Collaboration Within The Tool-And-Die Manufacturing Industry Through Open-Source Modular Erp/Crm...

AIFB

Collaborative Services to MaintainElectronic Business Relationships

Dr Peter Weiß

Institute of Applied InformaticsUniversity of Karlsruhe (TH), Germany

10 September 2007Session B2. Social Network Analysis8th IFIP Working Conference on Virtual Enterprises (PRO-VE 2007)Hotel de Guimarães, Guimarães, Portugal

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PRO-VE 2007, Guimarães, Portugal, 2007-09-10, B2 Session, AIFB: Weiß

Framework of collaborative networks’infrastructure

• networkperspective

• subject ofanalysislinkages andrelatedrelationalprocessesand struc-tures

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Objectives

• Develop necessary collaborative services environment– Concept of semantically enriched business partner

profiles– Sound, proven techniques of information retrieval,

data mining, and machine learning• In focus are

– Support creation of informal structures, self-reference and spontaneous order (emergence)

– discovery and matching services– Provide field for further enhanced services and

functionality in collaborative networks

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Background and Motivation

• Concept of self-organisation is interestingly nothing newin the context of collaborative networks

• Concepts ‘organisation’ and ‘evolution’ as two antipoles oforganising and corporate governance of networked-basedorganizational structures

• Evolutionary process of spontaneous creation of order inthe sense of emergence

• Duality of structure– Modalities as intermediary

between structure and actorand the phenomenon of dualityof structure and actor;

– Signification and legitimation

structure

activity

modalitiesduality

of structureduality

of structure

(Giddens; source Dierkes 2001)

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Conceptualization of ability of systems toself-organize

- permanent re-configuration of system elements- initiated learning process

adaptivity

- self-configuration, self-management, self-development- learning aptitude- semantics for communication- subjective understanding of information

self-reference

- decentral management competence- multiplicity of qualifications- openness- conditions for admission and withdrawal

redundance

- maintenance of relationships and interactions- changing episodes of self- and extrinsic organisation- generate artificial durability- establish management processes

complexity

- produce identity through description of system- self definition- spontaneous creation of new structures between elements- loosely coupled system- create system borders- self-management, -configuration, -regulation

autonomy

Description/ abilityDimension

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Analysis of Electronic NetworksChosen Approach

• Three layerarchitecture ofadaptive businessnetworks (ICT-perspective)=> ontologies,semanticallyenrichedinformation

• Social networkanalysis=> analysisframework andmethod, relationaldata (stored inBPP)

ICT infrastructure layer

business process layer

organisational layer

net core business

supports

supportssupports

supports

interacts

withinteracts

with!

O

K!

O

K

!

O

K

!

O

K

!

O

K!

O

K!

O

K

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Approach

• Method for the analysis and investigation of relationalaspects of network structures (social network analysis)– Formal language for describing relational ties

• Facilitate communication at early stage ofcollaboration– Transfer of information between individuals– Establishment of social norms– Creation of degree of consensus (such as

cooperative behaviour, network culture, etc.)• Requires to stimulate interaction of business partners• Initiate learning process

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Design of approach for business partnerrelationship management with ontologies

BP 1 BP 2

organisational

layer

ICT

infrastructure

layer

business

relationship

management

configuration

human

agents

machine

agents

empirical

model

ontology-

based

model

collaborative

data

BP = Business Partner

BPP = Business Partner Profiles

Legend

BPPBPP

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Steps towards digital business ecosystems

Steps towards a Digital Business Ecosystem

stage 2

business partners same network

decentralized model

bp_x

RDF

Daten

RDF

Daten

bp_y

stage 1

business partners same network

centralized model

stage 3

business partners different network

decentralized model

bp_2

bp_xbp_1

bp_y

RDF

Daten

centralized

co-operation portal

RDF

Daten

RDF

bp_x

RDF RDF

bp_y

increasing virtuality

degree

bp_y' bp_x'

Daten Daten Daten

ontology-based model (e.g. in OWL)

bp_x business partner shared semantic

relationship, selecton criteria/ characteristic

search business partner/ initiate business relationship

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Typical concepts for measurement ofrelational data

• Analysis and description of quality of relations• Derived from analysis of interpersonal networks• Graph theory and matrices provide mathematical

foundations• Applied concepts:

– Reciprocity, intensity, durability, density,reachability, central

– Formal or informal structures– Centrality, centralisation

• Different levels of measurement:– Numeration: binary, valued– Directionality: undirected, directed

