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  • 标题:Research goals realising supported by double metodology approach.
  • 作者:Kremljak, Zvonko
  • 期刊名称:Annals of DAAAM & Proceedings
  • 印刷版ISSN:1726-9679
  • 出版年度:2009
  • 期号:January
  • 语种:English
  • 出版社:DAAAM International Vienna
  • 摘要:The research in this article is defined by the following research goals (RG):
     RG 1 To establish the presence and suitability of real  options, theory logic with the examples of decision  making in creation of supply chains.  RG 2 To develop a heuristic systematic approach, that  will support, on the basis of real options theory,  decision making process in the development of  production capabilities in organisational systems.  RG 3 To improve a heuristic approach so that it will  facilitate an effective interpretation of numerical  results and their support in decision making  process. 
  • 关键词:Methodology;Research methods

Research goals realising supported by double metodology approach.


Kremljak, Zvonko


1. INTRODUCTION

The research in this article is defined by the following research goals (RG):
RG 1 To establish the presence and suitability of real
 options, theory logic with the examples of decision
 making in creation of supply chains.

RG 2 To develop a heuristic systematic approach, that
 will support, on the basis of real options theory,
 decision making process in the development of
 production capabilities in organisational systems.

RG 3 To improve a heuristic approach so that it will
 facilitate an effective interpretation of numerical
 results and their support in decision making
 process.


The focal point of scientific contribution is in the realisation of RG 2. Mathematical methods which come from the transfer of logic of financial options to real options usually turn out to be very limited at managing strategic capability development. Amounts, like price movement of the underlying asset and available time to defer the decision are impossible to determine precisely.

Uncertainty which stems from several sources in capability development is impossible to determine, on the basis of extrapolation of past movements, for the present. Because of the problems of modelling, today scientific literature contains no known heuristic approaches that would represent alternative to mathematical model switch are used in evaluating investment in technical systems. The developed heuristic approach should conform to several conditions. It should have to keep the basic assumption of real options theory, like retaining flexibility in circumstances of high uncertainty and focus and realisation of decisions in conditions where circumstances become more certain. The heuristic approach has to integrate a large number of amounts that the persons making decisions see as the sources of uncertainty. Analysis of importance of identified sources and their interrelated influences must lower the bounded rationality, which the individuals are subjected to in an organisational or production system, when they decide on strategic capability development. The developed heuristic approach must allow rational transfer of objective opinions into measurable factors which will support the decision making process. The third goal complements RG 2 and represents the appositional aspect of heuristic model. RG 2 reflects scientific contribution of this work; RG 3 represents applicative expansion of the developed heuristic approach. Complex systematic approaches which are based on sophisticated mathematical models often offer measurable results which are difficult to interpret, and use them for directing the decision making process. The latter is in accordance with work by Meredith et al. (1989) who criticise the development of scientific field of operational research. With their high lighting of mathematician accuracy they decrease the applicability of models, for they do not deal anymore with complex reality of an organisational system.

Heuristic models with higher applicative weight have to be based on empirical data, even if it is qualitative, to be able to encompass interdisciplinary reality of an organisational system and provide holistic view of the examined topic. RG 2 and RG 3 try to balance adequately the desire to provide analytical measurable amounts which will direct decision making process, and wish to reflect complex reality of organisational system in the developed heuristic systematic approach.

2. METHODOLOGY

Realisation of all three research goals demands the appropriate methodological approach. For the present research double methodological approach is typical. The duality of methodological approach demands a wish for synchronisation between holistic management of analytical problem, and analytically numerical accuracy of designed heuristic approach. The first part of methodology is based on methodological approach that is used for scientific examinations of events in or organisational systems. The book used methodological approach of case study which enabled the realisation of RG 1 and start of development of heuristic model. On the methodological approach represents mathematical modelling which comes from the treasury of methodology used for describing technical systems. The distinction of double methodological approach used in this research hides in the fact that numerical model is built by taking into account the empirical reality in the examined organisational system. Commonly developed numerical models present only an abstract model of real system and are developed without the empiric qualitative foundations which define complex system reality. Use of double methodological approach presents a new development in treating these kinds of problems. Previous research leaned especially on mono-methodological approaches that either precisely described the factors which form reality of an organisational system, or the precisely modelled subsystems of the system in question and thus sacrificed holistic view to numerical accuracy. Case study methodology represents one of the most established methodological approaches in dealing with organisational systems. Many studies of authors (Eisenhardt, 1989; Gummeson, 1988; Stake, 1995; Yin, 1989) point out the importance of case study methodology. This methodology is especially appropriate when it is desired to encompass the complexity of the examined organisational system and when it is desired to closely link the examination of reciprocal dependency between the environment and the system. Yin (1989) divides case studies to descriptive, exploratory and explanatory. Descriptive case study is appropriate when researched phenomenon does not have a strong theoretical background. This kind of case study describes what kind of data was gathered for the investigation.

