1  

Knowledge Networks, Absorptive Capacity and Institutions: Software Firms in Guadalajara and Mexico City

-Preliminary Findings-

Verónica Quiroz Estrada (Mexico – Faculty of Economics UNAM)

This paper presents preliminary findings of the doctoral research project. The main objective of the research project is to analyze the emergence of knowledge networks in the software sector in Mexico, specifically in the territories of Guadalajara and Mexico City. The Mexico City case is presented in this document and the Guadalajara case will follow the same methodology. Afterwards comparison will be made between both cases, which is pending. The research questions were stated as follows: 1) Have knowledge networks emerged in these territories? and 2) How are knowledge networks structured on the studied territories? In Guadalajara and Mexico City, knowledge networks have already emerged, but they are weak or incomplete. There are two interconnection determinants between firms and other actors in the areas studied: absorptive capacity and institutions. On the one hand, firms with major trajectory, organizational capabilities and with a higher technological base are more likely to be linked. On the other hand, the Mexican institutional matrix has largely determined the low formation of knowledge networks.

1. Introduction

Innovation processes directly impact the competitiveness of firms, even when innovation

processes take place within firms and are associated to development of technological

capabilities, supranational and national factors of systemic character contribute

significantly to its development and are framed in national and regional innovation systems,

a set of institutions understood as instances of channeling social behavior and determinants

of the innovative behavior of national and regional firms (Freeman,1987; Nelson 1993;

Lundvall, 1992; Cooke, 1992; Metcalfe, 1994). Accordingly, firms, institutions and other

actors can interact to store and transfer knowledge, skills and artifacts, which define new

technologies forming network relationships. It has been said that the interconnection

between different actors provides advantages in accessing useful knowledge for the process

of creative destruction that otherwise might not be accessible. Thus productive activity

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organized in network structures has increased. Knowledge networks are an emerging

phenomenon of such complexity. Therefore we should consider in what sense is it relevant

to analyze these processes and what are the relevant analytical categories for developing

countries like Mexico. This paper shows preliminary findings of the doctoral research

project based on a study case prepared in two territories of Mexico: Mexico City and

Guadalajara. The structure of the paper is divided as follows: i) theoretical framework; ii)

methodological approach; iii) preliminary findings and iv) conclusions.

2. Theoretical framework

Knowledge Networks  Knowledge networks are based on "network approach" or "social network approach". The

network approach is based on the assumption of the importance of relationships over units

that interact. In this paper, the network approach is framed in terms of its explanatory

usefulness to the study of the innovation processes and technological learning. A variety of

related concepts such as collaboration networks, techno-economic networks, innovation

networks or networks of innovators and knowledge networks have been mentioned in

networks literature. The central idea of these notions is that, under certain conditions, the

joint may encourage and enable innovation processes and technical change. There is a large

set of theoretical and empirical studies that have been stressed on the network phenomenon

(Casas, 2003; Cowan, 1991, 2004; Callon, 1992; De Bresson & Amese 1991; Freeman,

1991; Giulianni, 2002, 2004; Gross and Stren 2001; Lawton, 1991; Malerba and Vonortas,

2009; Senker & Faulkner, 1996). A pioneer study in firm’s perspective was made by

Christopher Freeman who examined the importance of external sources of scientific,

technological and commercial information on the innovative success of companies showing

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the growth of formal and semi-formal innovation networks in the 1980s (Freeman,

1991:500); otherwise De Bresson & Amesse (1991) provided a conceptual introduction to

the study of innovation networks. His first characterization of such networks shows no

reference to inter-organizational networks in general, only those related to innovative

firms1. A related notion to innovative networks and knowledge networks are collaboration

networks referring to the forms of cooperation between innovative companies.

Collaboration is understood as a form of horizontal integration, where companies operating

in the same or related industry establish joint arrangements for the exchange of technology

and information even in competition environments Lawton et. al (1991: 459). The techno-

scientific networks were addressed by Callon (1992: 133), Callon's ideas are suggestive

because they include not only the purely "technical" relations, but include the actors and

their relationships as a decisive and complementary element to create spaces where these

unified elements are interconnected. In this paper, technology is considered as a

combination of tacit and explicit knowledge and therefore innovation networks, techno-

economic networks, collaboration networks comprising knowledge networks. In this case,

the analysis is focused on the perspective of the firm, reflecting on the developing

countries’ context. Thus, knowledge networks are complex structures defined by the

relationships between the different actors involved in the process of generating and sharing

knowledge for various purposes such as technological development, improvement of

production processes and implementation innovations.

                                                                                                               1 Innovative networks are understood beyond the sum of relationships, including networks of suppliers and users, networks between pioneers and adapters, inter-industrial regional networks, international strategic technology partnerships in new technologies and professional inter-organizational networks that develop and promote new technologies, all sums up to the chain of links where complete relations matter as a whole (De Bresson & Amesse 1991:363).      2 It is expected to raise the sample to 30 companies in each territory. 3 In this paper the findings of multidimensional analysis are not including because they are in process. Multivariate analysis will serve to

     

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Absorptive capacity

Absorptive capacities are skills that a company develops to recognize the value of

knowledge and new external information, assimilate it and use it in products and processes

for commercial purposes, often allowing the creation of new technologies, and includes the

ability to acquire, assimilate and adapt technical and scientific knowledge in the production

process (Linsu Kim, 1997; Cohen, Levinthal, 1990). The importance of absorptive capacity

development is that it largely determines innovation processes in a company or a set of

them. In empirical studies the following elements have been identified as relevant for

absorptive capacities: 1) trained and experienced owner and employees, 2) innovation and

learning activities, 3) technology-embedded equipment and 4) organizational capabilities

(De Fuentes, 2007). This paper considers, in agreement with other authors, that there is a

close relationship between absorptive capacities and knowledge networks as an access to

new knowledge, and the ability to spread it also depends on the absorptive capacity of firms

(Giulianni, 2002).

