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CONFERENCE PROCEEDINGS
14th Toulon-Verona Conference “Organizational Excellence in Services”
University of Alicante - University of Oviedo (Spain) – September 1-3, 2011
pp. 379-392 – ISBN: 978 88904327-1-2
New technology for Strategic Management Policy in Small Areas:
the ‘GIS Piedmont region’
Monica Cugno, Scilla Angela
Business Economics Department – Economics and Business Management Section
C.so Unione Sovietica, 218/bis
10134 – Torino
Phone (+39) 011/670.60.51 Fax (+39) 011/670.60.52
E-mail: [email protected]; [email protected]
Abstract: The report describes the results of a pilot project on strategic management policies in
business-area systems carried out with the objective to experiment with alternative methods of
delivery and analysis of the geospatial data. This has been constructed through integration
between three components open-source licenses: a geographical information system (GEODATA), a
data analysis programming language and environment (R) and a database system (PostGIS).
The analysis introduces an ad hoc advanced quantitative methodology for the strategic
management policies of small-sized business-area systems.
The making of this study was organized into phases:
1. Creation of a set of indicators to measure the phenomenon.
2. Identification of variables, data collection and data analysis methodology.
3. Detection of any business-area system clusters and/or of spatial outliers.
The system – called ‘GIS Piedmont region’ – is currently available in its prototype form with data of
the Piedmont region (North Italy) for the period from 2000-2010, that can be integrated with new
information, geographic and statistic tools.
Keywords: Strategic Management Policy, Indicators, Exploratory Spatial Data Analysis, Cluster, GIS
1. The problem
Over the past decade, the economic changes that have affected all modern economies have
outlined a new concept of territory, less and less identified with the physical and spatial extent of
a place but as a social organization, resulted from the interaction of relations among the actors
who are embedded in it [Golinelli C.M., 2002].
The territory becomes a strategic asset for local development which is meant as the result of
collective actions made possible by the common belonging to it and as a strengthening of all
potential resources that reside in it.

Although this paper is based on collaboration, Monica Cugno, Ph.D., is to take credit for paragraphs 3, 4 and 6; and Angela
Scilla is to take credit for paragraphs 1, 2 and 5.

Monica Cugno, Ph.D. in Statistics Applied to the Economic and Social Sciences – University of Padova. Now is Professor of
Economics and Business Management at the Faculty of Economics  University of Torino.

Angela Scilla, Ph.D. Student in Business and Management – University of Torino.
One of the most direct consequences of globalization is the extension of the concept of
competition to the territories as systems which are more or less able to create within themselves
the conditions for economic and social development, since they support the local firms and attract
new entrepreneurship from the outside [Golinelli, 2000; Barile, 2006; SINERGIE, 2007; Tardivo,
2007]. In other words, the territory and its networks [Rullani, 2004, 2006, 2008] play a key role in
the enterprise innovative dynamics thanks to typical features, which are the determinants of
strategic and decision making processes of the business system.
There are numerous contributions that have highlighted the need to explore the external factors
that affect the competitive success of the company [see, among others: Porter, 1990; Salone,
2005; Garofoli, 2003; Caroli, 2006; Favaretto, 2006; Camuffo and Grandinetti, 2006; Viassone,
2008; Tardivo and Cugno, 2011].
The factors that affect the competitive success (externalities) must be identified and interpreted as
changing and dynamic phenomena. They must be studied over time and space, considering the
production, economic and social changes, which characterize the local context.
On the one hand if today there is no doubt about the importance of externalities, on the other
hand there are discrepancies and gaps in the methodological approach and in the analytical
instrumentation support. Contributions aimed to propose set of indicators, to validate the
usefulness of methods of multidimensional analysis and/or storage system, analysis and return of
the information, in fact, are still limited in number and overall they cover only part of cognitive
demand.
It should be noted that a fair share of research in the this field is taking shape outside the area of
the study of strategic management and is prepared for purposes which are different from those
of the business world. Consequently, it “suffers” a limited sensitivity to the managerial
implications of the production system as a whole or of the individual business units.
