Customer Value Oriented Marketing Information Management. Ph.D Thesis

Dr. Attila Bernáth

Customer Value Oriented Marketing Information Management Ph.D Thesis

„Theory and practice of enterprises” programme Director of Ph.D. course:

Prof. Dr. Aladár Nagy D.Sc. egyetemi tanár Scientific principal:

Dr. István Piskóti Ph.D egyetemi docens

Miskolci Egyetem, Marketing Intézet Miskolc, 2005.

Thesis Customer Value Oriented Marketing Information Management, Ph.D thesis

TABLE OF CONTENTS

TABLE OF CONTENTS ......................................................................................... 2 1. OBJECTS AND FIELDS OF RESEARCH OF PH.D. THESIS IN CUSTOMER VALUE ORIENTED MARKETING INFORMATION MANAGEMENT....................... 3 2. THE APPLIED RESEARCH METHOD, INTRODUCTION OF THE CONDUCTED RESEARCH ..................................................................................................... 4 3. SUMMARY OF THE MAIN, UNIQUE OUTCOMES OF THE RESEARCH: THESIS ........................................................................................................... 4 3.1. VARIABLES AND MODEL OF MARKETING ORIENTED DECISIONS ...............................4 3.2. THER CENTER OF MARKETING ORIENTATION REGARDING THE HUNGARIAN B2B MARKET OF SMALL AND MEDIUM ENTERPRISES ...............................................7 3.3. SAND-CLOCK MODEL OF VALUES .........................................................................11 3.4. RISKS OF APPLYING RANKING TECHNIQUES IN CUSTOMER VALUE RESERCH .........15 3.5. OPTIMALIZING PRODUCT/SERVICE CHARACTERISTICS BY MAXIMALIZING CUSTOMER AND COMPANY VALUES ........................................................................16 3.6. THE DEVELOPMENT OF COMPANY INFORMATION AND DECISION SUPPORT SYSTEMS ................................................................................................................18 3.7. EFFICIENT MARKETING INFORMATION AND DECISION SUPPORTING SYSTEMS .......21

4. LIST OF PUBLICATIONS CONNECTED WITH THIS DISSERTATION .................. 26 5. LIST OF EMPIRICAL RESEARCHES CONNECTED WITH THIS DISSERTATION ............................................................................................. 27 6. REFERENCED PUBLICATIONS ...................................................................... 29

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1. OBJECTS AND FIELDS OF RESEARCH OF PH.D. THESIS IN CUSTOMER VALUE ORIENTED MARKETING INFORMATION MANAGEMENT

The rediscovered center of the orientation development of marketing management is customer value, putting the relation of expenditures and expectations into the limelight again. Furthermore, nowadays’ information technology generates significant advantages in translating the theoretical implications into practical life. The aim of the dissertation is to point out and draw attention to the importance of customer value oriented marketing information management, to define the elements of marketing information management process, and the alternatives of its integration into company processes. Besides it makes an attempt to identify the imperative engagement points of company systems and marketing information systems while bringing customer value into the focus. In the first part of the research I am examining the conceptual and empirical definitions of customer value and value of the customer on different markets. Measuring customer value offers the advantage of the ability of strategic and tactical planning, providing the benefit of making the company’s activity conscious and deliberate, concentrating on satisfying customers’ need at the highest level, which proved to be the key factor of profitability. Recognizing customer value specifies the customers’ attitude towards the company; it also determines the amount and quality of the company’s attention required for improving this attitude. On the field of customer value research I have conducted several empirical research examining the customer market (food industry, paint market, bank sector, B2B markets, political marketing and many more) to give a multi-colored complex picture of the importance of the customer value topic and its differences of research methodology and content in markets of different characteristics. Only the selected elements of these markets are studied thoroughly in this dissertation, due to the limited size of this paper. The other mayor axis of my dissertation is the new approach to systematizing the tools and devices of marketing information management embedded in company information management, by this means forecasting the direction of system-development. The company management can be functionally sustained on all points of the value-chain by information and decision support systems. This study is accentuating the importance and necessity of introducing the phrase and way of thinking of marketing information management, as this is the key factor – integrated with all other company systems – to prepare the way for making and implementing marketing management decisions. The present dissertation is defining the main points of marketing information management considered in the narrow sense.

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2. THE

APPLIED RESEARCH METHOD, INTRODUCTION OF THE CONDUCTED RESEARCH

The method of approach adopted in this research was guided by the rules of modern scientific problem-solving. My general approach of research methodology    

 

Clarification of the conceptual categories, theoretical comprehension, explanation through examples Conceptualization, expressing the problems by stating questions and hypothesis Operalization, verifying hypothesis via empirical and other researches conducted on selected fields Conducting analysis strongly supported by mathematical-statistical methods (factor-, conjoint-, cluster-analysis, multidimensional scaling, multidimensional regression and correlation analysis, etc.) Conclusions, deductions, and on its basis Summarizing the characteristics of the examined system via modeling

The results and consequences of the analysis are based on a decade of research experience and several years of management skills. The last phase of research collected information on marketing orientation, applied marketing management solutions and expectations towards marketing information systems of enterprises, by questing 200 small and medium size enterprise. The sample was selected by the method of multiple stage optimal layering, which ensures the territorial representation of Hungarian small and medium enterprises operating in the field of metal-working. The applied research method and modeling process can be the basis of comparing national and international research results.

3. SUMMARY OF THE MAIN, UNIQUE OUTCOMES OF THE RESEARCH: THESIS 3.1.

VARIABLES AND MODEL OF MARKETING ORIENTED DECISIONS

1. Thesis: The orientation of company marketing management is determined by the characteristics of exchange, the abilities and the strategic plans of the company under given market circumstances and given geographical location. The system of company values performs as a qualification filter of marketing orientation. The marketing orientation of a company is formed by the affect of market potential, company abilities and eventuality. Therefore marketing orientation is the subsequent upon the abilities and chances of the company, and the necessities formed by the system of the market factors.

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About the well-known marketing orientations can be said that they are overlapping, have several similar features. It is not rare that when examining one company, several marketing orientation scale of value can be identified, due to the complex range of activities.

INDEPENDENT VARIABLES IN MARKETING ORIENTATION DECISIONS When chosing a marketing orientation and the preferred tools of the marketing system a company is driven by the following group of factors, which are to be considered as independent variables, i.e. given conditions: 1. 2. 3. 4. 5.