Institutions

Knowledge networks are mediated by the systemic environment; the institutional

framework can promote or limit the process of technological learning and innovation

(Jhonson, 1992:23). Institutions are understood as socially constructed rules that determine

the actions and govern the behavior of individuals in society regularly. These institutions

also help solving problems of coordination and cooperation, however, not all institutions

are efficient and this may change over time (Hodgson, 2006: 2-3; North, 1990: 13-15; Greif

2000:80-82); In this paper is assumed that such institutions may limit or enhance

knowledge mobility in a society. Knowledge networks can be seen as a result of

technological changes and productive needs to act together, but also its emergence is

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largely fueled by formal or informal institutions. On a broader level of disaggregation, the

role of the institutional matrix is decisive: the institutional matrix incorporates the notions

of institutionalism, especially in the line of North, Wallis and Weingast (2009),

reconsidering the importance of the political factor in the explanation of social change in

the long term, this institutional matrix is often gestated within the state and according to

Rivera (2010: 72) consists of three elements: a) behavioral patterns, b) social vision of

reality, indivisible ideology as justification for existing order c) legality of its variants,

including the formal rules. Thus, innovation and processes of creative destruction would be

permeated by the dominant type of institutional matrix, therefore, if the matrix is adverse to

innovation, the process of creative destruction works poorly and it would generate

economic and power concentration, both adverse factors to innovation (Rivera, Robert and

Yoguel: 2009: 10).

3. Methodology Approach

Research Design

It has been chosen to conduct the research as a qualitative analysis. The qualitative analysis

has been supported by fieldwork undertaken in Guadalajara and Mexico City territories.

These areas were chosen because of their importance in terms of production for the sector,

the number of economic units established as well as the characteristics of the territories that

at least suggest the creation of knowledge networks.

Sample Features

The research focuses on the firm’s perspective. The empirical study proceeded through the

collection of data at firm level. Due to the limited availability of resources to study all

software companies and because of the reticence of the firms to attend interviews or answer

surveys, it was impossible to perform a randomization process for sampling, therefore, we

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proceeded to define a nonrandom sample type, this type of sample includes all respondents

that were willing to take part in the research. 28 firms were studied in Mexico City and 24

firms in Guadalajara2. The sample contains an heterogeneous size group of firms (Table 1).

It should be noted that in the software industry most of the firms are micro and small firms.

As to the origin of capital, most sample firms were domestically owned and only 2 firms

were foreignly owned.

Table 1. Size of sample firms in Guadalajara and Mexico City

MICRO (1-10 employees) SMALL (11-50 employees)

MEDIUM (51-250 employees)

LARGE (250 – and more employees)

14 22 12 4

Data Collection

The data collection was based on structured interviews and electronic surveys conducted

with CEOs, general managers and engineers of software firms. The reason why these actors

were chosen as key informants is because they have an extensive knowledge of the

organization, in addition they can be considered as "knowledge workers" too, which means

that they are engineers operating in areas of high valuation. The questionnaire for

conducting interviews or sending surveys was made of questions grouped into five broad

themes: 1) Company details, 2) Technology and infrastructure, 3) Human capital, 4)

Networking, 5) Innovation activities. Additional sources were used to validate data

collection such as firms’ webpages and online documents. Other actors from the sector, like

officers of professional associations public officers at public administration and officers of

public and private universities have been interviewed as well.

Information processing

                                                                                                               2 It is expected to raise the sample to 30 companies in each territory.

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A qualitative analysis was performed based on supportive, theoretical framework and

contextual information; also, quantitative tools will use to accompany the analysis: a)social

network analysis and b)multivariate analysis3. Social network analysis was used to identify

interconnected nodes, positions of nodes in networks, properties of density, centrality, etc.

The actors will be described in terms of their role in knowledge sharing. The actors selected

as nodes were divided as the following: 1) firms, b) universities and R&D centers; c)

professional associations; d) government agencies and e) other firms. Available data from

interviews and surveys was entered into a relational matrix. The name of each of the

previously defined and identified respondents inscribed actors in columns and rows. The

intersections between rows and columns indicate, in each case, whether or not there was a

link (later on the type of links will be discussed). 1 was assigned as the existence of bond

and 0 the absence of link. Once the data is incorporated into the matrix, it was exported to

UCINET VI software, through which the values of the indicators of cohesion measures

(density) and centrality (degree and betweenness centrality) were obtained.

