Expert Systems with Applications 41 (2014) 5636–5646

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Expert Systems with Applications

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Network-based innovation systems: A capital base for the Monterreycity-region, Mexico

http://dx.doi.org/10.1016/j.eswa.2014.02.0140957-4174/� 2014 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +52 81 8287 0634.E-mail addresses: blancagnava@gmail.com (B.C. Garcia), tredicinov@gmail.com

(D. Chavez).1 Tel.: +52 81 8625 8360.

Blanca C. Garcia a,⇑, Danilo Chavez b,1

a Colegio de la Frontera Norte, COLEF, Northern Borderlands Research College, 277, Técnicos St. Col. Tecnologico, Monterrey, N.L. 64700, Mexicob EGAP School of Government and Public Policy, Tecnologico de Monterrey, Eugenio Garza Lagüera & Rufino Tamayo, Colonia Valle Oriente, San Pedro Garza Garcia, N.L. 66269, Mexico

a r t i c l e i n f o

Keywords:Knowledge-based developmentKnowledge-cityCapitals systemRelational capitalRegional innovation systemsMonterreyMexico

a b s t r a c t

This paper advances notions of interactive learning as one of the key drivers of the knowledge based-development perspective. The paper explores the strategic role and close relationship between socialand institutional learning as critical processes in order to generate knowledge and innovation in an urbancontext—i.e., knowledge city. The research reported in this paper makes an account of: (i) considering acapitals system perspective for knowledge flows to add value for the development of knowledge citiesand communities; (ii) learning interactive processes among actors that leverage institutional capacitywithin regional innovation systems, and; (iii) adopting a knowledge-based development framework forinvestigating the capital basis of the City of Monterrey, Mexico. This research sheds light on how knowledge-intensive elements—such as higher education institutions, research centers, firms and other local actors—are contributing community building in a knowledge-based urban context—i.e., knowledge city.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

It has been advanced that a knowledge-based economy hasbecome an attribute of leading urban centers (i.e., knowledge cities,or in short KCs) and has transformed them into important creatorsof value for nations, communities and regions (Carrillo, 2004;World Bank Institute [WBI], 2008; Yigitcanlar, 2009). Indeed, thenew millennium has seen how knowledge content of goods andservices are on the rise: we are increasingly buying and sellingmore and more knowledge. Such changes have given birth tonew development paradigms, for example, the knowledge-baseddevelopment paradigm or in short KBD—it is also referred asknowledge-based urban development (KBUD) further focusing onurban development dynamics (see Yigitcanlar 2010; Yigitcanlar &Lonnqvist, 2013; Yigitcanlar, O’Connor, & Westerman, 2008). Thisparadigm is the combination of a number of trends and develop-ment approaches: such as sustainable development and knowl-edge management. In addition to changes under the KBD flag,the emergence of complementary paradigms such as relationalsociety (Allen, Deragon, Orem, & Smith, 2008; Castells & Cardoso,2006; Donati, 2010; Mendoza & Vernis, 2008) is seemingly acceler-ating their impact and influence on a global scale. Unfortunately

relational society only explains part of the complex and radicaltransformation of global cultures taking place in our cities, regionsand nations.

Within these contexts, this paper focuses on notions of interac-tive learning as a key driver for KBD. It explores the strategic roleand close relationship between social learning, knowledge andinnovation in city-regional contexts for which social capital modelsindicate that proximity matters. The paper aims to characterizeexisting knowledge-based structures within regional innovationsystem (RIS) models through the lens of a KBD framework. This,in order to identify if learning competences and knowledge-basedscaffolding are actually being built in the RIS. In such aim, this pa-per is set out to explore what we currently know about an emerg-ing RIS in Monterrey, a city at the heart of the Mexico-Texas, USborderland region. Hence, the paper would invite a glimpse onhow key individuals and organizations in Monterrey are buildingtheir intangible assets, their experience and their knowledge-basedrelationships their institutions and their future.

This paper first introduces the role of knowledge in city build-ing, so as to give a context for the meaning-creation processes thatdefine value-based taxonomies such as the KC concept. This is fol-lowed by a literature review on RIS and notions of interactive learn-ing for innovation, as some identified models advance. The paperalso attempts to bring further understanding on how intangibleinfrastructures contribute to the creation of new knowledge-basedurban community paradigms. Then, the paper introduces theKC case for Monterrey, and the kind of RIS developing in the

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city-region. The closing section aims to highlight a culture shift ob-served in the way people share their knowledge in a wider, moresocial sphere, thus creating new forms of social learning andinteraction.

2. Knowledge city: learning, knowledge and innovation

In urban settings specially, the 1990s challenged our societies tobecome accurate information managers. As data flows escalatedand multiplied, individuals, organizations and societies were com-pelled to make sense of information (and ideally, knowledge) inreal time despite of geographical distance (Castells, 2000). Infor-mation flows also changed our concept of development. A franticrush for golden strategies to process knowledge and enable learn-ing accelerated most organizations, and not few societies. In suchcontext, the notion of learning regions started to emerge as aframework for understanding development in a multi-dimensional,highly networked setting beyond city limits (Florida, 1995), alongwith other conceptual tools such as a system of innovationapproach (Cooke, Gomez-Uranga, & Etxebarria, 1997; Edquist &Johnson, 1997; Lundvall, 1992), clusters ⁄⁄(Porter, 1995), intellec-tual capital systems (Stewart, 1997), global networks (WBI, 2002),capacity building strategies (United Nations DevelopmentProgramme [UNDP], 1997), capacity development (WBI, 2009),and other related concepts.

However, such rich blend of theory and practice is directed toknowledge-based typologies such as digital city, learning city, KC,a learning city driven by knowledge production (Work Foundation,2005); or the Ideopolis, a city of Ideas and inclusive communities.The nature of knowledge, as an intangible asset, a flow and a pro-cess, imposed a new millennial epistemological shift from matter-centered to relation-centered knowledge (Carrillo, 2002). Hence,for the purposes of this paper, value-based systems and capitaldimensions are the key elements of a KC definition. A KC is a city‘‘purposefully designed to nurture knowledge’’ (Edvinsson, 2002,in Dvir & Pasher, 2004, p.17). It is ‘‘a region that bases its abilityto create wealth on its capacity to generate and leverage its knowl-edge capabilities through knowledge-based extended networksformed by enterprises and people’’ (Chatzkel, 2004, p.62). In an-other terms, a KC is one ‘‘in which its citizenship undertakes adeliberate, systematic attempt to identify and develop its capitalsystem, with a balanced and sustainable approach’’ (Carrillo,2004, p.34).