The characteristics of exchange, including its location, its relation, and its amount The resources and abilities of the company Environmental circumstances

The complexity of marketing activities is surrounded by the external circumstances and parameters. The elements of the external circumstances are hardly be changed (in significant amount and in a short period) therefore these factors must be considered and accepted as given ones.

DEPENDENT VARIABLES IN MARKETING ORIENTATION DECISIONS The dependent variables in the space determined by the market dependants(environmental factors, characteristics of exchange, values) and the ability of the company are:  The evolved scale of values  Marketing orientation  Strategic goals of the company  Marketing strategy Values and the system of scales of values are functioning as filters or like glasses setting these values into the focus of every strategic effort of the company. These modified aspects do not mean difference regarding the applied marketing tools, just accentuate and concentrate on the contents of planning and implementation. The difference in the evolved values does not determine different styles of marketing. These values are such as:    

Society-orientation Network-orientation Customer value orientation Relationship-management orientation, etc

The following illustration summarizes the steps and factors of the process of elaboration of the companies’ marketing orientation. As a resultant of the independent variables (market determinants and knowledge of company abilities) emerges the content of the dependant variables as a result of deliberate planning and implementation process.

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The illustration is based upon the collected viewpoint of almost 30 authors, and the results of empirical researches of Sajtos (2004), Bernáth (2004) and Coviello - Milley – Marcolin (2003).

A vállalati marketing orientációt meghatározó elemek Maba©

Csere helyszíne (ágazat)

... Turisztika Közmű szolgáltatások ...

MO

... Vegyipar Gépipar

B2B

B2C

B2G

G2B

Egyedi gyártás, szolgáltatás Kis sorozatú gyártás, szolgáltatás

...

Csere relációja (résztvevői)

Tömegszerű gyártás, szolgáltatás Értékek, értékrendek

Csere tömegszerűsége

Marketingcsatorna politika Marketingkommunikáció Termékpolitika Árpolitika

MIM

MFM

MKM

MEEM

MB

VÁLLALATI FUNKCIONÁLIS TERÜLETEK

Marketing környezet

Marketing management styles are multi-coloured just likethe creativity of marketing specialists, therefore it is hard to lay down one orientation as a fundamental axiom that holds true for every situation and every company. More advisable – for the sake of practical usage – to optimalize a variation derived from given market and company factors.

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3.2.

THER CENTER OF MARKETING ORIENTATION REGARDING HUNGARIAN B2B MARKET OF SMALL AND MEDIUM ENTERPRISES

THE

2. Thesis The center (the focus-point) of marketing management scales of values regarding the Hungarian B2B market of small and medium enterprises – similar to the international examples – is relationship marketing orientation. But diversely to international practice the Hungarian version of relationship marketing orientation excludes almost all other types of marketing orientation, slightly ready to adapt or integrate technology-dependent or other modern marketing aspect or practice. The research I conducted by questionning 200 Hungarian small and medium enterprisespoints out that diversity and variousness is typical in nowadays’ Hungarian marketing practice. Even the most “up-to-date” relationship marketing could not gain a dominant share, “only” could be the first among all other types of orientations. The conceptualization model of the research defines three layers of contents, via 40 qualificative statements, also considering those factors of the before-presented model of company marketing orientation that may directly affect marketing orientation:  Characteristics of exchange (market)- (factors reducted according to B2b market)  Factors determined by company orientation, scale of values, and style  The preferred tools of company marketing strategy Typical that regarding the obtained ranks, 7 of the first 10 statements referred to relationship management and relationship-quality with customers, so we can draw a conclusion that relationship orientation stands in the focus of Hungarian small and medium enterprises scale of value. The next ones in rank are competition orientation, and marketing technology orientated types of aspects. Analysing the respons via factor analysis I defined 10 individual styles of which the first 8 are the following:

Factors: 1. Relationship marketing 2.Professionalist marketing, development and system oriented marketing 3. Competition and competitor oriented marketing 4. Transaction marketing 5. Network marketing 6. External resource oriented commisioners 7. Customer value oriented marketing 8. Assortment and trade oriented

-7

Variance: 7,510 5,984 5,482 5,282 4,734 3,942 3,892 3,494


As can be seen, 7 of the above-listed styles are marketing oriented. Styles 1., 3., 4., 5., and 7. are coincide with observed marketing orientations. Relationship marketing is the dominant orientation in the sample, as will be proven by further findings of this research. On course of the research the respondents classified their companies’ attitude towards five given marketing style. Analysing the applied relationship marketing based styles via multidimensional scaling and reducing the dimensions into the following two distinguishing factor: 



The formalization of the relationship on course of the exchange, which ranges from formalized contractual relationship of network marketing to the intuitive form of relationship marketing. The range and the modernity of the applied marketing tool system, which runs from traditional to modern tool systems.

Marketing orientációk pozíciója multidimenziós skálázással

Maba©

Modern

Adatbázis marketing 1

E-marketing

0,5

Kapcsolati mark eting 0 -2

-1,5

-1

-0,5

0

0,5

1

1,5

2

-0,5

Hálózati marketing

Hagyományos

Marketing technológia

1,5

-1 -1,5 -2

Tranzakciós marketing

Formalizált

Nem formalizált Kapcsolat formalizmusa

Comparing the findings of the Coviello (2001) research with the Hungarian results, we can state the conclusion that Western marketing application is much more balanced and intensive considering the orientations. As can be seen, the orders in ranks of marketing orientations are identical, but there is significant difference in the intensity of usage.

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Marketing stílusok mennyire jellemzők a cégekre Magyarországon illetve az Egyesült Királyságban és ÚjZélandon? 5

4,57

4,23 3,863,69 3,55

4 3 2

2,82

2,79 2,15 1,79 1,79

Kapcsolati marketing Hálózati marketing Tranzakciós marketing Adatbázis marketing E-marketing

1 M.o.

UK-Ú-Z.

The findings of the Coviello research and the research I conducted are coincide when concerning the relationship of transaction marketing with the other marketing orientations, and concerning the relationship of e-marketing with database marketing. An apparent common mark is that transaction oriented marketing strictly exclude the presence of network and relationship marketing orientation.

