MONITORING OF AUTONOMOUS COOPERATING LOGISTIC PROCESSES IN INTERNATIONAL SUPPLY NETWORKS

The main contribution of this paper is to achieve measurability of the management approach of Autonomous Cooperation (= AC). This is a necessary basis for its application to business logistics and to management in general. For the practical context a measuring instrument allows International Supply Networks (= ISN) to be appraisable concerning possible effects of AC. Therefore in the following a monitoring concept of autonomous cooperating logistic processes will be presented regarding its different sub-components and discussed concerning its present options and limitations. THE NECESSITY TO OPERATIONALIZE THE MANAGEMENT APPROACH OF AUTONOMOUS COOPERATION FOR ISN International Supply Networks could be understood as an assembly of certain logistics networks (Sydow 2002, p. 10-11) alternatively supply chain webs, which are interlinked with each other. This means single firms are involved in different supply chains building up networks and such supply chain networks again compete among each other on the global market (Seebauer 2003, p. 62; Lambert et al. 1998). From such a perspective logistics management has to cope with an increasing complexity and dynamics regarding its systemic structures, as well as its processes and its coordination (Hülsmann and Berry 2004). Logistics management actors have to face higher requirements, especially in the form of intensified cooperations in logistic processes (e.g. through the integrated, company-transcending use of information and communication technologies) (Herzog et al. 2003, p. 1-2). This development of globalized logistics is even pushed, especially by the phenomena of "hyper-competition" and "hyper-linking" (Tapscott 1999; Siegele 2002). Hyper-competition results especially from an increasing world-wide intensity of rivalary among competitors and the risk of products, which could e.g. substitute presently existing services (Porter 1980). The second phenomenon occurs in the form of companies as international players (Hülsmann and Berry 2004), e.g. such as multinational service logistics providers. As there is an increasing number of actors involved in ISN between whom information processes have to take place, it becomes more difficult for the affected centralized planning unit to coordinate the immense exchange of data for an effective decision-making as well as efficient conducting of logistics activities (Hülsmann and Grapp 2005, pp. 243). From a system-theoretical perspective balancing flexibility and stability of ISN Reference: Hülsmann, M. ; Grapp, J.: Monitoring of Autonomous Cooperating Logistic Processes in International Supply Networks. In: Pawar, K.S. et al. (eds.): Conference Proceedings of 11th International Symposium on Logistics (11th ISL). Loughborough, United Kingdom, 2006, pp. 113-120 seems to be necessary to cope with complexity and dynamics (Luhmann 1973, p. 173). On the one hand organizational flexibility is needed to respond to the occuring changes and diverse environmental conditions such as technological progress (Sanchez 1993, pp. 251) by opening the logistic system ́s borders (i.e. handle service goals, e.g. to deal with orders received). On the other hand the absorbed complexity can only be compensated if stability is ensured by closures of the respective system (i.e. hold up supplier-buyer-relationships, e.g. to produce high quality in well-known structures). This process of stabilization is consequently needed for a permanent adaptation (Hülsmann and Wycisk 2005, p. 8) as well as the cited flexibilization and thereby maintenance e.g. of the ISN-existence. For realizing flexibility and stability in ISN it is assumed, that the concept of AC could contribute to improve planning and managing capacities by balancing these opposing demands. This expectation is based on the assumption, that by reducing the quantity of systems and sub-systems they operate independently towards decisions and gain more flexibility. Sub-systems (e.g. local manufacturers) get a general direction (i.e. by ISN-Management) for its decision-making and can flexibly decide within a predefined decision frame, which could be realized and manifested in organizations by processes of delegation and decentralization (Kappler 1992, p. 273). Because complexity is absorbed by an increased quantity of such decision units it is reduced to a partial complexity. This ensures stability as less coordination work is needed and failures remain in the sub-system (Hülsmann and Grapp 2005, pp. 243). However, to definitely increase the effectiveness and efficiency of managerial decisions for any company first of all it is necessary to find out its individual and optimum degree of AC. This necessity lies in the fact that AC can either have positive and negative effects. Only on the basis of the optimum degree of AC specific technological, informational and communication-related and management measures could be deduced and implemented adequately in