Amongst KBD approaches, a strategic framework will be ad-vanced for the identification, valuation and systematic develop-ment of the city’s traditional and knowledge capital in anintegrated way (García, Carrillo, Rivera, Leal, & García, 2009), whichin turn will support a RIS analysis. The advanced knowledge-basedframework is basically a taxonomy of urban capital that deliber-ately and systematically maps out all city resources—both tradi-tional and knowledge-based required to leverage the balancedand sustainable development of contemporary urban communi-ties. Such taxonomy is based on an assessment of a city’s urbancapitals system (CS) (Carrillo, 1997; Carrillo, 2002). The CS taxon-omy has been the foundational basis of applications such as theMost Admired Knowledge City Awards (MAKCi), which greatly re-flects how knowledge-intensive research work now depends onan extended community network to gain the necessary perspec-tives and paths to learn and make sense of emerging KBDinitiatives.

The underlying rationale for this taxonomy is to satisfy the for-mal requirements of a value-production system, i.e., that it be com-plete, consistent and homogeneous. This taxonomy builds uponother efforts to identify and value collective individual capital inurban, national or regional levels. Known as CS, this taxonomy

identifies the basic capital elements of productive systems and‘‘meta-capitals’’: those other forms of capital not productive them-selves but significantly leveraging the system’s overall capacity. Inthe particular case of the RIS for Monterrey, the CS methodologywill be applied in first instance to build up the analysis of the cap-itals system within the city. This would eventually create a com-plete and consistent set of indicators, within a coherent andpractical framework. The key capital category dimensions used inthe present exercise are:

1. Identity capital2. Intelligence capital3. Financial capital4. Relational capital5. Human individual capital6. Human collective capital7. Instrumental-material capital8. Instrumental-knowledge capital.

The first four capital dimensions are considered ‘‘meta-capitals’’as they facilitate the action of the ‘‘agent’’ (human) capitals and theinstrumental capitals. The CS is the base criteria for the eight MAK-Ci Awards category dimensions that shape the consultation exer-cise. They constitute a generic taxonomy of urban capitals,deliberately and systematically mapped upon all the resourcesboth traditional and knowledge-based. The CS assumes that theeight capital dimensions are required to leverage the balancedand sustainable development of contemporary urban communi-ties. The CS framework is immersed within context, where the va-lue-based background, history and capabilities of a city play amajor role. It mirrors the city’s historical antecedents and pre-existing knowledge, as well as present knowledge repositoriesand capital, which in turn will enhance the city’s future potentialfor development.

2.1. Interactive learning for innovation

Cities are but one type of adaptive social forms of organization,an ever-challenging task in our post-modern world (Giddens,2002). In them, social capital characterizations on emerging socialstructures are clearly sensitive to their corresponding ecosystems.They express their full complexity, through actors who are intelli-gent, expert, complex adaptive systems as well. Actors in cities areaccompanied by organizational and institutional structures andrules that are continuously reconsidered and adjusted to matchthe multifaceted and ever-changing environment. Clearly, ‘‘innova-tive capability and the spread of innovation are a property of a so-cial system that depends on its learning capability’’ (Wenger, 2009,p. 2). This notion of learning was introduced by Etienne Wenger in1998, following a long tradition of learning as a social process ofdevelopment. With Jean Lave, Wenger pioneered research workon the communities of practice (CoPs) concept. They advanced thatpeople in CoPs could develop the capacity to create and shareknowledge. This could become a social ecosystem of (social) learn-ing ‘‘which includes the ability to find meaning in activities and toengage competently with other people involved’’ (Wenger, 2009,p. 4). Wenger sees such engagement as social learning accountabil-ity. It is perhaps the central challenge for 21st century organiza-tions in all sectors that are concerned with systemic learning andinnovative capability (Wenger, 2009; Wolfe, 2009).

In these emerging paradigms, notions of a ‘‘learning economy,’’(Lundvall & Borrás, 1998; Lundvall & Johnson, 1994), and a ‘‘knowl-edge-based economy’’ (WBI, 2008) have been recurrent. Moreover,knowledge-based frameworks that involve RIS and/or clusteringprocesses for development (Wolfe, 2002) assume learning asknowledge-generative and innovation-led, in which ‘‘social

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processes engage people in mutually beneficial dialogues andinteractions’’ a kind of ‘‘learning-through-interacting’’ (Johnson,1992; Lundvall, 1992). These perspectives presuppose the socialnature of learning, knowledge management and innovation.Embedded in relational capital perspectives, these processes seem-ingly work best when partners involved are close enough to oneanother to allow frequent interaction and the easy, effective ex-change of information (Wolfe, 2002; Wolfe, 2004; Wolfe, 2009).Moreover, it is believed in these models that innovative capabili-ties are sustained through regional communities that share a com-mon knowledge base. According to some observers, the regionallevel is critical because the factors of space and proximity contrib-ute to the kind of tacit knowledge and the capacity for learningthat support innovation’’ (Granovetter, 1973; Wolfe, 2002). Re-gions seemingly generate a ‘‘collective learning process leadingto the rapid diffusion of knowledge and best practice’’ (Nauwelaers& Reid, 1995 in Wolfe, 2002, p. 6) that links social (or societal)learning to knowledge, knowledge to innovation and innovationto development altogether, as advanced henceforth in this paper.Innovation is thus understood as the result of interaction betweenvarious economic and social processes (Manley, 2008), in whichentities need the capabilities of other fellow actors. Research in thiscontext focused on innovation systems supported by interactivelearning, because ‘learning has become the central core of thenew canonical thinking about the source of wealth of nations’(de la Mothe & Paquet, 1998, in Lundvall, 1992; Manley, 2002).Emerging shapes and forms of interactive innovation frameworksinvolving learning and knowledge sharing (Manley, 2008, p. 3) are:

� Development blocks (Dahmen, 1988);� Complexes (Glatz & van Tulder, 1989; Marceau, 1995);� Innovation milieu (Camagni, 1991; Ratti et al., 1997);� Complex products and systems (Hobday, Rush, & Tidd, 2000);� Competence blocs (Eliasson, 1997);� Technological regimes (Nelson & Winter, 1982);� Industrial filigrees (van Tulder & Junne, 1988);� Innovation districts (Pyke et al., 1990);� Sectorial innovation systems (Breschi & Malerba, 2000, chap. 6);� Regional innovation systems (Cooke et al., 1997);� Technological innovation systems (Carlsson & Stankiewicz,

1991);� National innovation systems (Lundvall, 1992; Nelson, 1993);� Innovation networks (De Bresson & Amesse, 1991);� Business networks (BIE 1991);� Value-chains (Walters & Lancaster, 2000), and;� Clusters (Porter, 1990).