Párosítások: RelationshipMarketing / Network Marketing e-Marketing / Network Marketing Database Marketing / e-Marketing e-Marketing / Relationship Marketing Database Marketing / Network Marketing Database Marketing / Relationship Marketing Transaction Marketing /Database Marketing Transaction Marketing / e-Marketing Transaction Marketing / NetworkMarketing Transaction Marketing / Relationship Marketing

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Corelation coefficient: UK – New-Z 0,75 0,52 0,47 0,40 0,35 0,31 0,28 0,03 -0,14 -0,29

Correlation coefficient: Hun. 0,15 0,04 0,34 0,00 -0,13 -0,21 0,20 0,11 -0,16 -0,33


Kapcsolatmenedzsment alapú marketing stílusok kapcsolatszorossága 1,00

0,80

Korrelációs együtthatók

0,75

Korrelációs együtthatók: UK

0,60 0,52

Korrelációs együtthatók: Mo.

0,47

0,40

0,40 0,35

0,34

0,20

0,31

0,28

Lineáris (Korrelációs együtthatók: Mo.)

0,20 0,15 0,11 0,04

0,00

0,03

0,00 -0,13

-0,20

Lineáris (Korrelációs együtthatók: UK)

-0,14 -0,16 -0,21 -0,29 -0,33

-0,40

Examining the relationship-system of other marketing orientation, there is much less resemblance can be found between the results of the two research, which illustrates the lack of consciousness of choosing marketing orientation styles in Hungary. Another typical Hungarian feature of marketing practice is that relationship and network oriented marketing styles are not attached to technology-demanding marketing styles like database and emarketing.

Kapcsolatszorosság jellege

Marketing orientációk kapcsolatszorossága a többi orientációval két kutatás összehasonlításában 1 0,8 0,6 0,4 0,2 0 -0,2 -0,4 -0,6 -0,8

M. o. UK-ÚJ-Z.

-1 e-marketing

adatbázis marketing

hálózati marketing

tranzakciós marketing

kapcsolati marketing

The consciousness of Hungarian small and medium ventures notably falls behind the practice in the United-Kingdom. The only exception is transaction marketing, which is agreed to be a traditional type of marketing orientation.

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3.3.

SAND-CLOCK MODEL OF VALUES

3. Thesis: Exchange is the exchange of values. Any kind of exchange can be realized only and only if the expected customer value and the value of the customer are balanced – according to prefences at the exact place and time of the action – and the ratio of efforts and sacrifices induce the parties to compromise and realize the exchange. Exchange is not just a transaction or deal. Being envolved in an exchange is influenced by much more elements than money and goods. The process of exchange takes place in a multidimensional space, where the joint influence of subjective and objective factors generate the readiness to the exchange. Theories published before have not recognized or described in details yet so far, that the necessity of consonance in values is the crucial factor of the exchange decision. This harmony in values is particularly important regarding the expected value, the perceived value and the transferred value. The idea of customer value raised notable interest both on the field scientific (Woodruff, 1997) and practical approach (Bradely, 1994). They defined several method of approach for researching values. Some reports define value to be an advantage (functional, social, emotional, knowledgebased, aesthetical, delightful, situational, holistical, comfort). Zeithaml (1988) and Bolton &Drew (1991) define value as a substituting phrase for the relation between the price and quality of the traded goods. In Lai’s (1995) opinion value is a special cost-cathegory (financial, time, risk, human resources).

Every characteristic of a traded good is a positive and negative consequence of the cutomers’s usage of the attributes of the goods, as a form of value hierarchy(Woodruff és Gardial, 1996, Woodruff, 1997). Hofmeister-Törőcsik (1996) points out five common elements to be present in describing values. Values are considered to be durable concepts or convictions, which may emerge in different situations, dominate the evaluation process and well-settled according to their importance. All the above detailed scientific opinions are synthesized by Kotler (1988, 1998, 2003), amplifying them with the statement that every phrase in the system of values is a one-word representation of a multidimensional element. On the basis of the quoted idea of Kotler, the exchange of values is based on: customer-orientation, usefulness, customer-satisfaction, customer value and value of the customer.

CUSTOMER VALUE: difference between the total customer value and its cost, while total customer value is the sum total of values expected by the customers regarding the concrete commodity or service. (Kotler, 1998)

ELEMENTS OF THE TOTAL CUSTOMER VALUE (customer expectations in an exchange situation)  Impression of the optimal price, which conveys value for the customer. Its level orientates the customer when evaluating the expectable quality and utility of the item or service. Much too low price can be deterrent as well, as it communicates

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    

 

the expectation of low performance and quality. Optimal price is a subjective cathegory, determined by the conditions of the customer. The practical value of the commodity or service, the complexity of functions obtained by the customer when purchased the product. Performance of the product or service, the level of accomplishing the promised functions Quality, correspondence with the customers’ subjective and objective expectations regarding the product or service Convenience, accessibility of the product or service Prestige/reputation value, resulting in emotional satisfaction when purchasing the product or service, for instance when accompanied by members of a reference group The value-transferring ability of the staff, as a mean of procuring the joy of possessing the goods for the customer on course of the exchange Need for security, which is presented by safeguarding of customers’ interest, and the individual affection of the customer towards the product or brand.

THE ELEMENTS OF THE TOTAL COST OF CUSTOMER VALUE   

 

Cost of purchase consists of the purchase price, the cost of transportation and traveling, etc. Cost of usage: cost of necessary replacement parts (battery, fuel, etc.) and the expenditures of servicing Dedicated time value, in exponential ratio with the cost of the customers’ time necessary for the purchase and the acquisition of skills necessary for proper usage Cost of energy, similarly to time value, the energy-demand of purchase and the acquisition of skills necessary for proper usage Psychical costs, costs of conflicts and risks resulting from decision, purchase and usage

The value of the customer is not merely the price that is realized via the purchase process, it means much more. The value of a customer can be degfined as the balance of the advantages realized by the company, and the expenditures of the company in connection with the exchange process.

THE REALIZED ADVANTAGES OF THE COMPANY (among others) 



 

The realized income of the purchase, which consists of the purchase price, the revenue of the connected complementary services (sevice, maintenance), spare parts, attachable parts, etc. Relationship and attitude established on the purchase between the customer and the seller. In case of network type of co-operations the price can be modified from the profit maximalization practice, if it generates collective benefit. Loyalty of the customer, the proportion of the customers’ purchases at a certain seller regarding a certain product or service. Volume of purchase, the knowledge of which is an important precondition of proper forecasting of the total volume of demand so as the planning of the production.