One aspect, up to now neglected, regards the creation of an information system that is suitable
not only for the study of all possible aspects of the facts but at the same time simple enough to be
used by both expert and less experienced users.
Such a system must be capable of organizing information with different levels of territorial detail
and be produced, up-dated and implemented with a restricted cost.
Such an objective could be achieved thanks to the recent development of geographic information
systems (GIS). These allow for the placing side by side of the traditional mechanisms of filing and
analysis of the data with instruments that permit one to unite the information to the territorial
position, that facilitate the user-friendly consultation with different levels of aggregation, the
realization of spatial analysis and risk maps.
The original result is an open-source structure useful to back up the operations of the local
decision makers in the strategic management policies. The application – called ‘GIS Piedmont
region’ – is currently available in its prototype form with data of the Piedmont area for the period
of 2000-2010, but easily extendible to Italy.
The article is structured as follows: the second paragraph highlights the special features of
competition between territories; in the third paragraph there is reference to the characteristics of
the system and to the integration between its components; the fourth paragraph will introduce
the architectural parts of the project under examination and the resolution of problems for
realization; the fifth paragraph shows the example of the application of GIS; the ideas that evolve
as a result of the work and that establish directions useful for future development will be given in
the conclusion.
2. Peculiarities of the territorial competitiveness
According to an analysis of the major contributions to the enhancement and management of
territories [Golinelli C.M., 2002; Caroli, 2006; Rullani, 2008;], a territory is competitive if it is able
to compete in the market ensuring, at the same time, an environmental, economic, social and
cultural sustainability based on the organization in the network and on inter-territorial forms of
articulation.
A competitive territory attracts capital and people. It also allows firms located there to get better
results than those obtained elsewhere. Since a competitive territory enables the production and
exploitation of externalities then it is able to increase the resource efficiency and to attract them.
It should, first of all, understand what are the elements that compose the territory in such a way
to decide what to focus on.
In addition, the development of the territory cannot disregard the involvement of institutions,
local actors and policy makers, who should acquire four types of skills:
1. ability to enhance the environment,
2. ability to take joint action,
3. ability to create links among different sectors in such a way to keep on site the most valueadded,
4. ability to make contact with other areas and with the rest of the world.
These four skills can be related to the “four elements” of territorial competitiveness, which are
combined in a specific way in each territory, or rather:
 “social competitiveness”: ability of the actors of the area to act effectively together on the
basis of a common conception of the territory;
 “environmental competitiveness”: ability of the actors of the area to enhance the
environment because it is a “distinctive” element of their territory, ensuring , at the same
time, the protection and renewal of natural and heritage resources;
 “economic competitiveness”: ability of the actors of the area to produce and maintain
within the territory the maximum of the value-added, combining effectively the resources
in order to enhance the specificity of local products and services;
 positioning in the global context: ability of actors of the area to find their own position in
relation to other areas and the outside world.
Very often the territories present ambiguities as regards their geographical location, because their
natural or economic-social boundaries may not coincide with those of the institutions.
This leads us to the problem to identify the skills or possible partnerships among the different
actors interested in the development of the considered area.
In order to overcome these limitations, we wanted to carry out this work. For its development we
need 5 steps:
1. selection of the units of analysis,
2. definition of the panel of indicators,
3. identification of sources of data and retrieval of new information,
4. creation of a geographic information system,
5. data analysis.
3. The creation of the structure: integration between GeoData, R, Postgis
The creation of a GIS must consider some indispensable steps in order to function well: the system
must be capable of loading and up-grading the spatial database and the attributes which are at the
heart of the system. The information may be internally produced (through the statistic and
geographic tools provided for by the system) or through external processing systems.
The proposed system is born from the integration1 of GeoData [Anselin, 2004], R (R Development
Core Team, 2009) and PosGIS (PostGIS, 2011) and guarantees:
 the non-standardization of the structure, that can be enriched with new analysis instruments
through the simple implementation of the statistic and geographic tools;
 the possibility to up-date/modify the available data, without the necessity of re-designing the
structure;
 the flexibility of the examinations depending on the requirements of the people involved.