Research prior to this paper has concentrated on four key ap-proaches from this list of frameworks: systems, networks, value-chains and clusters. However, compared to other frameworks,the innovation system approach encompasses the broadest rangeof relationships, also focusing on technical support instances anda norm-based regulatory framework. In terms of a networking/learning approach in institutional contexts, the innovation systemapproach is the most comprehensive of the four approaches(Manley, 2008) and has therefore been preferred for this paperpurposes. Indeed, authors like Manley (2002), Manley (2008) andLundvall (2004) stress the increasing complexity of successfulinnovation and the importance of external knowledge sources.Both authors account for two main modes of innovation: explicitcodified knowledge (STI-mode of innovation) and learning-basedinnovation, accessed by doing, using and interacting (DUI-modeof innovation). In brief, an innovation-based interactive learningis the ability to learn from success as well as failure, to identifyand correct mistakes, and to diffuse technology throughout theorganization. This ability is essential for long-term survival of the

system, if it is able to adapt to changing circumstances (especiallychanges in technology). Interactive learning assumes a reliance onmultiple sources of tacit knowledge in the learning process,according to Lundvall (2004). Manley (2002), on the other hand,identified four key drivers of innovation in innovation systems:knowledge flows, institutions, interactive learning and economiccompetence, all of which are critically important when definingcapacity building and impact aspects of a RIS.

As shown in Table 1, Manley’s dimensions and indicators havebeen further developed in the recent literature on RIS. This is par-ticularly true for the knowledge flows driver, and a list of indicatorsis available from Organization for Economic Co-operation andDevelopment (Organization for Economic Co-operation, 1997),Franke (2005) and Manley (2008) among others. However, theinstitutions driver is a more complex process to observe and itwas clear that a gap in the literature on how to approach this driverexisted. As part of an on-going research that aims to eventuallytackle all four drivers here proposed in a deep and extensive man-ner, this paper will introduce an operational model to observe theinstitutional aspect of a RIS. It will put the model in context andwill complement it with knowledge flows observed through a par-allel instrument: a capitals system approach in the nextparagraphs.

2.2. Institutions, interactive learning and the capacity approach

Cities have become a privileged place where innovation takesplace due to its urban conglomerate where (positive or negative)outcomes like patents grow at an exponential level (Badger,2013; Shearmur, 2012). This is why specialized literature linksthe concept of learning (defined as a knowledge-generating capac-ity) with the ability to improve a condition or set of circumstances(Sen, 1999). The term capacity is matched to the skill, and the po-tential availability of performing, producing and developingimprovements. This term applies to governments, public institu-tions and communities. It involves the level of achievement ofthese entities and additionally, assets and/or powers to achievethe objectives (Hall, 2002). Hence, capacity refers to the ability ofits individuals, organizational units and institutions to carry outtheir functions effectively, efficiently and sustainably (Ospina,2002). Capacity involves the active use of a continuous process,where people are the central factor in capacity building in all areas.Also defined as ‘‘the ability of a context in a set of entities operatingunder a common purpose according to certain rules and processes’’(United Nations Development Programme (UNDP)., 1997, p. 121).One aspect to consider is measuring the concept of capacity. Intrin-sically, the ability refers to resources and their allocation. Requiresan agreement and the mapping of the agents involved. Grindle(1997) suggests that capacity development initiatives in the publicsector must be seen in three dimensions: human resource develop-ment (focus on providing professional and technical personnel),management systems for organizational development (to improvethe performance of specific tasks and functions, micro-structures),and institutional reforms (institutions, systems and macro-structures).

Institutions: In the context of a regional system of innovation,the role of institutions as social organizations are elements withinthe system that change and shape the relationships among eco-nomic, state organizations and private firms. Institutional capaci-ties are the ability of the state to enforce the board sets of rulesthat govern economic and political interactions (Grindle, 1997).The concept of institutional capacity has expanded and has beenapproached from various perspectives, some authors understandit as an input (in-put), a process, as a result (Morgan, 2006) andinstitutional quality (Fukuyama, 2004; Israel, 1987), as an attributeof governance, governance (Grindle, 1997), as an organizational

Table 1Four drivers of an innovation system approach (Lundvall, 2004; Manley, 2002; OECD, 1997).

Drivers Dimensions

Industrial AlliancesInter-firm Research CooperationFirm surveys. Literature-based countingIndustry/University InteractionsCo-operative industry/University R&D – University Annual ReportsIndustry/University co-patents – Patent record AnalysisIndustry/University co-publications – Publications analysisIndustry use of university patents – Citation AnalysisIndustry/University information-sharing – Firm Surveys

Knowledge Flows Industry/Research Institute InteractionsCo-operative industry/Institute R&D – Government ReportsIndustry/Institute co-patents – Patent record AnalysisIndustry/Institute co-publications – Publications analysisIndustry use of research institute patents – Citation AnalysisIndustry/Institute information-sharing – Firm SurveysTechnology DiffusionTechnology use by industry – Firm SurveysEmbodied technology diffusion – Input/output analysisPersonnel MobilityMovement of Technical Personnel amongst industry, universities and research – Labor Market statistics, University (Institute Reports).Institutional SubsystemsFinance system; the taxation system; the intellectual property rights system; the training system; the education system; the industrialrelations system.