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 

 

Predictability of the time of purchase, which results in direct profit, and enables continous availability which leads to higher level of customer satisfaction. Reference, prestige, image building by the seller, if the customer is a member of a different potential reference group – as will be proven by the later detailed results of the research. Readiness to pay, the most attractive value of customers, if its liquidity is continous, payments are realized on time or before due Deadline of payment: in case of powerful multinational companies 90 and 120 days of contractual payment deadlines are common.

COSTS OF THE VALUE OF THE CUSTOMER  





Invested time: time of activity and attention Tied up capacity: the company sacrifices other possibilities for utilization of capacities like planning (CAD), technology (CAM), investment, creative knowledge, etc. Indirect expenses: like system management and operation (quality assurance, information and decision-supporting systems, etc.), reserve economy, financial management. Direct expenses

In the opinion of Woodruff (1997) the different viewpoints of parties (seller, buyer) result in notably different values. To make it more perceptible he introduces the phrases expected value and transferred value.

EXPECTED VALUE: the value which fulfils the preliminary expectations of the customer for maximalizing the satisfaction in accordance with the invested amount.

TRANSFERED

VALUE: factors, parameters which can influence the actual value of the product or service. Its coincidence with the expected value is possible only in case of tailormade services or products. In case of surplus in seller’s performance it results in unnecessary loads, in case of succumb of customer expectations it results in disappointment and negative customer attitude.

PERCIEVED

VALUE is customers’ developed picture of the practical advantages of the

product/service, that usually differes from both the expected and the transferred value (Rekettye, 1999).

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SAND-CLOCK MODEL OF VALUES

An exchange is realized when the customer value and the value of the customer are in balance and harmony. Both the buyer and the seller are weighing up the pros and cons before getting involved into the exchange. During this process consciously or unconsciously they are measuring the achievable benefits and the expectable costs and sacrifices. The answer to the question - Can the object of the exchange go through the bottleneck of the sand-clock and get to the customer? – is determined by the concrete values of the above factors, detailed in the following model.

Érték homokóra modell Maba©

- Teljes vevőköltség

Teljes vevőérték + Személyzet értékközvetítő minős. Termék/szolg. használati értéke Termék/szolg. minőség Kényelem, elérhetőség Termék teljesítmény Optimális ár érzete Presztízsérték Biztonság

Beszerzés költsége Használat költsége Pszichikai költség Energia költség Időáldozat

Vevőérték Csere Vevő értéke Fizetés ideje Vevő lojalitása Fizetési készség Realizált árbevétel Vásárlások volumene Vásárlói kapcsolat és kötődés Vásárlások időbeni kiszámíthat.

Céges előnyök

Időáldozat Közvetlen költségek Közvetett költségek Erőforrások lekötése

+

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- Cég ráfordításai


3.4.

RISKS

OF APPLYING RANKING TECHNIQUES IN CUSTOMER VALUE RESERCH

4. Thesis: In customer value researches improper chosing and applying of ranking technique bears the risk of distortion in information. This defect can be eliminated by applying precompensational information gathering technology. Assumptions of the research: 1. Research methods, in which respondents are ranking a simple given list of factors, automatically result in distorted outcomes. 2. different lists with different order of factors are differ in quality, i.e. they diverge from the actual value in different extent, ceteris paribus. 3. When applying alternative lists, the average ranking of least preferred aspects have smaller standard deviation than the ones which more preferred On course of the research I examined the hypothesis on technical defects due to ranking techniques, the possibility of the generalization of its liability and similarity by applying empirical research. The decision-factors listed in the questionnaire obtained various ranks depending on their position in the list. This kind of difference roots in different types of defects of the research method. The obvious and well-provable fact, that a certain part of these mistakes are tendentious. The real value model of accuracy of research measurement defines two kinds of mistakes: Xm=Xt+Xs+Xv, Xm: Measured value, Xt: Actual value, Xs: Systhematic mistake, Xv: Random mistake In tzhe examined situation the actual (real) value can be modified by both the systhematic and random mistakes. The interpretation of mistakes relevant in this research: 1. Xv random fault: a. The obtained results’ deviation may root in the mistakes of the sampling. The value of the random mistake is 2,423% at 95,5% reliability level, p=0.125 probability, handling the average values of the sample together. This eight-degreed scale accounts for a distortion in average position of 0.1696 projected to class intervals. The maximum degree of mistakes in the evaluation of aspects b. The maximum rate of faults when evaluating the different aspects (see the following tables) is 6.854 %, with value of 0,4797. The value of random faults dependent on merely the position in the list has the same rate of 2.423 %, and nominal value of 0.1696. This value of fault is corresponding with the average 8,93% tendentious deviation by positions. We may state that during the determination of the aspect-free values merely depending on their positions in listing, the random faults described in points b.) and c.) are compensating each other. c. Mistakes deriving from the attributes of scaling techniques of ordinal scales. (Pfanzagl, 1968)

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d. Mistakes deriving from the actual context of aspects listed (the different order variation of factors listed in the questionnaire) In case there is no systematical mistake, the occurance of random mistakes has standard deviation around the average. The compensating trend for the influence of these mistakes is theoretically horizontal, so it is not correlated with the positions of factors in the list. 2. Xs systematical mistake is relevant in this research only in case of mistakes deriving from the different positions of factors in different lists. Irrespectively from the position of purchase factors in the list of aspects, the average of gained ranks are shown on the table bellow. It came obvious that the stripe of the calculated rate of sampling containes the trend-line, so the differences can be explained by merely the mistakes of sampling.

Átlaghelyezések a listában elfoglalt pozíció szerint 5,2 5,0

y = 0,0893x + 4,0947

4,89

4,8 4,63

4,60

4,6 4,4 4,2

4,55

4,50

4,45 4,20

4,16

4,0 1

2

3

4

5

6

7

8

"vásárlási szempontok" pozíciója On the course of research all three hyphothesises were proven right. The distortion effect can be compensated by applying precompensationing techniques described in this paper.

3.5.

OPTIMALIZING

PRODUCT/SERVICE CHARACTERISTICS MAXIMALIZING CUSTOMER AND COMPANY VALUES

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BY


5. Thesis: Exists, and can be realized - by applying modern company information systems - an optimum of product/service characteristics which synchronizes the profit-maximalizing efforts of companies with customer value maximalizing efforts of the market.