The possibilities of analysis with GeoData are increased thanks to the utilization of spatial tools
[Bivard, 2003; Bivard et al., 2000]. This analysis is made possible thanks to the libraries (see table
1) available in the Cran R [http://www.r-project.org] or through the creation of new libraries.
The quality of the information produced and diffused by the structure is however not without
problems of accuracy. Distortions originate from the degree of aggregation of the territorial data
available and/or from the transformations they could undergo in order to make possible
processing and the desired analysis [Openshaw, 1987].
Table 1 – Principal packages on CRAN R
Macro-Area
Connection
R-PostGIS
Point Pattern
Analysis and
geostatistics
Lattice/
Area data
Package
Author/s
RpostGIS
Solymosi et al. 2006 Read the maps through the ODBC connection and
transformed or generated by the PostGIS and GEOS
functions to the R system to apply further operations
Spatial
Hornik et al.
Include: variogram/correlogram functions, surf.ls(.)
Else See Ripley 2002 and surf.gl(.) for trend surfaces and kriging, and
prediction functions
spatstat
Baddeley et al. 2005 Spatial Point Pattern data analysis, modelling and
simulation including multitype/marked points and
spatial covariates
splancs
Bivand 2000b
Spatial and Space-Time Point Pattern Analysis
Functions
geoR
Ribero et al. 2003
Model-based geostatistics
geoRglm
Ribero et al. 2003
Functions for inference in generalised linear spatial
models. The posterior and predictive inference is
based on Markov chain Monte Carlo methods.
Extension to the package geoR
Spdep
Bivand 2003– with
contributions by
Anselin et al. –
Spatial dependence: weighting schemes, statistics
and models
DCluster
Goméz-Rubio et al.
2005
A set of functions for the detection of spatial clusters
of disease using count data. Bootstrap is used to
estimate sampling distributions of statistics
Maps
Brownrigg 2005
Display of maps
projmap
Maps
1
Main objective
Projection code and larger maps
Maptools
Bivand 2003
Set of tools for minipulating and reading geographic
data, in particular ESRI shapefile; c code used from
shapelib
Mapdata
Bivand 2003
Supplement to maps package, providing the larger
and/or higher-resolution data-base
Shapefiles
Stabler 2005
Functions to read and write ESRI shapefile
Proportional
symbol maps
Tanimura S. et al.
2006
Providing a function and some examples
On the problem of integration, see also Bivand et al, 2000.
Interactive
exploratory spatial
data analysis
GeoXP
2
Laurent et al. 2006
Interactive exploratory spatial data analysis
(measured at geographical sites or geographical
zones) and coupling between a map and statistical
graph
Sourse: Our processing
4. The ‘GIS Piedmont region’
Given the necessity to organise highly detailed information (see the UE DIRECTIVE, CARE PROJECT), the
elementary facts taken into consideration are: the region, the district, the metropolitan area of
Turin, the towns, the number of kms of the main roads network (outside of the urban centres) and
motorways.
To meet with the different examinations the “GIS Piedmont region” makes use of:
A) an ad hoc indicator panel (see Table 2) which provides clear signals in real-time of
efficiency/effectiveness, in relation to the virtuous or emergency situations present in the
context [Cugno, 2008]; we have identified three dimensions of indicators:
1. Territory, environment and infrastructures
2. Socio-economic aspects
3. Competitive level of the community
Each dimension was split into sub-dimensions and each of this into subcomponents:
B) a set of maps that can be consulted interactively. By clicking on the map the user can obtain
the numeric details of the parameters under consideration or supplementary information on
the facts and the territorial or infrastructural characteristics of the zone.