Institutions Other Institutional/organizational StructuresLabor markets; the internal structure of corporate firms and government bodies;Norms and perception of normsConceptions of fairness and justice held by capital and labor; the structure of the state and its policies; and idiosyncratic customs,traditions, norms, moral principles, rules, laws, standards and routines.UncertaintyThe lack of full information about the occurrence of known events, the existence of techno-economic problems whose solutionprocedures are unknown, and the inability to predict precisely the consequences of one’s actions. The involvement of multiple players ininteractive learning increases the stock of knowledge and the breadth of experience that can be drawn onto reduce uncertainty in theinnovation process.

Interactive Learning Scientific KnowledgeThe increasing reliance of major new technological opportunities on advances in scientific knowledge highlights the importance oflinkages between R&D users and major R&D organizations in interactive learning.ComplexityThe increasing complexity of R&D activity means that multiple players are needed in order to access multiple knowledge sources, ratherthan just relying on the skills of individual innovators. Experimentation: the increasing role of experimentation in the form of learning-by-doing and learning-by-using requires access to appropriate partners to maximize the value of experimentation.ExperimentationThe increasing role of experimentation in the form of learning-by-doing and learning-by-using requires access to appropriate partners tomaximize the value of experimentation.CumulativenessThe cumulative character of innovative activity means that past decisions shape future opportunities. Hence, it is important to keepoptions open by maintaining a broad array of innovation interests through multiple relationships, through activities such as: user-producer interaction, formal R&D agreements, professional association functions, consultations with regulators/training organizations/finance providers, production agreements, licensing, joint ventures, sub-contracting and conference/workshop/forum attendance.

Economic Competence(Firm-level)

Selective/Strategic Ability. The ability to: make innovative choices between markets, products, technologies and organization structures;engage in entrepreneurial activity; select key personnel; and acquire other key resources, including new competencies. An importantpart of strategic capability is the notion of receiver competence or absorptive capacity, which involves the ability to scan and monitorrelevant technological and economic information; identify technical and market opportunities; and acquire knowledge, information andskills needed to exploit opportunities.

Organizational/Integrative/Coordinating abilityThe ability to organize and coordinate resources and economic activities within the organization so that overall objectives are met. Thisincludes the ability to generate and improve technologies through new combinations of existing knowledge and skills. This should be themain function of middle management in an organization.Technical/Functional abilityThe efficient execution of various functions within the firm to implement technologies and utilize them effectively in chosen markets.Learning/adaptive abilityThe ability to learn from success as well as failure, to identify and correct mistakes, and to diffuse technology throughout theorganization. This ability is essential for long-term survival. A firm that is both effective and efficient at a point in time eventuallybecomes neither unless it can adapt to changing circumstances (especially changing technology).Organizational/Integrative/Coordinating abilityThe ability to focus on core competencies and utilize complementary resources from other firms. This ability has increased in importancein recent years due to the pressures of globalization, the increasing complexity of input and output markets and the increasing speed oftechnical change.

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feature (Tobelem, 1992; Morgan, 2006), or as an element that en-hance the individual (Sen, 1999). In addition, it has been used as asynonym for quality management, organizational performance,efficiency, management or training (PNUD, 2009, p. 49). Nelissen

(2002) suggests that the capacity can be of two types: indicatedwhen government bodies have to perform a certain task, or itcan be effective in terms of performance of the capacity of localgovernment to act and the context where the action occurs.

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3. Regional innovation systems

On the other hand, a working definition for innovation is ‘‘a pro-cess that leads to an outcome’’ (and this outcome is an object or away of doing that previously did not exist) (Shearmur, 2012). Inparallel, an innovation system can be defined as a ‘‘collective of‘organizations, institutions and people that interact in the produc-tion and diffusion of new economically useful knowledge’’ (Lundv-all, 1992, p. 11). These definitions frame a number of key strategiesfor regional development has been identified as RIS.

3.1. Regional innovation system as a network-based hub

RIS has been identified as the constellation of institutions at theregional level that contribute to the innovation process (Braczyk,Cooke, & Heidenreich, 2004). A RIS is clearly identified with itsset of institutions, both public and private, that produces pervasiveand systemic effects which encourage firms within the region toadopt common norms, expectations, values, attitudes and prac-tices—in short, a common culture of innovation that is reinforcedby the process of social learning (Wolfe, 2002). Hence, definitionsof a RIS vary, but for this paper purposes, it will be defined as‘‘the set of economic, political and institutional relationshipsoccurring in a given geographical area which generates a collectivelearning process leading to the rapid diffusion of knowledge andbest practice’’ (Nauwelaers & Reid, 1995, in Wolfe, 2002, p. 6)where innovation activities takes place (Niosi, 2000).

Clearly, like any other knowledge-based environments, RISfunction both on the basis of inclusion as well as exclusion, andthese processes may assume sharp contours within the entiredynamism of any given system. Networks and clusters within aRIS work as bodies or entities where new knowledge and innova-tions can be generated and disseminated. They seem to have re-placed—to a great extent—other more rigid institutions in whichnot so long ago knowledge was created and preserved. However,this can lead to a gloomier side of network life. It could lead tothe creation of global networks, which could multiply and parcelglobal competition that may lead to polarization, creation of elitenetworks at the cost of greater exclusion of many groups. Indeed,for a number of international observers, the key problem of knowl-edge society will be to cope with inequality and exclusion(Hamdouch, 2008).

3.2. Regional innovation system frameworks

There is a consensus that economic development is based onthe capacity to generate and absorb innovation processes (Cimoli,2000). It becomes relevant to master the use of knowledge in sci-ence and technology from external sources. Learning processes de-pend on the role between institutions related to science,technology and innovation (STI) and appropriate policy frameworkto foster business relationships (Niosi, 2010).