Before introducing a new product to the market, companies usually take the advantage of several supporting devices in order to optimalize their risks. The main subject of research is that which are the factors and what types of their interaction have effect on the optimal product mix, and if this correlation of factors can be modeled. The utility factor of all products of all competitors on the market can be calculated, even more the utility value of our prospective product and the combination of all relevant products can be calculated via conjoint analisys. The assertions of the thesis are confirmed by several empirical research results, detailed lated in this paper. Obviously the evaluation can be made for the customer usefulness of only the factors appeared in the conjoint analisys, which could result more than 90% coverage of in case of a well-prepared research. Accepting the simplifying effort of the following idea, we can assume that the rational kind of customer behaviour is aiming at value-maximalizing, so we can consider customer value (VÉi) to be the optimum criteria of customer. The usefulness of the “i”th product variation is Ui, the unit price is Pi, therefore the optimum criteria is: max (Ui / Pi = VÉi) The optimal product is entirely different from the point of view of customer and the company, because the most important factor of purchase for the company is profit, while for the customer the focus is on maximalizing pleasure provided by the product. In direct ratio with the increasement of the utility/usefulness of the product, its market image is improving as well. Easy to accept that – ceteris paribus – the Qi sale volume of ti product variation with VÉi customer value have a relation to a pproduct variation ti+1 with VÉi+1 customer value and Qi sale volume as the following: if VÉi < VÉi+1 , then Qi < Qi+1. If all factors are identical, the customer choses the product variation that offeres higher degree of pleasure, so if the customer value is increasing, - ceteris paribus - the sale volume is constantly increasing as well. The revenue optimum criteria of the company FTi, can be calculated as the multiplication of the per-unit contribution (fi) and the sale volume (Qi), so Qi increases in direct ratio with VÉi so the joint optimum criteria for customers and the company is: max FTi(VÉi)  max (VÉi*fi) On the basis of the above formula, we can state that the common optimum criterium for customers and companies in introducing a new product or service is formed by the joint effect

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of two different factors: the maximalization of the customer value and the per-unit contribution at the same time. Via conjoint analisys we can calculate the utility/usefulness factor of the examined product variations which is the basis of the customer value. The value of per-unit contributions can be calculated from expenditure factors and the perunit prices of the different product variations.

Optimális termék kiválasztását segítő TOF függvény

150

10 9 8 7

50

6 0

5 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 4

-50

3

Fajlagos fedezet -100

Transzformált vevőérték

Fajlagos fedezet, Optimum mutató

100

2

TOF Termék optimum függvény

1

Transzformált vevőérték -150

0 Termékváltozatok

1. ábra:

Algebraical function supporting the selection of the optimal product variation

The above function visualizes the optimalization process of product variations, supported by a graphical method of TOF (Product Variation Optimalization Function) which culminates in the optimal product.

3.6.

THE

DEVELOPMENT SUPPORT SYSTEMS

OF

COMPANY

INFORMATION

AND

DECISION

6. Thesis: The direction of development of company information and decision supporting systems must be towards customer oriented information management. On demand driven markets – as customer is the bottleneck of the process – within marketing, customer orientation is the inevitable future dominant focus of company information and decision supporting systems.

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The mangement of a company can be functionally supported at all points of the value chain by information and decision supporting systems. The trend of the development process regarding the past decades is as the following:

Vállalati információ menedzsment és döntéstámogatás szintjei Maba©

SIS Felső vezetés Elemzők, döntés előkészítők

EIS

EIS

DSS

DSS

ERP CRM

Funkcionális vezetők

MIS

MIS

IOS Végrehajtók

Warehouse

Warehouse

Rendszerek a 80-as években és a 90-es évek elején

Napjaink rendszere

CRM-IOS

SIS-EIS

DSS

ERP CKM ERP CKM

MIS

Warehouse

A jövő rendszere

The first data structures were arranged in databases (AB). As the following step, simple accountancy based company management systems, which helped the controlling of the company’s performance regarding types of costs.

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The next in scale were the development of process oriented company management systems, which welded higher management skills, accountancy modules with company real process modules. Their weakness is the low degree of data processing. As the amount of necessary information increased, management information systems appeared (Management Information Systems, MIS), and the executive information systems (Executive Information Systems, EIS). The intensive computerizing of information management technology was the basis of the development of decision supporting systems (Decision Support Systems DSS) so as to Marketing Decision Support Systems (MDR). The 90’s brought significant change in expectations for company information and decision support systems. The more sophisticated and highly integrated company management systems (ERP) came into the focus of companies. The office automation systems (Office Automation Systems, OAS) are the outcomes of the 90’s. These systems were developed for efficient management of personal and company data (text, images, calculations, documents, etc.). The following step was the development of transaction processing systems, supported by the elements of company management systems, but not in an integrated form. (Transaction Processing Systems, TPS) As a result of the development of information technology appeared interorganisational systems (Interorganizational Systems, IOS), which ensured the communication and information-current between co-operating organizations. An example of these systems is supply chain management system (Supply Chain Management, SCM) (Michelberger, 2004) One of the latest chapter of marketing information management is customer relationship management (Customer Relationship Management, CRM), which is an idea of wider sense than customer management, as it also deals with potentional customers as well. CRM systems are overcoming their operative features and developing towards decision support systems. In most cases they integrate the advantages of decision support systems with the techniques of information and process management of company management systems. Data ware houses (DW), datamining, and OLAP (Online analytical processing, OLAP) and real-time and online analytical appliances and processes are all the results of the accelerating speed of development in the technology of data collecting and processing. Nowadays’ new idea is knowledge managemnent, which assimilates the company intellectual capital and management issues. Knowledge management co-ordinates, manages and developes the stream of knowledge in order to fulfill the expectations for competences of employees and organizations. In the opinion of Hippe (2004) datamining and knowledge exploration is the newest wave of academic researches. Strategic Information Systems (SIS) are the computerized adaptation of company planning and controlling systems. One of the most popular member of this approach is BSC (Balanced ScoreCard) strategic decision support system.