4. Preliminary findings

4.1. Characteristics of sample firms

Type of software

Most of sample firms develop application software (80%). Many of these firms also offer

software related services. 19% of firms offer exclusive services related to software. Some

firms have moved their spinning from software development to consulting services. No

firm develops programming software and just 1% develops system software.                                                                                                                3 In this paper the findings of multidimensional analysis are not including because they are in process. Multivariate analysis will serve to establish relationships between certain characteristics of companies and their propensity to link; multivariate analysis also aims to describe spatial behavior patterns and behavior of software firms that seeks to find homogeneous groups of variables that closely interrelate

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Company’s Age

86% of micro and small firms began operations between 2000-2014, while 14% between

1990-1999. In the case of medium firms 67% between 1990-1999, 25% between 2000-

2009, and 8% were created between 2010-2014. The total large firms were created between

1990-2009.

Export activities

21% of micro firms export; all micro firm exporters have been outsourced by foreign firms.

Little more than half of small and medium firms have notified exporting activities (59%

and 58% respectively). Firms generally export a very small percentage of their products or

services. The principal destinations for exportations are United States and Latin America.

Only one large firm did not report exporting activities. Firms from Guadalajara observed a

greater export orientation than firms from Mexico City.

How do they offer their products and services

Outsourcing is a new form to offer products and services, often firms use it for mitigate

costs and the shortage of skills and expertise in some areas. Contracts with public

administration frequently requires from these practices. 93% of micro firms reported selling

directly, 56% outsourcing and 35% were outsourced. Meanwhile, 95% of small firms sells

directly, 45% outsourcing and 64% outsourced. The sum of medium and large firms sells

directly, 50% of medium firms outsourcing and 58% is outsourced, while only 25% of

large firms have outsourcing process and are outsourced.

Technology

The technology in the industry progresses rapidly, platforms and programming languages

are continually changing. The type of languages and platforms used depends on the spin

and activities performed by the firm. The most common type of software produced is

application software, and programming languages and platforms used for it are

standardized technologies. Usually, firms try to update technologies, but there are firms that

required to use "older” technologies because certain customers continue using them, for

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example, "Cobol", which is a programming language used by the country's banking system

and therefore still used by some software although it is a technology from the 1970s. Often,

companies are associated with large companies and therefore use their platform or

programming languages (Oracle, Microsoft, Cisco). Employees of the software industry

acquire skills through self-learning, this means that they spend hours working on research

about the functioning of languages and platforms, it is quite common for them to use

internet tutorials or participate in communities or developers’ forums.

Infrastructure

Excluding large and some of the medium firms, most firms have very basic equipment

(computers, some local small servers, most rent servers and work in the cloud). About

telecommunication infrastructure, almost all companies report problems. The Internet in

Mexico is expensive and is not fast enough. The location of firm is not usually determining

because everything is done virtually, however, firms concentrated in clusters as the

Software Center in Guadalajara or in a University Technology Park report certain

advantages on infrastructure. In the other hand, firms located in Mexico City reported

having some benefits to be located in a place where the public authorities are concentrated

and commercial activities are very dynamic.

Human Capital

The mean of total employees in micro firms was 6, in small firms was 28, in medium firms

was 137 and in large firms was 737. About qualification of human capital, the mean

percentage of micro firms employees with graduated studies was 82%. Without graduated

studies was 3% and with postgraduates studies 15%. Owners and administrator employees

used to have postgraduates studies. In small firms, the mean of employees with graduated

studies was 83%, without graduated studies 11% and with postgraduates studies 6%. In the

case of medium firms was 77%, 18% and 5% respectively, while large firms reported an

average from 81%, 4% and 15% respectively. For small and medium firms there is a

perception that is not important the postgraduate level for developers, in fact, employers

recognize individual certifications or expertise as more valuable. It is also common that

firms are more willing to hire staff with less education because this reduces the salary to be

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paid, often technicians, interns or trainees are hired. An exceptional case is a large foreign

firm, which refers a high percentage of employees with postgraduate studies, approximately

400 employees.

Recruitment problems can help highlight the degree of experimentation of software

employees. Most of the employers believe that graduates have inadequate training (micro

firms 71% , small firms 82%, medium firms 92%, large firms 75%). 14 % of micro firms

believe that there is an insufficient supply of graduates, 50 % of SMEs believe that there is

an insufficient supply of graduates, while 50% of large firms mentioned having problems

with high turnover.

Training

Nearly the total of large and medium firms provide formal training to their employees. 91%

of small firms reported providing formal training and 57% of micro firms provides formal

training. Formal training can include: induction courses, soft skills, specific programming

languages, train abroad, agile methodologies and certification programs.

Innovation activities

Regarding innovation activities, all firms claim to have made at least one innovation or

substantial improvement in their company (Figure 1).

Figure1. Percentage of sample software firms reported innovation activities by size and innovation type.

Source: authors own 0   20   40   60   80   100   120  

MICRO

SMALL

MEDIUM

LARGE MARKETING

ORGANIZATIONAL

PROCESS

PRODUCT

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Improvements that prevail are innovation processes, partly because several companies that

want to implement quality models certifications are required to make improvements in the

management of their processes; companies, especially micro and small, have referred to

this as favorable. Most firms refer that certifications have helped them have a better

processes system and greater control and monitor of them for decision making.

These indicators point to what firms have reported, however, it must be noted that

innovation is a process that hardly takes place in Mexico, usually the kind of innovation

carried out is of an incremental type and tends to be a local improvement. Frequently, the

role of the local firm is merely to adopt the innovations made elsewhere or incorporate

technologies early.

