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NeP4B project — Firb 2005 — Networked Peers for Business
NeP4B
Networked Peers For Business
WP 1
Task T 1.1
Deliverable D1.0
Networks of Firms in Economic Systems:
A Methodology to Drive the Research
Questions
(Final, 12/03/2007)
Abstract –
Al fine di individuare i contesti in cui l’applicazione della tecnologia
NeP4B dia maggiori vantaggi, è stata sviluppata un’opportuna
metodologia di ricerca le cui prime fasi sono oggetto del presente
deliverable. In particolare, queste prime fasi di indagine mirano alla:
1) classificazione delle interazioni e delle relazioni esistenti fra
imprese di una rete, specialmente fra piccole e medie imprese
(PMI);
2) descrizione dei domini dove le soluzioni innovative sviluppate
attraverso il progetto NeP4B contribuiscono a migliorare le attività
dei partecipanti alla rete, sia in termini economici sia
organizzativi;
3) identificazione di differenti aree applicative dove specifiche
soluzioni tecnologiche soddisfano espliciti e latenti fabbisogni dei
partecipanti alla rete.
Per facilitare la classificazione di interazioni e relazioni, è stato
sviluppato un meta-modello che rappresenta la struttura di una
generica rete di peers. Dato che in una rete di imprese per creare
valore possono essere adottati differenti modelli di business, la rete
può assumere diverse configurazioni. Si distinguono ad esempio le
reti orizzontali e le reti verticali: le prime caratterizzate dalla
preponderanza di legami non gerarchici tra partecipanti; le seconde
generalmente costituite da un ristretto numero di leader che
coordinano le attività dei partecipanti alla rete attraverso legami
gerarchici. Indipendentemente dal modello di business adottato, ogni
rete può essere descritta attraverso un’insieme di fattori. In
particolare, il presente documento analizza la natura e le
caratteristiche dei nodi della rete ed anche le relazioni tra i nodi e le
loro peculiarità.
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La sezione 4 presenta la descrizione di due specifici domini: il polo
logistico virtuale (sezione 4.1) e la co-opetizione tra PMI nel settore
ICT (sezione 4.2). Per ciascun dominio, si analizza il contesto
economico al fine di individuare gli effetti potenziali (positivi e negativi)
dell’adozione della tecnologia NeP4B sul processo di creazione di
valore. In secondo luogo, si identificano differenti modelli di business
che possono essere applicati nei contesti precedentemente descritti.
Nel caso di poli logistici virtuali, ad esempio, sono state definite le
caratteristiche dei seguenti modelli di business:

Mercato virtuale dei servizi logistici (sezione 4.1.1)

Brokeraggio dei servizi logistici (sezione 4.1.2)
Nel caso di co-opetizione tra PMI del settore ICT, si sono rilevate le
caratteristiche di tre diversi modelli di business:

Catena organizzata

Consorzio tra pari

Consorzio a più livelli
La sezione fornisce inoltre informazioni riguardanti le relazioni
operative e sociali tra i partecipanti alle reti.
L’ultima sezione mira ad identificare le aree applicative in cui
un’avanzata infrastruttura tecnologica, quale è la tecnologia NeP4B
possa favorire il processo di creazione del valore. Le aree applicative
individuate sono:

Ricerca di partner per relazioni one-spot (sezione 5.1)

Ricerca di partner per collaborazioni a lungo termine (sezione 5.2)

Gestione dello sviluppo collaborativo di conoscenza (sezione 5.3)

Cooperazioni strategiche (sezione 5.4)
Per ciascuna area applicativa si descrivono gli scambi di dati e
servizi tra nodi indipendenti e interoperativi della rete virtuale, si
indicano i fabbisogni latenti ed espliciti che le soluzioni tecnologiche
possono soddisfare e infine si esplicitano le relazioni tra modelli di
business e aree applicative.
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D1.0 – Network of Firms in Economic
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Research Questions
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Document information
Document ID code
D1.0_v1
Keywords
Meta-model, Domain, Application Area
Classification
FINAL
Distribution level
NeP4B Consortium
Editor
NeP4B
Authors
Valentina Morandi
Larissa Rabbiosi
Francesca Sgobbi
CEFRIEL
CEFRIEL
CEFRIEL
Date
Version
Description
12/03/2007
FINAL
Final version
07/03/2007
DRAFT 0.2
Draft version
28/02/2007
DRAFT 0.1
Draft version
Date of reference
12/03/2007
Version history
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D1.0 – Network of Firms in Economic
Systems: A Methodology to Drive the
Research Questions
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NeP4B project — Firb 2005 — Networked Peers for Business
Contents
1
EXECUTIVE SUMMARY ...................................................................................................... 5
2
INTRODUCTION .................................................................................................................. 7
3
THE META-MODEL.............................................................................................................. 8
4
THE DOMAINS ................................................................................................................... 13
4.1
4.2
5
Virtual Logistics Pole................................................................................................ 13
Co-opetition among SMEs in the ICT industry ........................................................ 19
POTENTIAL APPLICATION AREAS.................................................................................. 23
5.1
5.2
5.3
5.4
Direct search for one-spot market partners ............................................................. 23
Direct search for long term partnerships.................................................................. 23
Joint knowledge management ................................................................................. 24
Strategic co-operations ............................................................................................ 24
6
GLOSSARY ........................................................................................................................ 26
7
BIBLIOGRAPHICAL REFERENCES.................................................................................. 27
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1 Executive Summary
The first step to identify a range of alternative scenarios where the NeP4B technology finds
suitable application is to define a research methodology. Accordingly, Deliverable 1.0. concerns
in addressing the three following research steps:
1) the classification of interactions and relationships among networked firms, especially of
small and medium enterprises (SMEs);
2) the description of significant domains where the innovative solutions developed by the
NeP4B project might provide economic and organisational improvements to the operations of the networked actors;
3) the identification of different application areas where specific technological solutions can
satisfy either explicit or latent needs expressed by the networked peers.
In order to address the first of the aforesaid steps, a meta-model has been identified to describe
a generic Network of Peers for Business. More specifically, different business models can be
adopted in order to create value through networked actors. From one extreme to another it is
possible to distinguish from an horizontal network to a vertical network. The former is characterised by the preponderance of non-hierarchical ties among participants. The latter business
model usually consists of a small number of leader nodes which co-ordinates the activities of
the networked actors through hierarchical ties. Apart from the fact that firms in a network should
base their activities on a specific business model, each network can be described through a series of features. In particular, the document analyses the nature and the characteristics of the
nodes of the network, as well as the relationships among nodes and their characteristics.
The second step outlined by the methodology refers to the selection and the description of significant domains of application of the NeP4B technology. Accordingly, Section 4 focuses on the
description of two domains, namely: the network represented by a virtual logistics pole (see
Section 4.1); and, the network corresponding to co-opetition among SMEs in the ICT industry
(see Section 4.2). For each domain, we analyse the business context in order to evaluate the
potential effects (positive or negative) on firms’ value creation adopting of NeP4B technology.
We identify different business models that can be applied to the above mentioned networks.
Specifically, in the case of the virtual logistic pole, we evaluate the relevant aspects highlighted
by the meta-model (e.g. characteristics of nodes, characteristics of relationships, etc.), for the
following business models:

the virtual market for logistic services (see Section 4.1.1);

brokering of logistics services (see Section 4.1.2).
Concerning the co-opetition among SMEs in the ICT industry, we focus on the following business models (see Section 4.2.1):

the organised chain;

the ‘fair consortium’;

the ‘consortium chain’.
Section 4 also provides valuable information to appreciate the operational and social relationships among peers within the two domains and for the different business models.
The last step of the analysis concerns the identification of a number of application areas (i.e. a
set of actions undertaken by firms belonging to a virtual network) where the adoption of an advanced technological infrastructure such as the NeP4B technology is expected to positively affect the value creation within the network. Contextually, the following potential application areas
are described in Section 5:

direct search for one-spot market partners (see Section 5.1);

direct search for long term partnerships (see Section 5.2);
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
joint knowledge management (see Section 5.3);

strategic co-operations (see Section 5.4).
For each application area, we describe the exchange of data and/or services among the independent and interoperable nodes of the virtual network; we briefly address which either explicit
or latent needs expressed by the networked peers the specific technological solutions can satisfy; and, finally, we indicate which business model best suits the application area.
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2 Introduction
The present document outlines the three-step methodology followed to identify a range of alternative scenarios where the NeP4B technology finds suitable application. Each step, briefly summarised below, wil
be more extensively described in the following sections.
1)
Definition of a meta-model to describe a generic Network of Peers for Business.
2)
Selection of two significant domains where the innovative solutions developed by the NeP4B project provide economic and organisational improvements to the operations of the networked actors.
The description of each domain specifies the meta-scenario for a particular Network of Peers and
provides the information to appreciate the operational and social relationships among peers. Selected
domains include:
a) the network represented by a virtual logistics pole;
b) the network corresponding to co-opetitive relationships among SMEs in the ICT industry.
3)
The aim of the NeP4B project is to develop an advanced technological infrastructure (in particular
Semantic Web, peer-to-peer and trust-based ICT applications) to enhance the economic value produced by firms in a virtual network. It is therefore crucial to identify which activities are potentially
more affected by the proposed innovative technological solutions.
Within the described domains, different application areas are identified where specific technological solutions can satisfy either explicit or latent needs expressed by the networked peers. An application area id defined as a set of actions that imply the exchange of data and/or services among the
independent and interoperable semantic peers – which behave as the nodes of a virtual network – in
order to achieve a specific economic target. The application areas allow to exploit the technical
competencies provided by the different operative units in the NeP4B project.
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3 The Meta-Model
The NeP4B project will develop a technology whose exploitation offers to economic actors new information-intensive services that will affect innovation processes and will allow to build up new activities
and/or to improve the effectiveness of the existing ones.
The application area of the NeP4B technology is a chain of production where the adoption of Information
and Communication Technologies (ICT) enables a new effective division of labour based on the specialization of each economic actor on a specific stage of the production process and on the coordination and
dynamic relationships among economic actors (picture 1).
The structure and the peculiarities of the network depend on the business model that justifies the existence of the network, or rather on the specific configuration that allows the network to create value for the
participants. The following structures are the extreme examples of the wide range of possible solutions.
1) The horizontal network predominantly bases on no-hierarchical relationships among the participants, who could stay at the same stage or at different stage of the chain of production (picture
2). The value created by the network consists by both the improvement of the effectiveness (i.e.
a more effective information flows, more swift information retrieval and product/component
finding, trust among the participants of the network,…) and the chance for each company to add
new activities to the existing ones (co-development of innovation, co-production of products and
services,…).
2) The vertical network is marked by few leaders who, thanks to authority and authoritativeness,
are able to plan and coordinate the activities of the participants in order to achieve a common
goal (picture 3). Among the other participants there could be both hierarchical and peer-to-peer
relationships. In this network, value creation comes from the improvement of the efficiency due
to the centralisation of planning (and also sometimes of the control) activities. A vertical network can extend to all the stages of a chain of production.
Independently from the business model, each network is described by a set of components (the nodes, the
relationships, the products/services and the sharing resources), whose characteristics are explained in the
following.
The nodes of the network stand for the participants who could be firms, research institutes, and public
administration agencies. The model divides the nodes into:

Internal participants: they carry out value added activities of the chain of production and regularly interact with other internal participants

External participants: they play a minor role in the chain of production (i.e., they are the end
customers or the users of products and services developed by the network, or rather they are public administration agencies that affect one or more internal participants) and/or occasionally interact with few internal participants.
In order to identify the conditions under which effective and efficient peer-to-peer constellations set up,
internal and external participants have to be portrayed by: their strategic goals; their know-how (technical,
cognitive and behavioural skills); their values (drivers of the propensity to enter peer-to-peer networks or
cooperative/coopetitive agreements).
The relationships among the participants can be qualified by:

Relationship nature: hierarchical or peer to peer. This defines the topology of the network or of a
subset of the network (hub-and-spokes, ring, hierarchical; ….)