2
Download: http://w3.univ-tlse1.fr/GREMAQ/Statistique/geoxppage.htm [October 2009]
Table 2 – Set of indicators to analyze competitive advantage or vulnerability sources
TERRITORY, ENVIRONMENT
AND INFRASTRUCTURES
TERRITORY
 area
 altitude
 amount of mountain
communities
 protected areas*
 coastal areas in Km**
ENVIRONMENT
 urbanization
 seismicity
 Flood
INFRASTRUCTURE
 roads and motorways in Km*
 railways in Km*
 amount of airports**
 amount of ports**
 amount of hospital and dayhospital bed-spaces**
 Universities
SOCIO-ECONOMIC ASPECTS
COMPETITIVE LEVEL OF THE COMMUNITY
(by macro sector)
DEMOGRAPHIC ASPECTS
LOCAL UNITS
 residents
 house/apartment density index
 old-age index
 underage density index
 feminization rate
 amount
 LU density index by Km2
 LU localization quotient
FAMILY AND HOUSING
 family
 cohabitation
 amount of wedding services
(civil, religious, total)
 houses/apartments
 house/apartment density index
FOREIGNERS
 amount of foreigners (by gender
and country of origin)
 underage density index
 feminization rate
JOB MARKET
 amount of employed persons
 employment rate
 activity rate
 unemployment rate
 youth unemployment rate
COMMUTING
 commuting
WASTE
 waste quantity
 recyclable materials quantity
 percentage of recyclable
materials
 waste per resident
FOREIGN TRADE
 import volume*
 export volume*
DOMESTIC TRADE
 amount of shopping centers (by:
dairy and food products, nondairy and non-food products,
mixed products)
 amount of local retailers (by:
dairy and food products, nondairy and non-food products,
mixed products)
 amount of newsagents
 amount of cafés
 amount of restaurants
 amount of pharmacies
 amount of post offices
BANKS AND CREDIT
 deposits
 jobs
 amount of tellers
TOURISM
 amount of beds in hotel
facilities;
 amount of beds in non-hotel
facilities;
 amount of museums and state
galleries, monuments, state
archeological sites, art
institutes
 arrivals
 attendance
OTHER TOURIST ATTRACTIONS
 cultural services (religious and
non-religious traditions,
cultural events)*
 leisure services: farm holiday
services, specific services
(trekking, cycling…)
 sporting events*
 amount of disco clubs,
ballrooms…*
 beauty and wellness services*
 local products*

*Unavailable datum at a town level ** Irrelevant datum  Census data
Souse: Our processing
The predisposition of the instruments sub A) and sub B) have rendered indispensable the
individualization and validation of opportune analysis instruments implemented to generate the
desired information.
The heart of the GIS‘Emergency Map Open Source’ – PostGIS – (see Figure 1) is made up of:
a) spatial database, for the cartographic representations;
b) database features, for measuring the levels of competition/vulnerability.
The latter are made up of existing records and must be up-dated by means of the
insertion/modification of the data as it is made available.
Figure 1 – The structure of GIS ‘Piedmont Region’
Source: Our processing
For the construction of the database, there have been integrated and duly enlarged upon [Cugno,
2008], after a careful evaluation of the comparability, more data sources (see Table 2).
The data have been stored in such a way as to guarantee the levels of aggregation desired or
rather maintaining the information: accurate only for the towns; areas (towns, districts, provinces
and regions).
The layers currently loaded are of a vector type: points, towns/districts centres; polygons, towns,
districts, provinces and regions (see Piedmont region Cartographic collection:
http://www.regione.piemonte.it/repertorio).
The information may be internally produced (through the statistic and geographic tools provided
by the system –GeoData –) or through external processing systems – R – .
5. Worked examples
The previously built architecture allows us to refer to a geographic information system
automatically, leaving the user the choice of the detail:
 macro-area level (e.g. Region)
 intermediate or sub-area level (e.g. Province)
 micro-area level (e.g. Town)
In addition to the geographical perspective, the phenomenon can be investigated through a
thematic (by attributes such as images, sounds, text, etc..) and/or time perspective.
The choice of GIS allows the user to consult the maps interactively allowing to obtain additional
information about the phenomenon and the spatial or infrastructure features of the area, clicking
on the map.
An example of the work done is then illustrated through the application of ‘GIS Piedmont Region’ in
the job market.
The job market is certainly demonstrated a strategic resource for determining the levels of
competitiveness/vulnerability of a territory.
The job market, for its economic and social centrality, is one of the dimensions of company life
investigated especially at the municipal level.
By limiting the analysis to the main statistical indicators we have taken into consideration:
 activity rate
 employment rate
 unemployment rate
 youth unemployment rate
The support of cartographic representations (see Table 3, 4, 5 and 6) of the indicators considered
allows us to perceive accurately the relationship among the measured phenomena. Administrative
areas where the employment rate is more important are also those where there is the higher
propensity for people to see themselves like part of the labor force. Moreover, the largest
thickenings are independent of the provincial border.