As for the observed impacts from improvements made, most firms observe an improvement

of the quality in the product and of efficiency in their process. To a less extent, they point

out an increase in market share, expanding the range of products or services, and finally

opening new markets (Table 2).

Table 2. Percentage of perception of sample software firms about benefits of innovation

Benefits Yes

Improved product quality 72%

Improved efficiency 67%

Reduced costs 46%

Increased market share 35%

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Expanded the range of products or services 33%

Specialization of staff 29%

Opening new markets 22%

Others 27%

Source: authors own

In other hand, firms observe some obstacles to innovation; some of the most mentioned are

lack of funding, lack of time, because they also live from hand to mouth, and lack of

institutional incentives. Others obstacles were mentioned like the fiscal issue,

entrepreneurial mentality, lack of information, digital gap with customers resistance to

change, lack of talent or the fact that there is no one who can run ideas (Table 3).

Table 3. Percentage of perception of sample software firms about obstacle for innovation

Obstacles Yes

Lack of funding 42%

Lack of time 37%

Lack of institutional incentives 27%

Period of return on investment 17%

Cost-Risk 12%

Possibility of imitation 12%

Others mentioned (fiscal issue, entrepreneurial mentality, lack of information, digital gap with

customers, resistance to change, lack of talent, no one can run ideas) 29%

Source: authors own

Funds

50% of micro firms and 68% of small firms have requested funds, while the total of

medium and large firms requested funds from public programs.

R&D

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The companies’ perceptions about their R & D activities are interesting. 67% of the

interviewed and surveyed firms invest a percentage of their profits in R & D, in fact they

reported a 3-15% average investment. However, considering other validation sources, with

few exceptions none of the firms have formal R & D departments and many refer to these

activities as work hours invested in research about updates, new platforms, programming

languages, etc. Sometimes, they refer to the salary of some employees as dedicated to

continuous improvement activities. Firms that have entered calls to solicit funds from the

ministry of science and technology have often developed R&D activities.

Membership of a cluster of industry

56% of companies do not belong to any cluster; as to the firms that do belong to a cluster

25% belongs to the Software Center (Centro del Software) in Guadalajara and 15% belongs

to Prosoftware in Mexico City. Two firms interviewed belong to university parks, one in

Guadalajara (ITESO Park) and other in Mexico City (ITESM ) they are small and report

that they have sought to settle in these parks to have more links with the university.

Intellectual Propriety

Almost 50% of sample firms report having copyright. In Mexico, the only way software

can be protected is through copyright rights. To protect their products in this manner

appears discouraging to entrepreneurs mostly because copyright registration is not a figure

of intellectual property with the same consistency as patents.

Certifications

Certified sample firms have certifications in the Mexican Norm MOPROSOFT (23%

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mentioned this norm); CMMI 1-2 (17%); CMMI 3-4 (21%) and CMMI 5 (6%). Most firms

refer that certifications have helped them have a better processes, in practice most

companies combine methodologies that are certified with agile methodologies and their

own.

4.2.Knowledge networks in Mexico City

Mexico City is the country's largest state, is home to the Union powers and is the national

capital city. Mexico City ranked first in science and technology and innovation 20134. In

2013, it was the best positioned in most components, as in the case of: academic and

research infrastructure, human resources training, teaching staff and research, investment in

CTI, scientific and innovative productivity, technology information and communications,

economic environment; in enterprise infrastructure size it occupies the second place; in

institutional component it has the fifth place; and gender dimension occupied the fourth

position (FCCyT, 2014). Although there are higher scientific and technological vocations in

Mexico City compared to the national average, knowledge networks have not been

consolidated in the territory. Figure 2 shows the main interconnections established by

software firms studied in Mexico City.

Figure 2. Main interconnections established by firms in Mexico City

                                                                                                               4 This ranking by the Scientific and Technological Consultative Forum (FCCyT) seeks to highlight the strengths, weaknesses, opportunities and STI of each of the states and is based on a comprehensive indicator of the quantity and quality of resources available on CTI for each of these entities The ranking includes 58 indicators grouped into 10 dimensions: academic and research infrastructure, human resources training, teaching and research staff, investment in CTI, scientific and innovative productivity, business infrastructure, information technology and communications, institutional component, gender the CTI (FCCyT, 2014).

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Blue = Firms; Yellow = Universities and R&D Centers; Green=Professional Associations and chambers; Dark green= government agencies; Turquoise=Other firms (suppliers). Source: Authors own

Based on the review of concepts related to knowledge networks and the characterization of

activities that involve an exchange of substantive knowledge for innovation, a typology of

networks is presented by type of established relations, which summarizes the main

activities that sustain these relationships (Table 4).

Table 4. Typology of knowledge networks depending on established relationships

Knowledge network

Type of Relations

Activities

Advanced knowledge networks

Licensing Patent; Technology Transfer offices; Agreements to share the results of the R & D or technological know-how; Licensing agreements

Creating technology-based firms

Spin-offs; Incubators; Actors hybrids formed by the company and the university

Intermediate knowledge networks

Services Consultant Services (several studies); Technical assistance; Use of equipment and creation of new facilities

Joint R&D activities

Joint work on a research site in parallel with development efforts, continuous transfer of results; R & D contracts; R & D joint agreements; Agreements or exchange of technology; Science and technology parks; Join Ventures and research corporations; Formal networks.