Degree of formalization of the relationship: the relationships among participants can develop
spontaneously and informally or rather they can be ruled by “soft” contractual agreements (i.e.
consortia) or by “strong” legal contracts (i.e. repetitive sub supplying contracts)

Transaction frequency: the frequency of new transactions among the participants of the network.
The higher the transaction frequency, the more favoured are cognitive learning and behavioural
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learning among the participants of the network. As a consequence, the risk of opportunistic behaviour reduces whilst the trust increases.

Interaction frequency within a specific transaction: the frequency of interaction among participants whitin a specific transaction. The higher the transaction frequency, the more favoured are
cognitive learning and behavioural learning among the participants of the network. As a consequence, the risk of opportunistic behaviour reduces whilst the trust increases.

Stability of the relationship: this factor enables the identification of a subset of the network’s
participants among which cognitive and behavioural learning are favoured by frequent relationships and, as a consequence, the risk of opportunistic behaviour decreases and the trust among
the participants increases.

Degree of communality: degree of codification of the knowledge that is shared or co-developed
by the participants. This factor is affected by the degree of trust among peers, by the amount and
quality of the shared information, by feedback processes and horizontal evaluation processes;

Nature of communication flows: horizontal or vertical; mono-directional, bi-directional or pluridirectional; information or knowledge exchanges
The products and services offered by the nodes of the network can be described by qualitative and/or
qualitative measures. Both internal and external participants can demand product/service offered by the
participants of the network. This request triggers one or more interactive processes to which different internal participants take part.
The non-monetary resources shared by the participants of the network are information (more or less structured), knowledge (more or less codified) and goods. Procedures, routines, the involved organisational
roles and the specific relational investment that an economic actor has to carry in order to activate and
develop a relationship, vary across the type of the exchange (that may or may not include financial transactions).
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PICTURE 1- THE META-MODEL
R
a
PA
   

PA
I
I
R
I
  
R
I
    
I
I
    

R
 

  
PA
I
I
I
I
I
I
    
b
R
PA

I
Firm inside the network
R
Research Institute inside the network
PA Public Administration Agency inside the network
I
Firm outside the network
R
Research Institute outside the network
PA Public Administration Agency outside the network
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D1.0 – Network of Firms in Economic
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Research Questions
a, b: subset of economic actors among which the relationships are more stable
than those among the other participants of the ntework
Relationships features
Hierarchical equity
Hierarchical subordination

heterogeneous partners

formal relationship

frequent exchanges

stable relationship

high complexity

exchange of structured information
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PICTURE 2. HORIZONTAL NETWORK
Internal participants
External participants
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PICTURE 3. VERTICAL NETWORK
Internal participants
Leader
External participants
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4 The Domains
4.1 Virtual Logistics Pole
In past times, logistics has long been considered no strategic issue for the firm. However, the reference
framework is today completely different. As an increasing number of industries de-verticalise their value
chain and outsource a greater than ever number of activities, logistic services become value-added activities and a source of competitive advantage because they significantly affect the quality perceived by clients. Moreover, nowadays complexity of logistics activities drives firms to outsource them to third party
providers (3PLs) that supply diverse logistic competencies such as planning, implementing and controlling the flow and the storage of goods, services and related information (Ben Sassi, 2007). By outsourcing
to 3PLs, firms’ costs declined by 7-10%, logistics assets declined by 16%, average order cycle length was
shortened by 0.9-2.2 days, and overall inventories declined by 8-9% (Langley et al., 2002). However, the
increasing resort to 3PLs makes the cost of logistics explicit (Slats et al., 1995) and drives the attention of
client firms towards more efficient and effective solutions.
The above trends have supported steady growth rates of the logistic industry (over 20% per year between
1999 and 2001, according to Gordon, 2003) and the continuous evolution of the industry competitive
structure. The late 20th century saw the rise of large integrated firms (Langlois, 2002). However, the diffusion of ICTs questions this trend. By enabling a match between demand and supply, ICTs increase
market transparency, reduce transaction costs and make coordination and collaboration easier (Malone et
al., 1987). Therefore, a handful of “mega-companies” could come to dominate the 3PL world wide marketplace after a massive wage of consolidation (Gordon, 2003), but the adoption and diffusion of ICTs
could support the successful participation of specialised SMEs to co-opetitive networks which create value by sharing real time procedures to collect and allocate the demand from client firms. This scenario is
particularly appealing for Italian logistics industry that, contrarily to other countries, is highly fragmented
among approximately 150.000 small and medium 3PLs and few large companies.
The survival of small and medium Italian 3PLs passes by investing in niche strategies and technologies
that create growth via differentiation (Gordon, 2003). The NeP4B technology is expected to support these
strategies and provide incentives to cooperate in order to complete and rationalize their offer to client
firms. The NeP4B technology could foster the rise of a Virtual Logistic Pole that, by combining logistics
assets among different companies, enables the achievement of efficiency via better equipment and resource utilization.
This Virtual Logistic Pole can assume two different configurations: the Virtual Market for Logistics Service and the Brokering of Logistics Services. In the first case, logistics operators and client firms interact
via an advanced e-commerce platform to achieve real-time matching of demand and offer of logistics services. In the second case, the combination of logistics assets and the supplying of logistics services to client firms are warranted by a third party organisation (the broker) that mediates between the needs of the
involved actors. Thanks to the centralisation of decision processes, this configuration increases the probability of achieving optimal solutions, but limits the discretional and control power of 3PLs and client
firms.
4.1.1 The virtual market for logistics services
In the virtual market of logistics services, the adoption of ICTs modifies the interactions among customers and suppliers because they facilitate the comparison among the suppliers’ logistics services, interorganisational communication and the exchanges of required business documents. ICT technologies modify the bargaining between suppliers and customers and, in particular, they affect the decision making
process of client firms in the choice of logistics supplier. In the virtual market, in fact, a firm looking for
logistics services posts its requirement to a digital platform that allocates it to the most efficient providers
among available ones. Thanks to ICTs, the costs and the time absorbed by the bargaining and the selection of the suppliers dramatically decrease.
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Whilst the advantages for client firms affect support activities, the virtual market directly affects the core
activities of third party logistics providers and changes the nature of the competition inside the logistics
industry. For example, 3PLs participating in the virtual market are more exposed to opportunistic behaviours as they share strategic information with their competitors. Moreover, they have to face a greater
competitive pressure as clients can choose each moment the best available offer. However, the participation to the network also gives 3PLs the opportunity to boost their productivity and cuts the costs of
searching clients and balancing orders.
According to the framework defined by the meta-model, the Virtual Market of Logistics Service can be
described as follows (Figure 1).
Nodes of the virtual network: firms and institutions