Table 3 – The job market maps in the Piedmont Region – Activity rate per 100 inhabitans
N
W
E
S
Limite provinciale
Nessun o
<=43 .5
43.5 - 4 7.5
47.5- 50
50.01 - 53
>5 3
Source: Our processing
0
10
20
Km
Table 4 – The job market maps in the Piedmont Region – Employment rate per 100 inhabitans
N
W
E
S
Limite provinciale
0
<=40
40 - 45
45 - 48
48- 50
>=50
0
10
20
Km
Source: Our processing
Table 5 – The job market maps in the Piedmont Region – Unemployment rate per 100 inhabitans
N
W
Limite provinciale
E
S
Nessuno
<=3
3-4.5
4.5 - 5.5
5.5- 6.5
>6.50
0
Source: Our processing
10
20
Km
Table 6 – The job market maps in the Piedmont Region – Youth unemployment rate per 100 inhabitans
N
W
Limite provinciale
E
S
Nessuno
<=8
8.01 - 12.5
12.51 - 17
17.01 - 22
>22
0
10
20
Km
Source: Our processing
In the level sub-area, for all indicators, we can see that there are large portions of area that serve
as ‘pull’, areas which stop the virtuous effects and other areas that are placed in an intermediate
position. However the location of the administrative units become ‘patchy’-shaped.
Given these results, it becomes interesting to identify areas in which the indicator, each time
considered, localizes the distinctiveness of the area on the basis of the degree of interconnection
and non-random agglomeration of local administrative spatially contiguous actors.
The implementation of policies for territorial competitiveness shall immediately raise the issue of
governance, that is to say the problem of finding a system capable of implementing and of
developing effective policies. Since government levels normally do not coincide with those of
territorial systems and objectives of different levels are not always consistent with each other, the
system of government is likely to be not only ineffective but also inefficient.
6. Conclusions and future developments
The innovation that the state of the art proposed in this project can therefore be identified: on the
one hand, in the implementation of the analytical tools available to the strategic management
research in the study of the relationship between externalities and competitive advantage, on the
other hand, in the deepening of the ways in which empirical data can be useful to support
decision-making activity and to develop strategies.
The usefulness of this project surpasses the limits of the cases studied in how it enables the
recognition of the value added of a solution that completes the potential of the applicatives
mentioned. In particular the integration resolves the problem of the successful and efficient
coordination of the date of filing, processing of the information and the diffusion of the results,
shortfalls overcoming the objective of a single application. Therefore, they solve the typical
problems of every construction project for an information system as a back up for implemented
research observatory.
The strengthening lines on which one could work in the future are so far individualized in the:
 harmonisation of the dynamics of local development that might be otherwise constrained
by the specific interests of different categories of operators. In fact, through the
identification of complementary policies aimed to the exploitation of resources of different
areas and especially through forms of collaboration between public and private sectors, it
would be possible to enhance the value of the land to a greater extent;
 research of networks among actors in each area, with particular reference to comparable
sub-areas so as to invest in creation and/or development of synergies among actors
characterized by similar needs;
 highlighting of situations of vulnerability or risk, to recognize the sub-areas in which the
strong presence of local units of mature business or absence of services for the firms could
result in obstacles to the competitiveness of the system and therefore require targeted
interventions for recovery and/or limitation of the social effects;
 knowledge of the degree of tertiarization of the local economy, to imagine the potential
consequences of the placement in the individual area of local units with the attraction
capacity of new production units or, conversely, the propensity to the
delocalization/closure of the located production units;
 ability to build time series or to consider the evolution of a specific phenomenon through
the maps. Another essential support for the planning is the monitoring and/or the
evaluation of the actions taken;
 identification of possible forms of collaboration and organization in network, dictated by a
certain increase in competition among territories.
The methodology exposed in this work gives way for further integration and improvements in
order to have more cognitive tools to support a more effective and efficient management in
achieving sustainable development of the territory each time identified.
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