: global economic crisis, technological and organizational solutions, sustainable business , emerging markets , culturally sensitive business behaviors, sustainable development index

Inder P. Khera

Professor of Marketing & International Business

Raj Soin College of Business , Wright State Univeristy

Dayton OH , United States of America

Keywords: personal ethics, business ethics, personal ...

Inder P. Khera

Professor of Marketing & International Business

Raj Soin College of Business , Wright State Univeristy

Dayton OH , United States of America

Keywords: personal ethics, business ethics, personal values and corporate ethics, culture and ethics, cross-cultural differences, applied ethics, global business ethics