The literature in RIS is extensive and has gained great recogni-tion in developed and developing countries. Factors that influenceRIS include: the presence of local public research institutions,industry clusters, venture capital, an environment conducive tobusiness creation and infrastructure for STI, vertical and horizontallinks in the clusters, the human capital endowment, the orienta-tion to export markets, the role of the State (Autio, 1998; Chavez,2013; Consejo Mexiquense de Ciencia y Tecnología [COMECYT],2011; Cooke & Memedovic, 2003; Niosi, 2000; Padilla-Perez, Vang,& Chaminade, 2009) among others. The regional level began to gainmore attention from scholars and policy makers; they began tofocus on the particular combinations of political, cultural, and eco-nomic structures (Cooke et al., 1997). The RIS approach emphasizes

external economies are generated by strong companies, a stock oflabor capacities, network of suppliers, and local based knowledge(Malecki, 1997). Hence, RIS as a concept is becoming increasinglyrelevant due to the implementation of policies at regional and statelevel that are concerned with the growth of specific regionmobilizing players in specific areas (Chaminade & Edquist, 2006).Porter (1990) showed that competitiveness and innovation are ex-plained in the existence of innovation systems based on local andregional clusters. These kinds of innovation systems are definedby regions of economic activities and depend largely on theemergence of intermediate organizations (Casalet, 2007) basedon the work of the actors and their networks. The competitivenessand sustainability of the countries and regions seemingly dependon their ability to attract, capture, generate and exchangeknowledge, eventually reflected in their value chains (Cookeet al., 1997).

Following such agenda, Autio (1998) developed a framework tostudy RIS capturing the main characteristics and relationships of aRIS operating at different levels of government such as local, na-tional and international level. It has distinguished two subsystemsthat constitute the main building blocks of RIS: (i) the knowledge-application and exploitation sub-system, and (ii) the knowledge-generation and diffusion sub-system. Both sub-systems co-habitin a socioeconomic and cultural context. The main external influ-ences on RIS take the form of national innovation systems (NIS).A RIS is formed by systems, networks, value-chains and clusters,and it can similarly be analyzed at a number of levels, including na-tional, regional, local, sectoral and technological levels (Manley,2008). The components of the structure according to Autio (1998)are in the two subsystems mentioned and its division also corre-sponds to a distinction between public and private sectors, and be-tween commercial and noncommercial activities. In this way thereis a reference to a bidirectional flow of knowledge and the interac-tion of resources and human capital. Autio’s (1998) model providesan approach to the RIS relations taking into account user and pro-ducer of knowledge, both seen as subsystems with bidirectional rela-tionship through the exchange of flows of knowledge, resources, andhuman capital in an environment where shared social, economic,political and cultural characteristics, which in turn are influencedby national and international external environment (Fig. 1). Clearly,regions are a privileged context to develop competitive environ-ments because of its factors of learning through interaction,geographical proximity, and the generation, use and disseminationof knowledge (Niosi, 2010). RIS’s approach emphasizes the systemicdimensions, the propensity of interaction and relation betweenactors in innovation processes (Manley, 2008).

Cooke et al. (1997) states that regions can be viewed as aregionalism or regionalization phenomena. The first type involvesa set of characteristics such as culture ties, language, and commoncustoms. The second type has to do with political boundaries suchas a municipality, province, State, Nations. Several examples ofsuccessful RIS exist in the literature, such as Silicon Valley, Route128, and so on. Other studies suggest that RIS are more frequentlyfound within cities or metropolitan areas (Katz & Bradley, 2013).Some regional differences in innovation performance are identifiedbetween old industrial regions, metropolitan regions, and periphe-ral regions. Some authors (such as Zucker et al., 1999) suggest thatmost knowledge externalities and venture capital activities takeplace within maximum 50 to 100 km. For Niosi (2000) in subna-tional jurisdictions like in the USA and Canada are far too largefor most externalities to occur homogeneously across their territo-ries. In that sense RIS are considerate also as urban agglomeration.The Metropolitan City of Monterrey in this case will be consideredas a RIS where the Nuevo Leon State government has the compe-tence to establish normative framework through policies, incen-tives, and regulations.

Fig. 1. Regional system of innovation (adapted from Autio, 1998, p. 134).

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4. A capital systems approach for the regional innovationsystem of Monterrey

4.1. Methodology of the capital system framework

For the purposes of this paper, two key moments of analysis arepresented for Monterrey RIS. (i) First, an interpretation of actualcity profiles with specific categories as expressed in a sample CSfor Monterrey (Table 2). Although not as apparent, this city CS ac-counts for a number of knowledge flows that were observed in de-tail in a previous research work (García, Carrillo, Rivera, Leal, andGarcía, 2009). For the purposes of this paper, a number of charac-teristics have since been identified for the Monterrey city-regionprofile generated by the MAKCi framework, highlighting the multi-dimensional tapestry that has already several successive buildingblocks (Garcia, 2010; Garcia et al., 2009) as observed by partici-pants in successive MAKCi exercises. (ii) A second moment of anal-ysis in the paper advances a detailed institutions (relational/institutional capital) process within Monterrey’s RIS, as an approx-imation of on-going research on the four innovation drivers men-tioned in previous paragraphs.

Monterrey is the capital city of the State of Nuevo Leon, in thenortheast Mexican territory, located at a three-hour driving distancefrom the Texas border (USA) and about a 12-h drive from Mexico’scapital city. Presently, a network of highway and railroad systemsconnect Monterrey to four borders crossing in Texas and to allmayor cities and seaports throughout Mexico, making it an epicen-ter for commerce and business. Back in 2004, the regional State Gov-ernment engaged the whole region into the Project Monterrey:International City of Knowledge (MICK). It became one of five corestrategic initiatives of the 2004–2009 State Government Adminis-tration. The corollary of the MICK initiative yielded a number of re-ports and documents, one of which is Monterreys CS taxonomy ofthe city as MICK. The project triggered an on-demand diagnosis ofMonterrey’s tangible and intangible capitals. This resulted in thefirst illustrated capitals-dashboard and a laboriously integrated Va-lue Capitals Report for the City of Monterrey, published in 2008.

Nonetheless, further and present research is now focused to ob-serve how the knowledge-based networks in Monterrey, as well as

its clustering strategies and its social learning practices are creat-ing advancements in a context challenged by pervasive povertyand inequality, climate change and violence. Following CS criteria,instruments and tools, Table 1 introduces a sample-summarizedinterpretation of the city profile (MAKCi dimensions) for Monter-rey city-region, in order to show how a full city profile is builtthrough the CS/MAKCi framework during the MAKCi consultationexercises of 2011 and 2012.