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Today’s obvious requirement is the development of Company Management Systems (VIR) integrated with CRM systems. The integration ensures the improvement of efficiency regarding strategic and tactical planning, the completion of data bases. In Scholten (1998) opinion expanded ERP systems mean a new element of Interaction Sales Systems (ISS) which supports communication between sellers and buyers. ERP systems of this approach support the entire market process from the first customer contact to the postpurchase services. These systems can be considered dynamic CRM systems. Customer Information Systems, (CIS) created by Zahay and Griffin (2002) establishes and manages gateways for customers and dealers. The higher level of customer relationship integration is mostly appears in network and relationship oriented marketing practice as these orientations are the most sensitive of quality of relationship. Gibbert, Leibold and Probst (2002) declared CKM (Customer Knowledge Management) system to be an improved form of CIS systems. Their point of view is accentuating the necessity of proactive marketing information systems. The main power of CKM philosophy and is creating value and improving customer knowledge together with the customers. For companies operating on B2B markets Gregory (2000) recommends the perspetive of open manufacturing plant. He proposes a technology for managing customer relationship where company manufacturing processes are open and can be seen by customers. The other obvious and necessary fundamental principle of future systems is Optimalised Customer Interviewing System (OCIS). These systems have to include decision supporting modules with authorizations, optimalized data structure tailor-made to user and company needs. Future systems will have the following characteristics (as also shown on an illustration in the first part of this thesis)  Complete informatical integration, with penetrability between different functions and data structures  Integration with customers and partners to the required extent, management of information platforms according to customer needs, customer value orientation, applying CRM-IOS systems for communication and data collection  Knowledge management based decisions, increasing establishment and awareness, the theoretical basis of company management systems is CKM philosophy.  Opennness towards the environment and surroundings (to a reasonable extent.)

3.7.

EFFICIENT

MARKETING INFORMATION AND DECISION SUPPORTING

SYSTEMS

7. Thesis: Expectations towards efficient marketing information and decision supporting systems (MIDR) exclude statical, linear approach of MIDR. Futire MIDR systems have to be - 21


integrated with customers and partners, interactive, dynamic, real-time, differentiated according to the customer needs and sensitive to customer values. Piercy and Evans (1983), Kotler (1988, 2003), Crimp 1990, Talvinen (1994), Marshall (1996), Bauer and Berács (1998), Jobber (1999), Burns and Bush (2003) presented different marketing information and decision supporting systems in their publications, which systems are significally differ regarding their subsystems. Marketing information systems Author(s) Cox and Good, Uhl

Year: 1967.

2.

Graf

1979.

3.

Piercy and Evans

1983.

4.

Kotler

1988.

5.

Crimp

1990.

1.

6.

Proctor

1991.

7.

Bauer and Berács

1992.

8.

Sisodia

1992.

9.

Li

1993.

10. Marshall

1996.

Subsystems Supporting system Opertaional system Information-gathering system Crisis information system Information system for unforseen events Data storing and producing system Monitoring system Analysing information system Marketing efficiency analysis Marketing Intelligence system Marketing iresearch system Marketing and marketing method system Internal reporting system Marketing monitoring system Marketing research system Marketing analyzing system Internal accountant system Marketing intelligence system Marketing research system Marketing management science system Planning system Controlling system Marketing research system Monitoring system Market research Marketing observance Internal data Marketing models Statistical models Optimalizing models Expert system Data storage Input subsystem : data processing marketing research marketing intelligence Output subsystem: (marketing mix) product, place, price, promotion User interface system Software applications

Administrative support

- 22

The functions of subsystems Data collection Analysis, planning, controlling Data collection, checking Analysis, decision support Analysis Data collection Controlling, checking Analysis Analysis, controlling (internal) Data collesction, controlling (external) Analysis Analysis and decision support Collecting employee skills Analysis, controlling (external) Data collection Analysis Data insurance (internal) Determination and analysis of key factors Data collection, analysis (external) Modeling and planning Analysis, planning Controlling Analysis Controlling (external) Data collection Data collection Modeling Analysis and decision support Analysis and decision support Decision supports Analysis, controlling Data collection, controlling

Analysis, decision support, planning Hardware, interactive methods, onscreeen display, reports Statistical decision support expert system, reporting systems System manager, formalized methods, network resources Internal and external marketing


11. Jobber

1998.

12. Burns and Bush

2003.

13. Kotler

2003.

Database resources Constant internal data supplying Internak ad-hoc data Environmental monitoring Marketing research Internal reporting system Marketing intelligence system Marketing research system Marketing decision supporting system Internal reporting system Marketing intelligence system Marketing research system Marketing decision supporting system Prediction and market share measuring system

research Data collection Data collection Data collection Data collection, analysis Collecting employee skills Data collection, external controlling Data collection Analysis, decision support Collecting employee skills Data collection, external controlling Data collection Analysis, decision support Forecasting (market share estimation)

Operative marketing information systems 14. Moriaty and Swartz

1989.

15. Schumann and Schmidt

1997.

Efficiency system of sales management Direct mailing and contacting system Telemarketing system Sales and marketing management system Map generating system Analytic system Geocoding system

Data collection, realization Data collection, realization Data collection, realization Analysis and controlling Map processing Analysis of spatial relations Combination of map and table database, graphical interpretation

The development process of these systems has an apparent curve. The early trade oriented marketing styles in the 60-70’s were supported by marketing information systems which enabled data collection, arrangement, analysis and evaluation. Decision preparation and controlling remained a management task apart from the system. From the 80’s when informatical potential was increasing, the environmental awareness of companies showed upward tendency, marketing observin, monitoring systems appeared. Those are marketing analyzing systems applying methods and models on then systhematic level. At the end of the 80-90’s operative, commercial network based, trade and marketing process oriented systems came to the forefront. Show and Stone (1988) defined database marketing as an interactive marketing application, which enables personal communication and channel usage. The most important results of system development in the 90’s were decision supporting orientation (Marshall, 1996) and application of artificial intelligence in marketing together with expert systems. Talvinen and Saarinen (1995) recommend the usage of dynamic marketing information systems in order to support adaptation to the changing environmental effects. Zahay and Griffin (2002) accentuate the necessity of developing Customer Information Systems (CIS).These systems are the improved forms of customer database systems, and operating as customer oriented marketing information systems.