Agreements for sharing and technology transfer Societies

Partnerships; Strategic alliances; Subcontracting relationships; Join Ventures; Testing; Training.

Basic type Flow of Internships; Training students in business; Recruitment of graduates; Recruitment programs.

DF-1

DF-2

DF-3

DF-4

DF-5DF-6

DF-7

DF-8

DF-9DF-10

DF-11

DF-12DF-13

DF-14DF- 15

DF-16

DF-17

DF-18

DF-19

DF-20

DF-21DF-22

DF-23

DF-24

DF-25

DF-26

DF-27

DF-28 UNAM

IPN

ITESM

UAM

UIA

UNITEC

TESOEM

ANAHUAC

UTVM

USJR

UAEM

UTEZ

UTFV

UTN

TESH

CIATEJ

UVUCOL

UAEM

ITCM

CIATEQ

UTT

AMITI

AMESOL

CANIETI

AMIPICI

CANACINTRA

FUMEC

OTRAS

PROSOFTWARE

SE-FONDOS

SE-MEXICO FIRST

CONACYT FONDOS

SEDECO PROSOFTWARE

STYPSINFOTEC

NAFINSA

MICROSOFT

ORACLE

IBM

CISCO IBM

SAP

INTEL

SYMANTECINDRA

OTRA TRASNACIONAL

OTRA NACIONAL

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knowledge networks

human resources Diffusion knowledge events

Seminars; Conferences; Publications, Joint publications.

Informal and formal relations

Informal contacts networks; Information exchange; Membership in professional associations; Free association with a technological community.

Source: Based on ECLAC, 2009; Freeman 1991, De Bresson y Amesse 1991

It is should be noted that there are differences between actors in the level of knowledge

exchanged, in Mexico City the kind of relationship established is mostly of basic type.

Cohesion

The density of networks reflects a very low connectivity; in all defined networks is less

than 1 (Table 5).

Table 5. Density of Mexico City’s Networks

Source: author owns

In the Mexico City network, the highest density is found in firm - professional associations

network (0.08); the lowest density is in firm – university network (0.0267).

Centrality

In general network, most actors have only 4 links in average. The best connected actor in

the general network is the professional association AMITI, with 14 links. In the case of

other firms, other foreign firm is the best positioned. This category includes other suppliers

firms mentioned by the sample firms, this actor is followed by Microsoft. In the case of

Network Density Ties General Network 0.0551 322 Firms - Universities and R&D Centers 0.0267 68 Firms - Profesional Associations and Chambers 0.0810 102 Firms – Goverment Agencies 0.0437 52 Firms - Other firms 0.067 100

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government, the Economy Ministry and the Science and Technology ministry were the

most linked (Table 6).

Table 6. Main Actors with centrally degree in Networks

Network Main actor with centrally degree Out –Input degree

General Network

AMITI 16 Other foreign firm 13

DF-3 13 MICROSOFT 13

DF-4 12 DF-27 12

SE-FONDOS 11 DF-6. 11

DF-25 10 CONACYT-FONDOS

10 DF-5; CANIETI, DF-22, PROSOFTWARE 9

Firms - Universities-R&D Centers

DF-4 5 ITESM 5

IPN 4 UNAM 4

DF-25, DF-6, DF27, DF8, 3

Firms - Professional Associations

AMITI 16 PROSOFTWARE 9

CANIETI 9

FUMEC 8 DF-5 4

DF-6, DF-3, DF-8, DF-27 3

Firms - Goverment Agencies

SE-FONDOS 11

CONACYT FONDOS 10 DF-9. 3

DF-5 3 DF-27 3

Firms - Other Firms

MICROSOFT 11 Foreign supplier 10 Other national 6

ORACLE 5 DF-3 4

DF-25 3 IBM 3

DF 17, DF-7, DF-22, DF-10, DF-27, DF-26 DF-6 3 Source: author owns

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About firms, DF-3, DF-4, DF-27, DF-5, DF-25, DF-5 and DF-22 had a better position,

however, their degree of centrality is low. If we analyze the firms with greater centrality,

we can highlight some features of the leading companies (Table 7).

Table 7. Characteristics of firms with greater centrality in the general network

Firms Characteristics

DF-3 Mature (1990-1999), Large, SW Aplication, Export, Innovation Product, Innovation Process, CMMI V, Prosoftware, Copyright, Funds, Conacyt, SE

DF-4 Young (2000-2009), Medium, aplication SW, Services SW, Export, Innovation process, MoProsoft 1, CMMI3, Funds Conacyt, SE

DF-25 Mature (1990-1999), Medium, Aplication SW, Services SW, Export, Innovation process, MoProsoft 2, Copyright, Funds, Conacyt

Source: Authors own

Firms - Universities and R&D Centers

A poor linkage between firms, universities and R&D centers, is observed. For example,

firms have an average of 1 link with universities. In this network, the most connected firm

was DF-4 with 5 links, followed by DF-25, DF-6, DF27 and DF8 with 3 links. The best

connected universities were ITESM with 5 links and UNAM and IPN with 3 links.

however, nearly 30% of players is not linked at all (Figure 3).