Internal participants: third party logistics providers, client firms, companies supporting the activities of 3PLs

External participants: institutions
Figure 1 – The virtual market for logistics services
I
S
L
L
C
L
C
L
Logistics operator (3PL)
C
Client firms
S
Companies supporting 3PL
I
Institutions
C
C
L
L
C
L
I
I
S
With more details, it is possible to describe each participant as follows.
L – Third parties logistics providers: All the organisations that supply logistics services, from transportation to warehousing. Small transportation companies as well as international carriers belong to this category, that also includes providers of storage and stock management services. Logistics operators also include physical logistic poles.
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C- client firms: This group includes all the firms that require logistics services from the network (i.e.
manufacturing firms and retailers)
S – companies supporting 3PL: Firms that provide 3PL with services such as planning of vehicle routing,
real time traffic information, etc.
I – institutions: Public and private institutions that provide relevant information and affect the industry
organisational structure. In particular, public institutions provide information about local and/or regional
regulations and issue import/export license or other kinds of authorizations such as transport permissions.
Transactions within the network:
a)
Spot relationships
b) Continued relationships regulated by long-term contractual agreements.
The nature of the transactions depends on the involved participants:

(L-C), (L-L), (C-C) logistics services
The network is set up by peer-to-peer interactions between client firms and 3PL providers where
the latter offer transport and warehousing services. These interactions involve the exchange of
information and business documents such as invoices or packing lists. The network also includes
peer-to-peer interactions among 3PL providers which can subcontract logistics services to competitors. In principles, the network could also support the exchange of logistics services among
manufacturers and/or retailers selling their spare internal logistics capabilities.

(L-S), (L- I)  support services
3PL also interact with providers of services supporting their activities, as well as with private
and public institutions.
Relationships among the nodes:

relationship nature: the relationships among logistics operators (L-L) is based on their competition in the provisions of logistics services to client firms and sometimes on their cooperation to combine their heterogeneous logistics capabilities; the relationships between logistics operators and client firms (L-C), those between logistics operator and services suppliers
(L-S), and those among client firms that share spare internal logistics capabilities (C-C) can
be defined as “customer-supplier” interactions.

degree of formalization of the relationship: the supply of logistics services is regulated by
either spot or medium/long term contractual agreements. The participation to the network
partially substitutes for these contracts, because it defines a general agreed framework
which will be subsequently detailed when a specific transaction takes place.

transaction frequency: high – internal and external logistics activities are carried out daily.

interaction frequency within a specific transaction: from the demand of logistics services by
client firms (beginning of the transaction) to the issue of the invoice by the logistic operators
(end of the transaction) there are more ore less 5 interactions between customers and suppliers of logistics activities.
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
stability of the relationship: opposed to current practices, in the virtual market of logistics
services, the relationships between logistics operators and users are not stable as the network
makes the continuous selection of 3PL providers according to costs and quality optimisation
criteria a feasible solution for client firms. On the contrary, firms’ participation to the network is stable.
Critical factors:

OPPORTUNISTIC BEHAVIOUR - In the virtual market each 3PL provider risks opportunistic behaviour by the competitors who share the same strategic information. Moral hazard
risks also characterise spot relationships between clients and 3PLs.

TRUST - as logistic activities are an important source of competitive advantage for many
companies, they are protected as an industrial secret, as well as the supplier base, volume
and requirements are hid from direct competitors. Therefore, among network participants
trust plays a key role for the right working of the whole systems. However the one spot relationships that characterise the virtual market for logistics services do not favour the rising of
trust in the network.

HETEROGENOUS NATURE OF LOGISTICS SERVICE – Operative routines, tools and
information markedly differ among 3PL providers which supply heterogeneous logistics
services. The virtual market of logistics services impose to smooth those differences.