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We can consider CKM (Customer Knowledge Management) systems as the improved versions of of CIS systems according to Gibbert, Leibold és Probst (2002). Hess - Rubin – West (2004) examined the possibility of joining Geografical Information Systems (GIS) with marketing information systems. A special type of Commercial Information System has been created by Wright és Donaldson (2002), which application has the features of MkIS systems, but its functions and applications are restricted to commercial usage. According to Norman (2004) the development of MkIS systems had the following evolutional steps:  70’s: “hard” marketing information systems with statistical method centre  70-80’s: marketing information systems integrated “soft” marketing factors as well.  80-90’s: the creation of CRM systems, by integrating several decades’ of experience of marketing information systems  Development by integrating the idea of knowledge management, introduction of the perspective of cross-functionality by improving models and methods  Nowadays’ latest development result is customer oriented or customer integrated systems (CIS, CKM) which systems react to the growing intensity of competition, shifting the new marketing paradigm from transaction orientation towards relationship management. The earlier definition of marketing information system (MkIR) has to be change into a more complex MIDR Marketing Information and Decision Support System. Examining the development process of MIDR systems we can define the range of functions and subsystems forming more or less complex systems. In accordance with the models of company information management and decision support, the required structure of marketing information and decision supporting systems is as the following: 1. Marketing Data Collection System (MAR) i. Marketing Databases (MA) ii. Marketing observer system (MFR, external information) iii. Internal reporting system (BBR, internal information) iv. Marketing research system (MKR) v. Operative marketing data collecting system (OMIR) 2. Marketing knowledge management system (MTR) i. Method and model development system (MMR) ii. Marketing Expert system development system (MSzR) iii. Human Resources knowledge-management system (HTR) 3. Marketing analytical and prognostic system(MEPR) i. Marketing analytical system (MER) ii. Marketing prognostic system (MPR) 4. Marketing decision supporting system (MDTR) i. Marketing decision supporting system ii. Strategic marketing planning and output controlling system (MTTR)

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The relationship network of the elements of MIDR systems is very complex and sophisticated, cannot be described in a single block-diagramm. The first three sub-system (data collection, marketing knowledge management, analysis and prediction) serves the “heart” of the MIDR system (the decision support system) in constant interaction. the cycle of raising questions, collecting data, analyzing and decision is constantly renewing, as the following illustration tries to viaualize.

Marketing információs és döntéstámogató rendszer fő moduljai Maba©

Marketing Információs és Döntéstámogató Rendszer

MAR

MTR MDTR

MEPR

The sytem has to provide selective performance, sensitively considering and corresponding with the different customer values, which altogether forms the basic strategy.

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4. LIST OF PUBLICATIONS CONNECTED WITH THIS DISSERTATION 1./

Bernáth A.: Stratégiai tervezés Portfolió módszerrel, MicroCAD’89 Konferencia, Előadás, kiadványban kiadva, 1989. február 22-25.

2./

Bernáth A.: A portfolió módszerek alkalmazási lehetőségei a stratégiai tervezésben, Borsodi Műszaki Hetek, előadás, 1989. május 17.

3./

Bernáth A.: Termék-piac irányultságú stratégiai tervezés, microCAD’90 Konferenciák, Előadás, kiadványban kiadva, 1990. február 27. - március 3.

4./

Bernáth A.: Stratégiai tervezési módszerek szakértő rendszer orientált megközelítésben, Borsodi Műszaki Hetek, előadás, 1990. május 23.

5./

Bernáth A.: Termék-piac stratégia tervezését segítő keretmetodika támogatása szakértő rendszerrel, microCAD’91 Konferenciák, előadás, 1991. február 26 - március 2.

6./

Bernáth A.: Korszerű informatikai eszközök a termékbevezetés szolgálatában, microCAD’95 Konferenciák, Poszter előadás, kiadványban kiadva, 1995. március

7./

Bernáth A.: Stratégiai termékfejlesztési, bevezetési döntések, Miskolc, Publications of the University of Miskolc, Economics Sciencis, kiadványban kiadva, 1995. augusztus

8./

Bernáth A.: Döntéstámogatás a marketingben, stratégiai termék-bevezetési döntések támogatási kérdései, Miskolc, ME Gazdaságtudományi Kar, Marketing tanulmányok c. kötetében kiadva, 1995. szeptember

9./

Bernáth A.: Stratégiai döntések: termékfejlesztés és bevezetés, Marketing & Menedzsment, XXX. Évf. 1996. március,

10./ Bernáth A.: Marketingkutatási módszerek, technikák, Szimpózium’96-Miskolc, előadás, 1996. november

Miskolc,

Marketing

11./ Bernáth A.: Stratégiai szemléletű marketing információ management, Marketing Szimpózium ’96, Miskolc, előadás, kiadványban kiadva, 1996. december 3. 12./ Bernáth A.: Döntéstámogató rendszerek a marketingben microCAD’97 Konferencia, Miskolc, előadás, kiadványban kiadva, 1997. február 26-27. 13./ Bernáth A. - Serfőző O - Szabó T.: Conjoint analízis alkalmazása a gyakorlatban: Fogyasztói pizza választási attitűdök vizsgálata, Magyar Marketing Műhelyek Harmadik Kerekasztal Konferenciája, 1997. június 4-6. 14./ Bernáth A. - Szabó T.: Kinyilvánított preferenciák elemzése conjoint analízissel, „Elméleti és gyakorlati kihívások az ezredforduló gazdaságában” Miskolci Egyetem Gazdaságtudományi Kar Konferenciája, előadás, kiadványban kiadva, 1997. június 1213. 15./ Bernáth A - Szabó T.: Új lehetőségek a marketing-információ elemzésben: A conjoint analízis, Marketing & Menedzsment, XXXI. Évf. 1997/4., 1997. szeptember 16./ Bernáth A.: Termékbevezetési döntések optimálása, conjoint analízis segítségével, Magyar Marketing Műhelyek Hatodik Kerekasztal Konferenciája, előadás, kiadványban kiadva, 2000. május 31-június 2.

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17./ Bernáth A. Péhl T.: Conjoint analízis alkalmazása generátorok és indítómotorok after market piacán, Magyar Marketing Műhelyek VIII. Kerekasztal Konferenciája, előadás, kiadványban kiadva, 2002. június 5-7. 18./ Bernáth A.: Fogyasztói vevőérték a termékváltozat optimum kutatásban, microCAD 2004, International Scientific Conference, előadás, kiadványban kiadva, 2004. március 18-19. 19./ Bernáth A.: Vállalati információs rendszerek használata magyarországi, elsősorban gyártással foglalkozó kis- és középvállalkozások körében, Marketing és megoldásai szimpózium, Miskolc, 2004. december, kiadványban kiadva 20./ Bernáth A.: Vevőérték és marketing menedzsment orientációk, Marketing és megoldásai szimpózium, Miskolc, 2004. december, kiadványban kiadva 21./ Bernáth A.: Rangsorolási technikák alkalmazásának buktatói a marketingkutatásban, 2004. december, Kari kiadvány (kiadás alatt) 22./ Bernáth A.: Gépipari kis-közép vállalkozások fejlődése során tapasztalható vevőérték változások és következménye a marketing menedzsmentre, 2005. február, Tanszéki kiadvány (előkészületben ) 23./ Bernáth A.: Egyszerű rangsorolási technikák alkalmazásának veszélyei a preferencia kutatásban, Szigma, Pécs, 2005. (előkészületben)

5. LIST OF EMPIRICAL RESEARCHES CONNECTED WITH THIS DISSERTATION 1./

Bernáth A.: Stratégiai tervezés Portfoliókkal, TDK dolgozat, Országos I. Díj., szeptember, 1988.