Figure 3. Links between software firms, universities and R&D centers in Mexico City

Source: Author own

DF-1 DF-2

DF-3

DF-4

DF-5

DF-6 DF-7DF-8

DF-9

DF-10

DF-11

DF-12

DF-13

DF-14

DF- 15

DF-16

DF-17

DF-18

DF-19

DF-20DF-21

DF-22

DF-23

DF-24

DF-25

DF-26

DF-27

DF-28UNAM

IPN

ITESM

UAM

UIA

UNITEC

TESOEM ANAHUAC

UTVM

USJR

UAEM

UTEZ

UTFV

UTN

TESH

CIATEJ

UV

UCOL

UAEM

ITCM

CIATEQ

UTT

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Binding types reported by Mexico City firms are mostly of the basic type knowledge

networks and, to a lesser extent, on intermediate knowledge networks. The Firms –

University and R&D Centers network involves an exchange of technological knowledge

mostly through the flow of human resources. The few companies in Mexico City that

reported having established links with universities have done so mostly through recruitment

programs including internship programs, social service, recruitment of trainees. Companies

often offer training courses in universities with the aim to attract human resources. Another

form of linkage less common that has been reported includes the following: R & D

contracts; R & D joint agreements; Testing; Training; Consultant Services (several studies);

Technical assistance and use of equipment. Note that some companies have established

relationships with these actors to access certain programs, as in the case of firms that have

linked to universities in order to enter the FIT and PEI programs (Ministry of Science and

Technology). In these cases, the pairing is through formal agreements on research projects,

technological design or consulting services. The relationship least used in the study

network is the one where a R&D center develops a component to be used by an enterprise.

While basic knowledge networks have emerged, most companies have seen that the

relationship with universities has not given them a tangible benefit. Besides, they reported

that the technological knowledge used in the development of improvements or innovations

most often comes not from these actors and therefore there is not an incentive to engage

with these institutions.

Firms - Professional Associations and Chambers

This network has the highest density, (Figure 4). The most connected actor is the AMITI.

AMITI is a private professional association that pretends to position in the IT industry and

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improve its competitiveness. It is an intermediary actor between companies and various

development programs for the IT sector and also offers training programs. The cluster and

civil association Prosoftware is the second most linked actor in this network, and in third

place appears the chamber CANIETI.

Figure 4. Links between software firms and professional associations in Mexico City

Source: Author own

If the official functions and objectives of such partnerships are reviewed, one could suggest

that these actors promote collaborative networks and provide an environment of trust

between actors facilitating the exchange of strategic information and translating knowledge

that is not accessible to the firm. Nevertheless, what has been reported by employers shows

a different reality. Contrary to expectations, even though firms from Mexico City tend to be

more interconnected with these kind of actors, the type of linkage remains in the mere

figure of affiliation. A constant among respondents in the territory was that such

associations do no promote an exchange of knowledge, and rarely provide strategic

information. In this respect, they also say that among the few advantages of belonging to

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AMESOL

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these organizations is the information of some calls for obtaining funds, and yet it is

reported that the mechanisms to access this information are highly politicized, and that the

firms from Mexico City lack the comprehension of these environments. Other activities of

these organizations are conducting trade shows and some training events. On the other

hand, an observation made by respondents regarding this type of relationship is that these

organisms do not help the national software industry to face the onslaught of transnational

corporations, which often capture large customers and even major contracts with the

government. Firms suggest that the professional associations and chambers could play a

more decisive role in defending and strengthening the national industry, and this would be

very useful to businesses as well as an incentive for innovation.

Therefore, it is necessary to ponder if this network could be a knowledge network. With the

exception of FUMEC, an international nonprofit organization with a vocation to attract

experiences and models that facilitate innovation in SMEs through programs like TechBA,

and performing activities like strengthening technological SMEs in national niches, setting

up innovation networks to open domestic and international markets, guiding business

intelligence studies, conducting specialized incubation processes, among others. Most of

the mentioned chambers and professional associations from Mexico City do not have an

important role in the exchange of knowledge in our sample.

Firms – Government Agencies

In Mexico City, a few companies were linked with government agencies (Figure 5). This

network has been considered as a knowledge network while the linkages have indirectly led

to the exchange and dissemination of technological knowledge. The main actors in this

network were the Economy Ministry through its fund program Prosoft and the Science and

Technology Ministry

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Figure 5. Links between software firms and government entities in Mexico City

Source: Author own

Prosoftware has contributed through the provision of funds to remedy enterprise

technological and organizational shortcomings and improve production processes. Several

of the comments made by interviewees recounted that the program has served mostly to

anchor certification quality models programs like Moprosoft and CMMI. The certification

programs, with their limitations, seem to be a benchmark for process improvements in

software companies. Firms have a well perception of certification programs, but in the

opinion of some interviewees, Prosoftware is very restricted and most of them wouldn’t go

back to request this kind of funds. Many mentioned limitations like poor organization,

corrupt practices and that ultimately they ended up paying more than they could afford after

receiving the fundings. They noted that the results were not as expected and could be

improved, more transparent, and with streamlined dissemination and management selection

processes. Other firms have participated in calls for Ministry of Science and Technology

(FIT, PEI). In this cases more advantages have been are observed. Most importantly, links

through fundraising with institutions such as CONACYT to stimulate innovation have

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enabled network relationships with other actors such as universities, and R & D centers

have been established as a result. This link also offers the possibility of formal R & D

contracts with other actors and the creation of formal networks, among others.