HETEROGENEITY OF TECNOLOGICAL CAPABILITIES – 3PL providers are characterised by different degrees of technological capabilities. The participation to the network
requires all participants to achieve hurdle ICT skills and culture.
4.1.2 Brokering of logistics services
The central player of this network configuration is the broker, which matches the demand and offer of logistics services. The role of the broker can be played by either a company or an institution (i.e. a trade association). In this configuration, 3PLs do not directly search for clients, but reveal their real time availability of logistics services to the broker, that optimises the use of the productivity capacity offered by the
network participants. In a similar way, clients do not directly sign contracts with specific 3PLSs, but
transmit their needs to the broker, who matches the request with the available offer from 3PLs.
According to the framework defined by the meta-model, the Brokering of Logistics Services can be described as follows (Figure 2).
Nodes of the virtual network: firms and institutions

Internal participants: third party logistics providers, client firms and brokers

External participants: institutions and companies supporting the activities 3PLs
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Figure 2 - The brokering of logistics services
I
I
C
L
L
S
C
B
L
C
B
C
C
L
C
L
L Logistic operator (3PL)
B
L
B Broker
L
C
I
C Client firms
S Companies supporting 3PL
I
Institutions
S
With more details, it is possible to describe each participant as follows.
B – Broker: The broker is usually an organisation (a company or an institutions) that supports the logistics
operators with coordination and control services.
L – Third parties logistic providers: All the organisations that supply logistics services, from transportation to warehousing. Small transportation companies as well as international carriers belong to this category, that also includes providers of storage and stock management services. Logistic operators also include physical logistic poles.
C- client firms: This group includes all the firms that require logistics services from the network (i.e.
manufacturing firms and retailers)
S – companies supporting 3PL: Firms that provide 3PL with services such as planning of vehicle routing,
real time traffic information, etc.
I – institutions: Public and private institutions that provide relevant information and affect the industry
organisational structure. In particular, public institutions provide information about local and/or regional
regulations and issue import/export license or other kinds of authorizations such as transport permissions.
Transaction within the network:

(B-C), (B-B), (L-B) provisions of logistics services
The network is characterised by peer-to-peer interactions between logistics operators and brokers, between brokers and clients of logistics services, and among brokers. The latter interaction
requires the joint optimisation of the provision of logistics services across different networks.
While the relationships between 3PLs and the brokers are generally based on medium-long term
contractual agreements, the other relationships can be either spot relationships or permanent relationships.
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
(L-S), (L- I)  support services
Brokers and 3PLs also interact with providers of services supporting their activities, as well as
with private and public institutions.
Relationships among the nodes:

relationship nature: the relationship among brokers (B-B) is based on their competition in
the supplying of logistics services to client firms and sometimes on their cooperation to
combine their skills and capabilities; the relationships between clients firms and broker (BC) as well as those between 3PLs and brokers (L-B) are “customer-supplier” interactions.

degree of formalization of the relationship: the supply of logistics services in the brokermediated network is regulated by (mainly) spot or medium/long term contractual agreements. The participation to the network partially substitutes for these contracts, because it
defines a general agreed framework which will be subsequently detailed when a specific
transaction takes place.

transaction frequency: high – internal and external logistics activities are carried out daily.

interaction frequency within a specific transaction: from the demand of logistics services by
client firms (beginning of the transaction) to the issue of the invoice by the brokers (end of
the transaction) there are more ore less 20 interactions between internal and external participants of the network.

stability of the relationship: the relationships between brokers and logistics operators are
comparatively stable, whilst the relationships among brokers and those between client firms
and brokers are volatile. For example, whenever a client firm is looking for a logistics service it can select a different broker whose offer is more suited to its fortuitous circumstances.
Critical factors:

OPPORTUNISTIC BEHAVIOUR – The lack of direct relationships with client firms and
the dependence on the broker make 3PLs more vulnerable to opportunistic behaviour of the
brokers.

TRUST – this configuration requires high trust on capabilities and reliability of the broker
from all the network participants.

HETEROGENOUS NATURE OF LOGISTICS SERVICE – Operative routines, tools and
information markedly differ among 3PL providers which supply heterogeneous logistics
services. The virtual market of logistics services impose to smooth those differences.