It stresses which data or amounts are important which can serve researchers as a conceptual model for basic understanding of phenomenon and further research. Exploratory case study is especially appropriate for inductive theory design. The goals are more explicit than in descriptive case study. Factors which influence the process have to be identified. Explanatory case study provides verification of hypotheses although case study methodology, in its basis, is not a method for rigorous verification of research hypotheses.

Stake (1995) divides case studies to intrinsic and instrumental. Intrinsic case study is used for increased understanding and familiarisation with a specific case. Instrumental case study is used when we wish to gain an insight into a wider field for theory development. In this case it is about orientation toward several case studies.

According to RG 1 the used methodology can be described as descriptive case study with addition of exploratory. Collected data and its interpretation serves as a basis for forming of the heuristic approach and is not directly focused on scientific contribution.

Nevertheless, the acquired results from the case study influence the discussion on appropriateness of the real options theory for management of strategic production capability development in organisational systems.

According to Stake's division of case studies, this research is an example of intrinsic case study. The fact that the heuristic model is designed on empiric fundaments of a single case study means that the research did not use several case studies, which would be intended for theoretical generalisations. At this point it must be mentioned that the developed heuristic approach is used in several contexts and is as such very robust. But empirical fundaments which enable content wise model formulation are not appropriate for generalisation. Categories and amounts formed in the research are specific for this case (see Figs. 1 and 2, Tab. 1).

[FIGURE 1 OMITTED]

3. CONCLUSION

Documentation and interviews with qualified individuals were used as data collection methods in studying the projects. Data interpretation was conducted in co-operation with experts for production system planning which reduces the individual's subjectivity that originates in the individual's work in the organizational system under discussion.

In-depth qualitative work in the framework of studying all three projects led to data that provided grounds for developing a heuristic systemic approach.

[FIGURE 2 OMITTED]

The approach was focused on the planning and implementation project of participation in peacekeeping operations. The reasons for selecting the above mentioned project were as follows:

* This is a project that requires the development of strategic capabilities;

* The project is not linked only to investments in individual technical systems;

* It deals with processes requiring evolutionary learning;

* The project is limited by a high level of uncertainty;

* Uncertainty can be perceived from various positions.

4. REFERENCES

Bollen, N. (1999). Real options and product life cycles. Management Science, Vol. 45, No. 5, pp. 670-684

Einsenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, Vol. 14, No. 4, pp. 532-550

Gummesson, E. (1988). Qualitative Methods in Management Research, Bromley, UK

Kogut, B. & Kulatilaka, N. (2001). Capabilities as real options, Organization Science, Vol. 12, No. 6, pp. 744-758

Ljung, L. (1987). System identification, Prentice-Hall, New Jersey

Meredith, J.; Raturi, A.; Amoako-Gympah, K. & Kaplan, B. (1989). Alternative paradigms in operations, Journal of Operations Management, Vol. 8, No. 4, pp. 297-236

Simon, H. A. (1982). Models of Bounded Rationality, The MIT Press, Cambridge, Massachusetts

Sommer, S. C. & Loch, C. H. (2004). Selectionism and learning in projects with complexity and unforeseeable uncertainty, Management Science, Vol. 50, No. 10, pp. 1334-1347

Stake, T. E. (1995). The Arto of Case Study Research, Thousand Oaks Sage, London

Yin, R. K. (1989). Case Study Research. Design and Methods, Sage Publications, London
Tab. 1. Categories (K) and Factors (D) in logistic system

K1 Dl--type of operation
Level of conflict D2--type of conflict
(what?, how much?) D3--type of action

K2 D4--distance
Geostrategic D5--relief D6--infrastructure
location (where?) D7--transportation

K3 D8--weather conditions change
Climate conditions D9--extreme conditions
(on what conditions?) D10--natural catastrophe
 D11--duration of operation
 D12--reaction time

K4 D13--public at home
Political situation D14--public world D15--strategic partnership
(frame?) D16--enemy strategic partnership
 D17--UNO resolution
 D18--inside political support at the enemy

K5 D19--own source limits
Capabilities/ D20--limits / available outsourcing
source (?) D21--delivery-food, medicaments, spare parts
 D22--communication

K6 Enemy D23--intelligence sources
(against whom?) D24--kind of defence, enemy doctrine, logistic
 D25--local civilian people
 D26--possibility of reserve activating
 D27--moral, political well for strikes
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