Monterrey as a city-region has nevertheless been both at theleading and bleeding edge of Mexico’s socio-economical history(Pavlakovich-Kochi, Morehouse, & Walst-Walter, 2004). Shapedby its unique geo-historical conditions, Monterrey has developedoriginal forms of human collective capital, defined and character-ized by its condition of ‘borderland’. Despite notorious povertypockets throughout the region, Monterrey’s recent government ini-tiatives were seeking to converge one of Mexico’s most thriving lo-cal economies with the oil-powered economy of the Texan USAborder (Gobierno de Nuevo Leon., 2004). This was an attempt tore-define the Mexican–American border, creating a corridor ofopportunities for collaboration within the contradictory, yet simul-taneous processes triggered by the North American Free TradeAgreement (NAFTA) (Pavlakovich-Kochi et al., 2004). Unlike theJuarez-El Paso or Sonora-Arizona borderlands, Monterrey’s leader-ship has sought to develop strong relationships with its Texanneighbors through business-led and academic-led co-operation,made possible by the core strengths of the city’s educational anduniversity system, as identified by Wolfe (2004; 2009). Whereasmost analyses of university-industry links focus primarily on theprocesses of creating and transferring knowledge from universitiesto industry (Villasana, 2011), the university, in fact, plays a muchbroader role as a key institutional support for the development of lo-cal innovation systems and cluster development. A key role for gov-ernment apparently lies in strengthening the governance capacity atlocal and community levels (Chavez, 2013) so as to deploy its en-abling powers more effectively to promote a process of social learn-ing among firms and local institutions (Wolfe, 2004). In 2012, withall these data available, the MAKCi exercise obtained a full city CSprofile for Monterrey, here summarized in a radial representingthe citys capitals (and apparent knowledge flows) profile (Fig. 2).

Table 2MAKCi capital dimensions for Monterrey (World Capital Institute, 2012).

MAKCi Capital dimensions The City of Monterrey, Mexico

1. Identity capital Monterrey is the entrepreneurial capital city of Mexico. Situated three hours from the Mexico-Texas border, a network of highwayand railroad systems connect Monterrey to all mayor cities and seaports throughout Mexico, and some important metropolis in theUSA, making it an epicenter for commerce and business. In balance, the Identity capital of the city resides in the positive value of itsdistinctive regional and urban personality, as well as the recent renovation in prominent areas of the urban infrastructure and thetechno-industrial background of the city.

2. Intelligence capital The Institute for Research and Technology Transfer (i2T2) is the GO appointed agency to develop the Monterrey International City ofKnowledge initiative along with links to technology development strategy: Innovation and Technology Transfer Park (PIIT).

3. Financial capital Industrial clusters are: Beverages, Glass, Food Processing, Petrochemicals, Cement, Steel, Household Appliances, Automotive, andElectronics & Telecommunications. Other emerging clusters are software, biomedicine, Aeronautics and Mechatronics. Indeed,Monterrey, as the capital city of Nuevo Leon has thus become a Mexican leading urban community in the 20th Century, with aprominent (iron & steel-based) industrial, commercial and educational potential in the Mexican context.

4. Relational capital Monterrey conveys several favorable elements for external relations, potentially positioning the city as an important inter-continental node. However, Monterrey’s relational capital also shows a negative balance in terms of internal social cohesion, due tothe recent increase of insecurity in the city, the wider poverty gap during the last decade and the marginalization of women from theproductive sectors. Moreover, the prevalence of the domestic violence in observed in almost all social scopes. This circumstancecauses a vicious circle of marginalization-poverty-criminality-corruption that begins to debilitate the internal social cohesion, whichalthough observed in the country as a whole, in Monterrey it deserves determined and effective regional solutions.

5. Human capital (Individualbase)

Monterrey presents great contrasts in terms of education, nutrition, self-care and participation in the productive life. The comparativenational and regional school performance are outstanding and are receiving growing attention, while the performance at the globallevel is rather poor.On the other hand, the nutritional bad habits, lack of self-care, as well as illiteracy, diminished the value added that each Monterreycan bring to the community, generating a huge social cost and avoidable health and a deterioration of the quality of life.

6. Human capital (Collectivebase)

Monterrey also encompasses a number of social account liabilities. Population habits such as obesity; gender inequalities; the stilldisadvantageous referencing of school performance at international level and the challenges in urban governability (amongst others)demand a sound response before they start compromising future viability of Monterrey’s local society. Consolidate educationaladvances, to bring them to international standards and achieve its value-transfer into the community, along with basic lifestyletraining, including eating habits, and emotional intelligence, are a prerequisite for Monterrey as a city of knowledge.

7. Instrumental capital(Tangible base)

The City of Monterrey is committed to promoting a sustainable future by conserving water, reusing, reducing and recycling solidwaste, building ‘‘Green’’ buildings and many other programs. To achieve success, the municipality (SDE) launched the Alliance for theFuture (2020) and the Environment Action Pledge.

8. Instrumental capital(Intangible base)

In order to identify, appreciate and systematically develop Monterrey’s elements of community value an urgent and immediateinstitutionalization of urban social capital accounts is needed, as a mirror created to reveal its intangible and tangible value base andtherefore allow the city to manage its advancements towards its Knowledge City aspirations.

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4.2. Regional innovation system of Monterrey

Today, Monterrey metropolitan area is working its way to cre-ate a distinctive long-term KC offer, by developing partnershipsin which HEIs and parallel knowledge-intensive entities are medi-ators across sectors. Despite an increasing gap in social justice,Monterrey has developed a number of knowledge-based character-istics of a KC. The city is home to the largest software-developmentfirm and a national top quality educational system that includesboth private and public sector HEIs. Over half of the fiscal alloca-tion of the city is budgeted for education with emphasis on privatesector participation. There are 231 technical schools, 2 technicaluniversities (i.e., Tecnologico de Monterrey [ITESM], UTM) andover 30 higher education institutions. Moreover, the city has

0

2

4

6

8

101.Identity Capital

2.Intelligence Capital

3.Financial Capital

4. Relational Capital

5.Human Ind Capital

6.HumanCollect Capital

7.Instrumental

Tangible Capital

8.Instrumental

Intangible Capital

Monterrey 2012

Fig. 2. Monterrey capital system overview.

adopted a cluster development approach with a focus on software,biomedicine aeronautics, mechatronics and automotive sectors.These clusters are characterized by values such as eco-friendliness,potential of high volume exports, trade with technological changes,talent development and hiring, and high salary profiles. In order tosupport this Monterrey boasts a close collaboration between aca-demia, public sector and private sector. Both prominent private(i.e., ITESM, University of Monterrey [UDEM]) and public (i.e.,UANL, IPN) universities have developed a mutually beneficial rela-tionship with the city, strengthening the power base in terms ofquality education for the city-region.