HETEROGENEITY OF TECNOLOGICAL CAPABILITIES – 3PL providers are characterised by different degrees of technological capabilities. The participation to the network
requires all participants to achieve hurdle ICT skills and culture.
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4.2 Co-opetition among SMEs in the ICT industry
The ICT industry: An introduction
Despite the worldwide importance recognized to Information and Communication Technologies (ICTs),
their diffusion still presents marked differences across OECD countries. New OECD data show that the
ICT investment accounted for between 0.3 and 0.9 percentage point of growth in GDP per capita over the
1995-2003 period. Australia and the United States received the largest boost (0.915 and 0.796, respectively); in Europe, Sweden (0.717), Denmark (0.674), and the United Kingdom (0.637) a lower one; while Italy (0.405), Germany (0.381), and France (0.362) a much smaller one (OECD, 2005).
In spite of the relative delay during the 1990s, the ICT eventually took off in Italy as well. Along with the
convergence among information and communication technologies, the national ICT industry has entered a
new phase of expansion and technical innovation (Iammarino et al., 2004, 2001a, 2001b) and the turnover
of the ICT market achieved 31,708 million € in 2006, with an increase of 0.8% over the previous year.
Different demand segments have contributed to the positive trend: the outstanding growth in the hardware
business – the PC sector grew by almost 12.7% in 2006 – was largely supported by investments carried
out by small and medium enterprises (SMEs) and start-ups in fast-growing sectors such as telecommunications; on the contrary, especially medium-sized and large firms drove the growth of ADSL services.
The importance of ICTs is generally argued by evidence concerning ICT-users. Nonetheless, also data
from the ICT-producers confirm the growing importance of ICTs for the whole economic system. ICTmanufacturers have shown very high rates of productivity growth, providing a considerable contribution
to aggregate performance. The ICT-based services sector (telecommunications and computer services)
plays a smaller role in the growth of aggregate productivity, yet it displayed rapid progress too. Between
1996 and 2001, the ICT services sector in Italy registered a contribution of about 0.22 percentage points
to the annual average labour productivity growth. This value is comparable to the contribution recorded in
the United Kingdom and Sweden (OECD, 2003). Some of the growth in the provision of ICT services is
due to the rise of the computer services industry. By providing key advisory and training services and developing customized software, the computer services industry significantly supported the diffusion of
ICTs among users.
Within the ICT services sector it is possible to identify different business segments, namely (i) industrial
informatics and automation; (ii) telephony, networking and security; (iii) services and internet applications; (iv) applications and software development; business software solutions; (v) multimedia; (vi) hardware retail and customer service.
SMEs and the co-opetition strategy: ICT suppliers in Italy
Besides the opportunities provided by a steady growing demand, other factors such as appropriate technical skills, change management competencies, as well as innovation capabilities play a crucial role to accrue the benefits from the ICT boost. These aspects should be carefully considered when assessing the
opportunities faced by the Italian ICT industry, which presents some important peculiarities. First, SMEs
play a leading role in the Italian ICT industry, as in the whole Italian economic system. Second, as all
over the world, processes of convergence are taking place in the ICT industry between content and media
forms, but also among different businesses (TV on mobile phones, telephone over the Internet, Internet
TV, etc).
Convergence is expected to intensify competition across the involved sectors, but ICT companies are currently still inadequately prepared to face these phenomena, and this particularly applies to the independent
and “isolated” Italian SMEs, generally unable to provide integrated end-to-end solutions to their customers.
In the above sketched framework co-operative capabilities among ICT companies become crucial skills
for survival. Specifically, in order to respond to customers requirements, as well as to compete within the
industry, a co-opetition logic (i.e. cooperative competition) of doing business (Brandenburger et al.,
1996) could benefit SMEs operating in different ICT segments. The traditional concept of business as a
"winner takes all" contest is giving way to the idea that in a networked economy companies must both cooperate and compete. This new perspective requires companies to create business strategies that capitalize
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on relationships in order to extract the maximum value from the marketplace. Internet and mobile technologies further stress the opportunities of co-opetition, because they reduce the costs of setting up and
managing both co-operative and competitive relationships by enabling information sharing and process
integrating and streamlining. In today's networked economy, co-opetition is a powerful means of identifying new market opportunities and developing business strategy.
A strong emphasis on new partnerships and a rethinking of traditional collaborations is the base to increase value for all players within the ICT industry. Indeed, leveraging co-opetition to develop business
strategy requires a thorough assessment of a company's network of players: customers, suppliers and
competitors, as well as “complementors” 1.
Such collaborations might simply involve information sharing and visibility within a specific business
segment, but they could also extend to more critical processes such as product design, planning, new
product development, and so on. Collaborations could result in either dyadic or network relationships,
eventually leading to a virtual or extended enterprise (Borders et al., 2001). It is important to note that
collaborative capabilities are more imperative for SMEs than for larger firms, as the reduced available resources constraints the capability of SMEs to adjust to changing demand and to innovate.
In order to foster the diffusion of co-opetitive networks to foster the success of SMEs in the ICT sector, it
becomes urgent to identify and describe both network strategies and network technologies providing solutions to encourage co-operation among SMEs without preventing the benefits from competitions in terms
of products innovation and price reduction.
By allowing the exchange of much richer information from a variety of data structure, rather than mere
textual data (e.g. pictures, sounds, drawings), the NeP4B technology could support inter-organizational
teams collaborating in a distributed environment. However, the widespread adoption of the NeP4B technology in support of co-opetition has to overcome some important obstacles, including data security concerns, or the definition of viable common standards and procedures.
4.2.1 Network business strategies
SMEs networks can pursue the creation of value through different business models focused on either centralization or decentralization of the decision processes. A centralized solution is represented by the organized chain (Figure 1). This business solution is characterized by a central node, either a larger firm or a
recognized institution, which co-ordinates the activities of the networked SMEs. Peripheral SMEs cooperate with the central node, but they could also compete with other network SMEs with similar specializations. The network value added derives from the rationalization of activities and processes achieved
via the co-ordination provided by the central node.
Alternative business models focused on decentralization are the fair consortium (Figure 2) and the consortium chain (Figure 3). In the fair consortium the co-opetition occurs among SMEs at then same stage
of the ICT value chain (for instance, software development, automation, etc.), while the consortium chain
involves SMEs in different segments of the ICT industry. Both the fair consortium and the consortium
chain are flat networks, where each participant links up on equal bases (i.e. same hierarchical level) with
partners. Each SME provides specialized know-how to deliver to end-clients integrated and co-developed
solutions. The network value added derives from the economies of scale and scope allowed by cooperative mechanisms and from the continuous search for efficiency induced by competition.
1
Complementors - a term coined by Brandenburger and Nalebuff (1996) - are those companies that provide products and services that enhance the value of a firm's products or services. For example, software
providers are complementors to hardware providers, and vice versa.
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Figure 1 – The ‘organized chain’
F
F
F
F
CN
CN
F
F
SME operating within the network
F
SME operating outside the network
F
F
Central node
PA
Institution outside the network
PA
Figure 2 – The ‘fair consortium’
F
PA
F
F
F
F
F
F
F
PA
Figure 3 – The ‘consortium chain’
F
F
PA
F
F
F
F
F
F
F
F
F
F
PA
F
F
F
F
PA
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According to the framework defined by the meta-model, the outlined business models in the co-opetition
domain can be described as follows.
Organized chain
Transactions within the network: commercial transactions (exchange of products and services) and strategic transactions (joint development of product and process innovations).
Nodes of the virtual network: central node (large firm or institution), ICT SMEs, customer and supplier
firms, institutions.

Internal participants: SMEs operating in ICT industries, large firm (or organized institutional community).