ISN. Therefore in this paper a measurement instrument alternatively monitoring concept will be presented and discussed regarding its basic components and different functions. MONITORING CONCEPT OF AUTONOMOUS COOPERATING LOGISTIC PROCESSES & APPLICATION IN INTERNATIONAL SUPPLY NETWORKS Former research has focused on the abstract contributions of the approach of AC (e.g. Hülsmann and Grapp 2005, pp. 243). But for the adequate establishment of this conceptualization its contributions will only be manageable if they are measurable (Drucker 1954). Before the measurement instrument alternatively monitoring concept will be explained it is necessary to define its basic requirements that determine its design. Besides general design requirements there exist specific ones e.g. from measurement theory such as the need for validity or reliability (Kromrey 2000). The general requirement for the measurement instrument is, that on the one hand it should allow deduction of the degree of AC. On the other hand it is necessary to construct a consistent measurement system in which economic indicators will be integrated, in order to identify the realisability and the contributions to the objectives of AC. However dynamics of a logistic system and its processes have to be assumed (e.g. Reference: Hülsmann, M.; Grapp, J.: Monitoring of Autonomous Cooperating Logistic Processes in International Supply Networks. In: Pawar, K.S. et al. (eds.): Conference Proceedings of 11th International Symposium on Logistics (11th ISL). Loughborough, United Kingdom, 2006, pp. 113-120 real-time economy), which cause not just a static optimum of AC. It can be assumed, that the degree of AC varies over time. This is why a continous monitoring is needed for the measurement of the degree of AC on all levels of ISN, e.g. for the L1: "decision system" (management), L2: "information system" (information and communication), L3: "execution system" (material and goods flow) (Herzog et al. 2003, pp. 124). The developed monitoring concept so far consists of three sub-components: 1. Polarisation Graph (visualization) 2. Scoring Model (measurement) 3. Temporal-spatial Measurement of Validity (relativisation) Polarisation Graph In the polarisation graph the main characteristics from the definition of AC can be found: "Autonomous co-operation describes processes of decentralized decisionmaking in heterarchical structures. It presumes interacting elements in nondeterministic systems which possess the capability and possibility to render decisions independently. The objective of autonomous co-operation is the achievement of increased robustness and positive emergence of the total system due to a distributed and flexible coping with dynamics and complexity. " (Hülsmann and Windt 2005). The deduced characteristics (C1 to C5) are C1: DecentralizedDecision-Making, C2: Autonomy, C3: Non-Determinism, C4: Interaction and C5: Heterarchy. They stand for each of the illustrated dimensions. Figure 1. Polarisation Graph The polarisation graph visualizes the degree of AC based on its different characteristics named above. On a scale form 0 to 100% a higher percentage indicates relatively more AC and a lower percentage indication stands for relatively more external coordination in logistic processes. This means, that a comparison of different logistic processes and levels of a production logistic system is assumed to be possible regarding their individual degrees of AC. Finally, the sketched area between all scopes respectivley dimensions representing each characteristics of AC symbolizes the aggregated degree of AC of a single production logistic system level L1: decision system L2: information system L3: execution system Reference: Hülsmann, M. ; Grapp, J.: Monitoring of Autonomous Cooperating Logistic Processes in International Supply Networks. In: Pawar, K.S. et al. (eds.): Conference Proceedings of 11th International Symposium on Logistics (11th ISL). Loughborough, United Kingdom, 2006, pp. 113-120 (L1 to L3). How could this visualization of AC in the polarisation graph be interpreted for ISN? As a practice-orientated example a logistics service provider of the automotive industry shall be chosen for illustration. In this context a globalized car production and distribution has to be assumed. Logistic processes, transportation and technical processing of millions of cars have to be coordinated in a service-orientated ISN that consists of many locations worldwide. (Koch 2006, p. 6). The degree of AC could be determined related to a specific point in time for each logistic system level of the respective ISN. In this case each logistic system level includes in a crosssectional perspective on the different worldwide dispersed companys the relevant elements belonging to L1 (i.e. aggregated local management units), L2 (i.e. aggregated elements of local information and communication technology structure) and L3 (i.e. aggregated local production plants, machinery, persons). That means ISN-Management could identify how autonomous its