Monterreys present RIS is composed by public and private orga-nizations, also local and national and international entities.According to the definition provided for the knowledge generationsubsystem, its elements are research institutions, universities andtechnical, human capital and intermediate organizations. Interme-diate organizations are entities involved in business support andtheir regular activities, which operate at national, regional or locallevel. They are also identified as facilitators of other actors withinthe RIS. These organizations within the subsystem are those dis-seminators of knowledge and serve as a liaison between buyersand sellers of products and services involved in the STI.

From the 14 public research centers established in Nuevo Leon(2003–2012) 10 are located in the Research of Innovation Technol-ogy Park (PIIT)—opened in 2005. In 2013 two centers were alreadybuilt and will start operation. The remaining four centers belong tothe State University of Nuevo Leon (UANL); three of these centersare located within the premises of the University and the other onenear the airport of the city. Regarding private research centers(PRC) detected in the document review. There are 19 PRC dedi-cated to scientific research and technological development. These

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centers belong to private HEIs, regional companies and multina-tionals such as Motorola. The seven remaining centers, six belongto the ITESM and one to the UDEM them are located in respectiveof their campus facilities. It is noteworthy that the ITESM has threecenters began operating in the late nineties and in the followingdecade and constituted strengthened. The rest of the PRC havebeen incorporated from 2005 onwards (see Fig. 3).

Knowledge application and exploitation sub-system: The subsys-tem of application and exploitation of knowledge is characterizedby producers, suppliers and consumers in general. Monterrey pri-vate sector system has been characterized by its entrepreneurialactivities in manufacturing. Historically, Monterrey has been con-sidered the industrial capital of Mexico. In its metropolitan areais San Pedro Garza Garcia, one of the municipalities with the high-est human development index for the Americas and the world (i.e.,index figure of 0.8). The city is home to major Mexican industrialand financial groups from abroad also found several internationalconsulting firms.

Regional policy sub-system: The regional policy subsystem is char-acterized by governmental regional entities, public administration, anormative set of framework, and policy instruments. A centraladministration, a semi-public administration and the government of-fice compose the States Government of Nuevo Leon. The centraladministration has fourteen central offices such as the Education,Security, Economic Development, Social Development, among others.Six administrative unites such as public relations, international af-fairs, and a representative office in the Mexico City.

The Secretary of Economic Development is in charge of policyinstruments from external source (NIS) can be mentioned inter-governmental coordination Mixed Funds (FOMIX) contemplatedin Article 35 of the Law of Science and Technology. FOMIX supportsthe scientific and technological development in municipal andState governments, through a sum of contributions from the StateGovernment or Municipality, and the Federal Government, throughCONACYT (National Council of Science and Technology). It hasthree main objectives:

� To allow the State governments and municipalities to allocateresources for scientific research and technological develop-ments, aimed at solving strategic problems, specified by thestate itself, with the sharing of federal resources.

Fig. 3. Monterrey regional innovatio

� Promote the development and strengthening of scientific andtechnological capabilities of states or municipalities.� To distribute economic resources to assist in the development

of the entity through scientific and technological actions.

Another tool that promotes the development of STI capabilitiesto the states is the Regional Institutional Fund for DevelopmentScience, Technology and Innovation (FORDECYT). Its objective isto promote scientific activities, technology and innovation as wellas the formation of high-level human resources, collaboration andintegration of regions and regional systems strengthening science,technology and innovation. Also, a major player in the governmen-tal side is the State Council of Science and technology. The name ofthese organizations is Innovation and Technology Transfer Insti-tute (I2T2). This organism has an autonomous characteristicamong the Public Administration. Three advisory councils composeit: academic, firms and citizen. Its internal configuration composedby directors of planning, education and promotion of new firms tofoster innovation activities in the metropolitan area and the State—see Table 3, which elaborates the institutional driver concept.

5. Discussion

Institutional capacity of Monterrey: In recent years, Monterreyhas maintained a leading place in competitiveness in Mexico(Instituto Mexicano para la Competitividad [IMCO], 2012; Organi-zation for Economic Co-operation, 2009). City competitiveness isbased on the ability to attract, retain and develop human talentand investment to produce goods and services of high value addedto generate gainful employment and quality of life for its habitants.The institutional framework that the state government has estab-lished includes policies oriented towards better and effective inter-actions between triple helix components. The STI public policyissue is set in a fast technological development environment, andthe composition of various actors taking part of it. There is an evo-lution in the STI policies in legislation in Mexico and in the State ofNuevo Leon, especially in Monterrey metropolitan area, using thedevelopment of scientific knowledge as an engine of development.Government actions are provided within a planning framework.This process is important because it is represented by a plan that

n system (Chavez, 2013, p.108).

Table 3Institutional drivers (adapted from Chavez, 2013).

Knowledge application sub-systemFinance system; the taxation system; theintellectual property rights system; thetraining system; the education system; theindustrial relations system.

Institutions Institutionalsubsystems

Knowledge exploitation sub-systemLabor markets; the internal structure ofcorporate firms and government bodies.Regional policy sub-systemConceptions of fairness and justice held bycapital and labor; the structure of the state andits policies; and idiosyncratic customs,traditions, norms, moral principles, rules, laws,standards and routines.

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includes explicit and consistent decisions to allocate resources topredetermined purposes to foster innovation. Thus it is importantto know the regulatory framework and the establishment of rules.

In Monterrey’s case, the efforts of the government have beenable to support the emerging RIS and create a bottom-up set of pol-icies. Subsystems shown in Table 3 are pat of the emerging struc-ture of institutions that support the knowledge flow andinteractive learning required for a RIS. This was reflected in theNuevo Leon, 2004–2009 and 2010–2015 State Development Plan.This Plan established the relevance of interactions among govern-ment, industry and academia for economic development throughinitiatives that involve these actors. In this period of governmentthere was a strategic administration supporting a long-term con-cept of KC, highly significant for the State of Nuevo Leon, (Ciencia,2010). These initiatives seek to stimulate these interactions pri-marily through: (i) establishing the institutional settings forknowledge transfer; (ii) creating the environment for attractingindustry, and; (iii) strengthening and developing clusters in theState.