External participants: institutions, customer firms.
Relationships among the nodes:

relationship nature: hierarchical cooperation between the central node and the peripheral nodes. Possible competition among peripheral nodes.

degree of formalization of the relationship: formal contractual agreements when the central node is a
firm; less detailed framework agreements when the central node is an institution.

transaction frequency: although there is no prearranged transaction frequency, the commitment of the
central node guarantees a minimum amount of transactions within a specific period.

interaction frequency within a specific transaction: the variety of the transactions affects the interaction frequency. Hence, sometimes interactions are very frequent (e.g. co-working on a project), and
sometimes are not (e.g. purchase of a specific component).

stability of the relationship: due to the presence of the central node, the relationship is expected to be
stable, although this may also depend upon the turbulence of the industry.
Fair consortium / Consortium chain
Transactions within the network: commercial transactions (exchange of products and services) and strategic transactions (joint development of product and process innovations).
Nodes of the virtual network: ICT SMEs, customer and supplier firms, institutions.

Internal participants: SMEs operating in ICT industries.

External participants: institutions, customer firms, supplier firms.
Relationships among the nodes:

relationship nature: heterarchical (Hedlund, 1986) cooperation and competition (i.e. co-opetition)

degree of formalization of the relationship: no ex-ante formal relationship exists between the nodes,
but the framework agreement which sets the participation rules to the network. Transactions within
the network require additional (formal or informal) contracts.

transaction frequency: the absence of a formal hierarchical organization affects the frequency of the
transaction among participants. There is no prearranged transaction frequency, since agents interact
on a voluntary basis and through different types of collaborations. Hence, the nature of the transaction affects the transactions frequency, which could be high (e.g. information sharing), or low (e.g.
partner search, new product development).

interaction frequency within a specific transaction: the variety of the transactions also shapes the interaction frequency. Hence, sometimes interactions are very frequent (e.g. co-working on a project),
and sometimes are not (e.g. information sharing).

stability of the relationship: as no formal relationship exists, relationships turn out to be unsettled and
their stability cannot be predicted in advance.
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5 Potential Application Areas
5.1 Direct search for one-spot market partners
Inter-firm transactions involve either one-spot contracts or longer term agreements. One-spot contracts
increase the flexibility of the client firm, favour a better match between the client’s needs and the provider’s offer and allow the client firm to exploit the benefits of competition among suppliers. One-spot contracts are particularly efficient when transactions involve low-strategic standardized products.
However, searching for the best partner every time a transaction takes place is time consuming (especially
when the number of potential partners is large and transactions frequently repeat), costly (partners have to
agree on a specific contract for each transaction), and risky (firms continuously face the trade off between
the cost/time of assessing the partner trustworthiness and the risk of opportunistic behaviour). The less the
market transparency, the higher the cost and risk of one-spot transactions against longer term agreements,
the higher the chance that firms will accept second-best solutions and lock themselves into a reduced
number of longer term agreements with few well known partners.
The NeP4B platform is expected to increase the transparency of the market by:

reducing the costs and time needed to find which suppliers offer the best technical and economic solution;

easing the comparison between the offers from different suppliers;

facilitating the assessment of the potential partner’s trustworthiness.
Consequently, the NeP4B platform is expected to increase the resort to one-spot market contracts when
firms directly interact for transacting low-strategic standardized products.

Critical issues: information retrieval; efficiency gain trade-off (benefits vs. costs); feedback systems.

This Application Area best suits the following business models in the chosen Domains:
-
Virtual logistic pole/Virtual market for logistics services
-
Co-opetition among SMEs in the ICT industry/Fair consortium
-
Co-opetition among SMEs in the ICT industry/Chain consortium
5.2 Direct search for long term partnerships
Partners will probably look for a long term agreement when:
a)
uncertainty is high;
b) the transaction concerns strategic core activities;
c)
the transaction itself takes a significant time to develop.
This is the case of R&D co-operations, joint development of commercial networks, co-design agreements,
etc.
The process of partners selection plays a key role to ensure the success of the whole transaction and requires to apprise the potential partners along several dimensions, from technical and organizational features to the partner mission, to strategic goals. However, public information is often too poor or dispersed
across different sites and supports to effectively help the selection process.
The NeP4B technology is expected to pull out deeper and meaningful information (data, imagines, drawings, etc.) from diversified public and private sources such as web pages, directories, tapes, videos, demos, etc. The access to these different sources is regulated either by an institutional actor or by formal/informal agreements among the participants to the network.
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
Critical issues: information retrieval; trust; feedback systems.

This Application Area best suits the following business models in the chosen Domains:
-
Virtual logistic pole/Brokering of logistics services
-
Co-opetition among SMEs in the ICT industry/Fair consortium
-
Co-opetition among SMEs in the ICT industry/Chain consortium
-
Co-opetition among SMEs in the ICT industry/Organized chain
5.3 Joint knowledge management
After a relationship has established, partners start to socialize their information and knowledge and to
create new one. Effective knowledge management is crucial to increase the benefits from long term partnership. In particular, knowledge management becomes more and more critical as knowledge sharing
shift from support activities to core activities (e.g., from invoices to technical drawings for manufacturing
companies) and knowledge contents switch from standardized information to co-developed new
knowledge (e.g., from existing public SW programmers to a new SW architecture).
It has to be noted that also the complexity of social interactions among partners increases as knowledge
management becomes more challenging.
The NeP4B technology is expected to support joint knowledge management in long term relationships by
facilitating the transfer and sharing of different types of knowledge and information.

Critical issues: partners commitment to the long term relationship; trust; data and knowledge transferability.