Firms – Other Firms

Firms reported having relationships with other firms to exchange technological knowledge,

mainly with foreign firms, which usually are the biggest suppliers. In this network, other

foreign firms, Microsoft and Oracle, were best connected actors (Figure 6)

Figure 6. Links between software firms and suppliers in Mexico City

Source: Author own

Significan range of software firms obtain technological knowledge from suppliers through

partnerships. Other activities reported were collaboration in development of joint projects,

strategic alliances; subcontracting relationships and joint ventures. In these cases, large

firms offer their software product, licensing, conferences, business intelligence and

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OTRA NACIONAL

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training. Sometimes, SMEs offer a service around a software licensing. Most of the links

are part of commercial strategies or business models and firms have to pay for this

alliances, but promote the technological improvements. Relations with other national firms

are less common, but there are a few cases were firms join to do a technological project or a

big project to some organizations like the government.

5. Conclusions

In this empirical study knowledge networks considered interconnections between different

actors for the exchange of knowledge that can be used for the development of innovations.

The preliminary findigs in Mexico City show that knowledge networks are almost nil or

mostly basic type. In Mexico City firms are not linked to universities and research centers.

There are exceptional cases where firms are really interested in this type of links and

commonly are encouraged by participation in public programs such as the programs of

Ministry of Science and Technology. Firms with a major trajectory and greater internal

capabilities seem to tend to bond more.

At least in the studied sample, firms do not easily trust in government agencies that support

the sector and similar happens with the case of professional associations. This discourages

the formation of links. This has to do with a series of practices and behaviors that appear to

maintain the existing order and contribute the concentration of power in our country. The

firms point out that there have been improvements in the joint and proper functioning of

industry players, however, they also highlight a need for funds, more information, a more

favorable tax regime but most of all a necessity to have organizations with practices more

transparent and efficient.

There is a different situation in the Guadalajara´s case. As well as in Mexico City, in

Guadalajara have emerged incipient knowledge networks, but there are differences.  At first

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sight in Guadalajara seem to have more networking activities and as will be seen later, the

perception of institutional environment is more favorable, in fact, the territory has an

interesting entrepreneurial trajectory and has fewer adverse institutions to innovation. This

will be addressed in the following research advances.

5. Main References

Callon M., (1992), The dynamics of techno-economic networks, in Coombs R., P. Saviotti & V. Walsh, (eds.) Technological change and company strategies, Harcourt Brace Jovanovich, Pub. London, pp. 72-102 Casas, R. (2003), Enfoque para el análisis de redes y flujos de conocimiento, in Luna, M. (Coord) (2003), Itenerarios del conocimiento: formas dinámicas y contenido. Un enfoque de redes., ANTHROPOS, UNAM-IIS, España. ECLAC (2010), Espacios Iberoamericanos. Vínculos entre universidades y empresas para el desarrollo tecnológico, Santiago de Chile, Noviembre. Cohen, Levinthal (1990), “Absorptive capacity: a new perspective on learning and innovation”, in Administrative Science Quarterly, 35 Cowan, R. (2006), “Network models of innovation and knowledge diffusion”, in Breschi, S. & Malerba, F. (Eds), Clusters, Networks and innovation, Oxford University Press, Oxford pp 29-53. De Bresson & Amesse F., (1991), “Networks of innovators: a review and introduction to the issue”, in Reserach Policy vol 20(5), pp. 263-380 D´Este Pablo y Perkman, M. (2010), Why do academics engage with industry? The entrepreneurial university and individual motivations, AIM Research Working Papers, ISSN: 1744-0009 De Fuentes, C. (2007). “Derramas de conocimiento y capacidades de absorción: el caso de las PYMES de maquinados industriales localizadas en Querétaro”, Ideas CONYTEG, Año 2, Núm. 19, 2 mayo 2007 Dutrénit, G., Capdevielle, M, Corona, J.M., Puchet, A., Santiago, F. y O. Vera Cruz A (2010), El sistema nacional de innovación mexicano. Instituciones, políticas, desempeño y desafíos, UAM-X Textual, México D.F, Uruguay. Freeman, C. (1991), Networks of innovators: a synthesis of research issues, Research Policy, Vol. 20, pp 499-514