• Data of variables (relational data) stored in matrices

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Business Partner Profiles

market

networkstructure

intensityof linkage

trust level

flexibility

timehorizon

integrationeffort

characteristics

goaldefinition

goalbinding

profitshare

roles innetwork

informationexchange

performance

success

internet

KM, DSS,....

workflow

groupware

telework

network

requirementsproblems

applications

networkcompany

inter-networkintra-network

performance

typology

technologydegree

strategicfit

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Some more details …

a2

a1 r1inter: intensity of linkage

r2inter: time horizon (durability)

r3inter: integration effort

r4inter: flexibility

r5inter: trust level

…

1) represent information in formal way (OWL)2) compute information according to rules in ontology3) store in collaboration portal

N= networkG = (A, R1,…Rn)Ad = (a1

d,…amd)

Rik = {ri

d,k}k = {inter, intra}

range={low, medium,high} low = {1-3} medium = {4-7} high = {8-10}

ontology = rules + dataentries + dimensions

Example: R6

inter = “2” = “low”

Each relationshiprepresented by vector

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Solution for Scenario 1: CentralizedCollaboration Portal

Questionnaire

Enterprise

Save

EnterprisePortal

Business PartnerProfile(RDF)

Create

OI Modeler

Search and Discovery

KAONOntology

Assess

KAON

Modelling

Enterprise Portal

Register Query

Matching Modify Delete

KAON-Portal

KAON-API

Enterprise Portal

Register Query

Matching Modify Delete

KAON-Portal

KAON-API

services

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Summary and Outlook

• Support business relationship and partner management withinelectronic networks

• Conceptual model of the management of businessrelationships

• Combination of two strands resulted into a novel solution andtool:– state-of-the-art data analysis and management techniques

(information retrieval, data mining, social networkanalysis, machine learning, etc.)

– business partner profiling• Research is still at early stage, we presented our research

design• Next steps: choose and define complex data types

– to implement a prototype– gain real-live relational data for explorative research– simulation

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Thank you!

University of Karlsruhe (TH)Institute AIFBD-76128 Karlsruhe, Germany

Dr. Peter WeißDr. Stefan Klink{klink|weiss}@aifb.uni-karlsruhe.de

Phone: +49 721 / 608-4556

Internet: http://www.aifb.uni-karlsruhe.de/en/BIK

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Business Partner Profiles

<?xml version='1.0' encoding='UTF-8'?>

<!DOCTYPE rdf:RDF [

<!ENTITY a 'http://vfw.fzi.de/unternehmen#'>

<!ENTITY b 'vo:unternehmen2#'>

<!ENTITY kaon 'http://kaon.semanticweb.org/2001/11/kaon-lexical#'>

<!ENTITY rdf 'http://www.w3.org/1999/02/22-rdf-syntax-ns#'>

<!ENTITY rdfs 'http://www.w3.org/2000/01/rdf-schema#'>

]>

<rdf:RDF xml:base="http://vfw.fzi.de/unternehmen"

xmlns:a="&a;"

xmlns:b="&b;"

xmlns:kaon="&kaon;"

xmlns:rdf="&rdf;"

xmlns:rdfs="&rdfs;">

[...]

<rdfs:Class rdf:ID="information-exchange-performance">

<rdfs:label xml:lang="en">information exchange performance</rdfs:label>

</rdfs:Class>

<rdf:Property rdf:ID="strategic-fit-perform-is-information-exchange">

<rdfs:label xml:lang="en">strategic fit perform is informationexchange</rdfs:label>

<rdfs:subPropertyOf rdf:resource="#perform"/>

<rdfs:domain rdf:resource="#network-company"/>

<rdfs:range rdf:resource="#information-exchange-performance"/>

</rdf:Property>

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Analysis of business relationships and relatedinteractions requires an appropriate analysisframework

time

horizon

H 1

flexibility

H 6

integration

effort

H 5

markets

H 4

trust

level

H 7

intensity of

linkage

H 2

network

structure

H 3

new em

erging,

niche market

dominated

long

medium

short

low medium high

stro

ng

med

ium

wea

k

high

medium

low

high

med

ium

low

hier

achica

l

hete

rach

ical

auto

nom

ou

s

notdom

inated

type I

type II

type III

Collaboration Within The Tool-And-Die Manufacturing Industry Through Open-Source Modular Erp/Crm...

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