This Application Area suits all the business models identified in the chosen Domains.
5.4 Strategic co-operations
Growth and possibly survival of SMEs is frequently questioned by the limited available resources which
limit the provision of customized and/or innovative products. Strategic R&D co-operation aimed at developing integrated solutions or new products constitutes a promising path to overcome those constraints.
Integrated solutions involve the development and supply of customized architectures which combine the
products and/or services independently provided by different networked SMEs. The development of a
new product implies the co-operation among partners during the stages of product development, codesign and/or engineering.
When firms start a strategic co-operation they have to select partners and projects (for partners selection,
see the Application Area “Direct search for long term partnerships”), co-ordinate activities during the cooperation, and eventually choose an exit strategy.
Each of the above actions consists of several distinct steps that impact on the overall co-operation success
or failure. For instance, a strategic co-operation to develop and integrated solution requires the dynamics
definitions of norms and procedures to: (i) modify products and services; (ii) share strategic targets; (iii)
drive the decision process; (iv) access the required documentation; (v) standardize the interfaces between
the modules provided by different partners; (vi) provide feedback. Up to now, the exit from a collaboration has still been poorly explored by the literature. However, the process could require to: (i) guarantee
the availability of the integrated solution in the future; (ii) decide how the investments in the collaboration
could be recovered; (iii) promote the involvement of new actors in the project.
It is clear that both the provision of integrated solutions and the development of new products are characterized by high complexity in social and technological interactions among partners.
The NeP4B technology is expected to support strategic co-operation among SMEs by facilitating the dynamics definitions of norms and procedures to manage the different steps of the collaboration process.
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
Critical issues: partners commitment; trust; change management; feedback systems.

This Application Area suits all the business models identified in the chosen Domains.
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6 Glossary
Behavioural Learning. Learning-by-doing process where information collected in subsequent interactions improves the capability to interact with partners.
Business Process. Set of organized activities that enable to achieve a valuable goal that is of value for internal or external customer/receiver. By combining of business processes companies create value.
Chain of Production. Sequence of processes from the raw materials to the end-product. The production
chain can be managed by a single organisation (vertical integration) or can be shared among several economic actors through the division of labour.
Cognitive Learning. Learning-by-doing process that enhances the effectiveness of operational and decisional activities. In a relational network, cognitive learning gradually improves the benefits of network
participation, as the cumulated experience makes the participants learn how to coordinate, which skills
are available, etc.
Division of Labour. Specialisation of labour in specific, circumscribed tasks and roles, and their allocation to people or organisations according to efficiency criteria
Economic actor. A player in the economic system, defined as a set of people and organisations who set
up relationships in order to satisfy the individual needs by the allocation of scarce resources (goods or
services)
Opportunistic Behaviour. Unfair behaviour in a contractual agreement under information asymmetry.
Pre-contractual opportunism occurs when, during the drawing up of the contract, needed information is
not completely available or verifiable. Post contractual opportunism occurs when the actions specified in
the contract cannot be completely observable by the contractors.
Organisational role. Position in an organisation defined according to the tasks and skills needed to perform successfully the assigned duty.
Procedure. Formalised sequence of instructions to execute an activity or a process. It can be detailed by a
document or can be embedded in a tacit routine.
Production Process. Set of activities that by adding value (transformation by manufacturing and/or assembly) to an input (raw materials or semi finished products) produce an output (semi finished or endproduct) for an internal or external customer.
Routine. Rule-guided behaviours emerging from testing and selecting sets of actions to achieve a target.
Routines allow to embed, stabilise and keep procedural innovation, making it transferable and replicable.
Specific Relational Investment. An investment needed to establish a relationship whose value dissolves
or significantly decreases outside that relational set. When economic actors undertake high specific investments they expose to the risk of opportunistic behaviour. They could be forced o agree to unfavourable conditions in order not to lose their investment.
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7
Bibliographical References
Ben Sassi, S. 2007. The Dynamics of the economic organization of the logistics sector, paper presented to
“Internal Organisation, Cooperative Relationships among Firms and Competitiveness”, Lucca, 1920 January.
Borders, A.L., Johnston, W.J., Rigdon, E.E. 2001. Beyond the dyad: Electronic commerce and network
perspectives in industrial marketing management, Industrial Marketing Management, 30, pp. 21–33.
Brandenburger, Adam M., Nalebuff, B. 1996. Co-opetition: A Revolution Mindset That Combines Competition and Cooperation, New York: Doubleday.
Gordon, B.H. 2003. The changing face of 3 rd party logistics, Supply Chain Management Review, MarchApril.
Hedlund, G. 1986. 'The Hypermodern MNC - a Heterarchy?' Human Resource Management, 25, pp. 925.
Iammarino S., Jona Lasinio C., Mantegazza S. 2001a. “Sviluppo e diffusione dell’ICT: l’Italia negli anni
‘90”, Studi e note di economia, 2, pp.13-44.
Iammarino S., Jona Lasinio C., Mantegazza S. 2001b., “The regional dimension of the ICT industry in
Italy: a preliminary description”, Economia e Politica Industriale, 110, pp. 153-169.
Iammarino S., Jona Lasinio C., Mantegazza S., 2004, “Labour productivity, ICT and regions: The revival
of Italian “dualism”? SPRU Electronic Working Paper Series, Paper No. 127.
Langley, J., Allen, G., Tyndall, G., 2002. Third Party logistics study – Results and findings of the 2002
seventh annual study, Cap Gemini Ernst Young, George Tech and Ryder Logistics, Atlanta.
Langlois, R.N., 2002. The vanishing hand: the changing dynamics of industrial capitalism, University of
Connecticut Working Paper.
Malone, T.W., Yates, J., Benjamin, R.J. 1987. Electronic markets and electronic hierarchies, Communication of the ACM, 30 (6).
OECD 2003, ICT and economic growth: evidence from OECD countries, industries and firms – ISBN 9264-10128-4.
Slats, P.A., Bhola, B., Evers, J.J.M., Dijkhuizen, G. 1995. Logistic Chain Modeling, European Journal of
Operational Research, 87, pp.1-20.
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