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Gross, J.y Stren, R. (2001), “Knowledge networks in global society: Pathways to development”, en Gross, J., Estren, R.y Maclean M., Networks of knowledge, Canada, ipac, iapc, University of Toronto Press, pp. 3-28. Greif, A. (1998), Historical and Comparative Institutional Analysis, American Economic Review, Vol 88 Num 2. Giulianni, E. (2007), “The selective nature of knowledge Networks in clusters: evidence from the wine industry”, in Journal of Economic Geography 7 pp 139-168 ______________(2002), “Cluster absorptive capability: an evolutionary approach for industrial clusters in developing countries”, paper presentado en el DRUID Summer Conference on Industrial Dynamics of the New and Old Economy- who is embracing whom? Copenhagen/Elsinore 6-8 Junio. Hodgson, G. (2007), Economía institucional y evolutiva contemporánea, UAM-Cuajimalpa - Xochimilco, México, D.F.ç Jhonston, B. (1992), Institucional learning, en Lundvall B.A. (1992) National Systems of Innovation. Towards a Theory of Innovation and Interactive Learning, Pinter Pub. Lawton H., K. Dickson & S. Lloyd, (1991), "There are two sides to every story: Innovation and collaboration within networks of large and small firms", en Research Policy, vol. 20, No 5, Holanda, octubre, pp. 457-468. Lundvall B.A. (1992) National Systems of Innovation. Towards a Theory of Innovation and Interactive Learning, Pinter Pub. Nelson R., (1993), National Innovation Systems, A Comparative Analysis, Oxford U. Press North, D., Wallis, J.J. y Weingast,B. (2009), Violence and Social Orders. A conceptual framework for interpreting recorded human history, Cambridge, Cambridge University Press. North, D. (1990/2006), Instituciones, cambio institucional y desempeño económico, Fondo de Cultura Económica Powell W.W., Koput K.W. & Smith-Doerr L. (1996) Interorganizational collaboration and the locus of innovation: networks of learning in biotechnology. Administrative Science Quarterly 41 , 106-145. ________ y Grodal, S (2005), Networks of innovators, en Fagerberg, J., Mowery, D. Y Nelson, R., The Oxford Handbook of Innovation, Oxford University Press. Rivera, Miguel Ángel (2010b) “Estado, atraso y desarrollo tardío. Una revisión histórica”. En: Alejandro Dabat (coord.) Estado y Desarrollo. México: Institutu de Investigaciones Económicas-UNAM, pp 65-98.

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Rivera, M.A., Robert V. y Yoguel, G. (2009),AMERICA LATINA: CAMBIO TECNOLOGICO, COMPLEJIDAD E INSTITUCIONES: los dilemas no resueltos del desarrollo económico. Documento de Trabajo, working paper. Senker J., & Faulkner, W. (1996) Networks, tacit knowledge and innovation, en Coombs R., Al Richard,s, P. Saviotti y V. Walsh (eds.), Viotti, Eduardo B. (2001). “National Learning Systems: A new approach on technical change in late industrializing economies and evidences from the cases of Brazil and South Korea. Science, Technology and Innovation” Discussion Paper No. 12, Center for International Development, Harvard University, Cambridge, MA, USA. Vonortas, N. (2009), Innovation Networks in industry, en Malerba F. & Vonortas, N. (2009), Innovation Networks in Industries, Edward Elgar, Cheltenham, UK Von Hippel E. (1987) Cooperation between rivals: informal know-how trading. Research Policy 16 , 291- 302. Annex. Acronyms

a) Universities and R&D Centers

Acronym Name UNAM Universidad Nacional Autónoma de México

IPN Instituto Politécnico Nacional

ITESM Instituto Tecnológico y de Estudios Superiores de Monterrey UAM Universidad Autónoma Metropolitana UIA Universidad Iberoamericana

UNITEC Universidad Tecnológica de México

TESOEM Tecnológico de Estudios Superiores del Oriente del Estado de México UTSJR Universidad Tecnológica del San Juan del Río UTVM Universidad Tecnológica del Valle del Mezquital UAEM Universidad Autónoma del Estado de Morelos CIATEJ Centro de Investigación y Asistencia en Jalisco (R&D Center)

UV Universidad Veracruzana UCOL Universidad de Colima

UAMEX Universidad Autónoma del Estado de México UTT Universidad Tecnológica Tehuacán

CIATEQ Centro de Investigación y Asistencia en Querétaro (R&D Center) ITCM Instituto Tecnológico de Ciudad Madero

UTANL Universidad Autónoma de Nuevo León

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b)Professional Association and Chambers

Acronym Name

AMITI Asociación Mexicana de la Industria de Tecnologías de la Información (Professional Association)

AMESOL Asociación Mexicana Empresarial del Software Libre (Professional Association)

CANIETI Cámara Nacional de la Industria Electrónica de Telecomunicaciones y Tecnologías de la Información (Chamber)

AMIPICI Asociación Mexicana de Internet (Professional Association)

CANACINTRA Cámara Nacional de la Industria de Transformación (Chamber) FUMEC Fundación México-Estados Unidos para la Ciencia (Civil Association)

OTRA Other organization non relational with software sector PROSOFTWARE Clúster Prosoftware

c) Government Agencies

Acronym Name SE-FONDOS Ministry of Economics (Secretaría de Economía) – Prosoft Program.

SE-MEXICO FIRST Ministry of Economics (Secretaría de Economía) - México First Program

CONACYT FONDOS Ministry of Science and Technology (Consejo Nacional de Ciencia y Tecnología)- PEI/FIT Programs

SEDECO PROSOFTWARE

Ministry of Economic Development in Mexico City (Secretaría de Desarrollo Económico en Distrito Federal)

INFOTEC Centro de investigación e innovación en tecnologías de la información y comunicación

NAFINSA Nacional Financiera STYPS Ministry of labor and social welfare

d) Other Firms

Acronym Name

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MICROSOFT

ORACLE

IBM International Business Machine

CISCO Cisco Systems Inc.

SAP System Aplication and Products in Data Processing INDRA Indra Systems

INTEL Inter Corporation PROV TRASN Other foreign firm

PROV NAC Other domestic firm