2./

Bernáth A. - Eszes L. - Gyetvai A. - Péhl T. Veresné Somosi M. - Vállalati döntések támogatására szolgáló szakértő rendszer kifejlesztése I-III. rész., OMFB pályázat zárójelentések, 1989-1990.

3./

Bernáth A.: Szakértő rendszerek alkalmazása a termék-piac stratégiai tervezésnél, mérnök-közgazdász diplomaterv, 1990. szeptember

4./

Bernáth A. - Szintay I. - Szakály D. -– Péhl T. – Eszes L.- Bíró Z. - Gyetvai A. Veresné Somosi M. - Illyés Cs.: Szakértő rendszerekkel támogatott projektek informatikai mintarendszerének kialakítása, Ipari Minisztériumi megbízás, szakértői jelentés, 1991. január

5./

Bernáth A.: Megkérdezéses vizsgálat a Stella Artois sör várható piaci fogadtatásának felmérésére, marketingkutatás, szakértői jelentés, 1992. február

6./

Bernáth A.: A vállalati stratégiai tervezés és marketing menedzsment egyes metodikáinak feldolgozása, támogatása korszerű informatikai eszközök segítségével, egyéni OTKA pályázat, részjelentés, 1993. február

7./

Bernáth A. - Csordás T. - Juhász G. -Kiss E.: Jelentés a Corvinbank Rt. pénzpiaci pozíciójáról, lehetőségekről B.A.Z. Megyében, marketingkutatás, szakértői jelentés, 1993. május

8./

Bernáth A. - Kiss E.: Jelentés a Corvinbank Rt. pénzpiaci pozíciójáról, lehetőségekről Hajdú-Bihar Megyében, marketingkutatás, szakértői jelentés, 1993. október - 27


9./

Bernáth A.: Az MSZP Miskolc városi képviselőjelöltjei várható fogadtatásának és a választási kampány elemek tesztelése, mélyinterjú, szakértői jelentés, 1994. február

10./ Bernáth A.: A vállalati stratégiai tervezés és marketing menedzsment egyes metodikáinak feldolgozása, támogatása korszerű informatikai eszközök segítségével, egyéni OTKA pályázat, zárójelentés, 1994. április 11./ Bernáth A.: A vállalati stratégiai tervezés és marketing menedzsment egyes metodikái, BKE marketing-szakközgazdász szakdolgozat, 1994. szeptember 12./ Bernáth A.: Döntéstámogatás a marketingben, Stratégiai termék-bevezetési döntések támogatása korszerű informatikai eszközök segítségével, doktori értekezés, 1995. március 13./ Bernáth A.: Az AKZO Nobel Rt. Supralux termékcsaládja csomagolási design váltásának előkészítése, marketingkutatás, szakértői jelentés, 1995. április 14./ Bernáth A. - Piskóti I.: A Nemzeti Tankönyvkiadó Rt. általános iskola felső tagozata számára kiadott tankönyvei piacának átvilágítása, marketingkutatás, szakértői jelentés, 1995. június 15./ Bernáth A. - Piskóti I.: A Zsákújság szolgáltatás piaci lehetőségei, lehetséges marketing stratégiái, marketingkutatás, szakértői jelentés, 1995. október 16./ Bernáth A. - Borsi K. - Kovács Zs.: A borsodi régió fogyasztói magatartásának, fogyasztási struktúrájának vizsgálata, marketingkutatás, szakértői jelentés, 1995. december 17./ Bernáth A. - Borsi K. - Büdi L. - Kiss E. - Kovács Zs. - Pálfi G. - Piskóti I. - Schupler H.: B.A.Z. Megyei termék-piac stratégia alapozó kutatás, marketingkutatás, szakértői jelentés, 1995. december 18./ Bernáth A. - Büdi L. - Piskóti I. - Schupler H.: Magyarországi befektetői attitűdök, szándékok, elvárások, B.A.Z. Megye megítélése, marketingkutatás, szakértői jelentés, 1996. szeptember 19./ Bernáth A. - Borsi K. - Kovács Zs. - Piskóti I.: B.A.Z. Megye országos lakossági megítélése, országos turisztikai, médiahasználati szokások, marketingkutatás, szakértői jelentés, 1996. szeptember 20./ Bernáth A. - Schupler H.: Felmérés Debrecen város piacai környezetének vásárlói megítélésére, marketingkutatás, szakértői jelentés, 1996. október 21./ Bernáth A. - Piskóti I. - Szabó T. - Pálffy G.: A MÉH Rt. piaci pozíciójának, stratégiai lehetőségeinek vizsgálata, marketingkutatás, szakértői jelentés, 1997. április 22./ Bernáth A. - Vladár A. - Szabó Á.: Reklámhatékonysági és fogyasztói attitűdkutatás a Falco húsipari vállalat számára, Miskolc, 1997. június 23./ Bernáth A.: Volánpack Rt. csúcsvezetői információs rendszerének kidolgozása, szakértői jelentés, 1998. június 03. 24./ Bernáth A. – Piskóti I. – Schupler H. – Szántó Á.: Magyarországi tankönyvpiaci magatartást motiváló tényezők és vásárlói szegmensstruktúrák feltárása, marketingkutatás a Nemzeti Tankönyvkiadó Rt. megbízásából, szakértői jelentés, 2000. március

- 28


25./ Bernáth A.: A Toolstyle Kft vállalatirányítási rendszerének telepítését előkészítő folyamat-funkció rendszer kialakítása, szakértői jelentés, 2001. december 26./ Bernáth A.: Marketingkutatás az Imagement Kft. CLIPPER VIR szoftverévek piaci bevezetéséhez, marketingkutatás, szakértői jelentés, 2004. augusztus 27./ Bernáth A. – Piskóti I – Kerekes R – Szántó Á.: A Siemens Nemzeti vállalat kiválasztott klaszterei vevőérték kutatása, illetve beruházási környezetének vizsgálata, marketingkutatás, szakértői jelentés, 2004. december

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