In 2003 the State Congress approved the Law for the Promotionof KBD. This led to the creation of the Coordinating Office for Sci-ence and Technology (COCYTENL) in 2004 with the purpose ofbringing together all actors of science and technology in NuevoLeon, and creates the Program of MICK. In 2005 the Law was refor-matted and create the I2T2 replacing the COCYTENL. The I2T2 it isan agency of the State Government of Nuevo Leon, with the author-ity to sign agreements and allocate financial resources to programsand projects of innovation, science, and technology. The Instituteadministrates the program MICK. MICK revolves around seven ba-sic strategies: (i) redesigning the agenda for the education system;(ii) attracting new research centers and technology-based firms;(iii) promoting innovation in firms, universities, and research insti-tutions; (iv) creating new innovation firms; (x) widening urban andcultural infrastructure; (xi) diffusing a new entrepreneurial culture,and; (vii) improving instruments that support innovation (Garciaet.al., 2009).

Fostering knowledge-based activities is also anchored in the na-tional STI instruments such as the FOMIX CONACYT-Nuevo Leon, inaddition to other programs designed by the State Governmentaimed at promoting the creation of new firms. The number of ap-proved projects through the mixed funds as well as the amountshas varied, and they include industrial development and the crea-tion of a scientific and technological infrastructure (Foro ConsultivoCientífico Tecnológico [FCCyT], 2009). The I2T2 is in charge ofmonitoring and evaluating the evolution of: (i) the developmentof a mayor cluster of researchers in the state; (ii) to build of tech-nological infrastructure; (iii) to foster graduated programs in insertinto international networks; (iv) to promote and attract ForeignDirect Investment (FDI); (v) to promote Nuevo Leon’s exports; (vi)

to accelerate development of human capital (Specialists andTechnologists); (vii) to link and make alliances between companiesand academic institutions; (viii) to incorporate of Science &Technology to basic education; (ix) to patent technology develop-ments and transfers; (x) to incorporate R & D in the companies,and; (xi) to create business incubators and venture capital (Ciencia,Conocimiento y Tecnología, 2010).

6. Conclusion

This paper has revisited a model of four key drivers of innova-tion in RIS—knowledge flows, institutions, interactive learningand economic competence. It has purposefully concentrated onthe second driver, institutions, for which models in recent litera-ture exhibited a gap in concepts and applications, particularly forthe context targeted for observation. In first instance, we were ableto see the City of Monterrey (in the Mexico-Texas borderland re-gion) emerging as a type of KC by using a CS lens, and the MAKCiframework, which aims to provide a comprehensive view of thecomplex interplay that city capitals and knowledge flows repre-sent. For some observers, Monterrey can be seen as a catalyst KC,the kind of city that found through challenges, crisis, and uncer-tainty the key inflection moments to make a swift transition possi-ble and needs to create the possibility to move into a harmoniousand balanced regional development (Scheel, 2011). Likely, one ofthose city possibilities is Monterreys RIS. Through the RIS ap-proach, we could perceive the role of subnational government insupporting innovation activities, and the policy process itself forinnovation policy. The new public management adopted duringthe 1990s and the first decade of the new century, is seeminglyleading towards a strong state in some countries; from centraliza-tion to decentralization activities; from the involvement of govern-ment in providing public goods to private and public partnerships;from transparency, accountability to open government; from pyra-midal structure of organization to new types of governance.

In terms of a RIS for Monterrey, a second moment of the paperhighlights the role of subnational government in supporting inno-vation activities. It has been argued that the performance of a gov-ernment through innovation policy can be measured by itscapacity to fulfill the objective for what the policy has been de-signed and implemented: to foster and support innovationprocesses.

With the framework proposed RIS and Institutional capacity theorganizations at governmental level can be track and see howsome strategies and the implementation of policy from local o fed-eral level foster innovation activities and foster the building of anemerging innovation system. Hence, further enhanced definitionsof social capital through clustering, norms, edges and borderlandterritories is deem necessary. A specific account of relational capi-tal in a borderland context will be expected to shed some light onhow creativity and innovation are leveraged to add value for thedevelopment of cities and communities. Borderlands are thoughtto be places where ‘‘the knowledge of the world can be decon-structed. . .. then reconstructed’’ (Pavlakovich-Kochi et al., 2004,p. 31). Hence, by using a KBD framework, and the Mexico-Texasborder as a context, the paper aimed to converge with parallel inte-grative exercises (PWC, 2006; Honeywill, 2010) in which cities’knowledge-based capital engages in similar institutional capacitycapital system frameworks brought into play as in the case ofMonterrey, a city with many knowledge-based aspirations.

References

Allen, S., Deragon, J. T., Orem, M., & Smith, C. F. (2008). The emergence of therelationship economy: The new order of things to come. Cupertino, CA: HA Books.

B.C. Garcia, D. Chavez / Expert Systems with Applications 41 (2014) 5636–5646 5645

Autio, E. (1998). Evaluation of RTD in regional systems of innovation. EuropeanPlanning Studies, 6(2), 131–140.

Badger, E. (2013). The real reason cities are centers of innovation. The Atlantic.Retrieved on 10 Jan 2014 from <http://www.theatlanticcities.com>.

BIE (Bureau of Industry and Economics) (1991). Networks: A third form oforganization. Bulletin on Industry Economics, 10, 5–9.

Braczyk, H.-J., Cooke, P., & Heidenreich, M. (2004). Regional innovation systems: Therole of governances in a globalized world. New York: Routledge.

Breschi, S., & Malerba, F. (2000). Sectoral innovation systems: Technologicalregimes, schumpeterian dynamics, and spatial boundaries. In C. Edquist (Ed.),Systems of Innovation: Technologies, Institutions and Organisations (pp. 130–156).London and Washington: Pinter.

Camagni, R. (Ed.). (1991). Innovation Networks: Spatial Perspectives. London:Belhaven.

Carlsson, B., & Stankiewicz, R. (1991). On the nature, function and composition oftechnological systems. Journal of Evolutionary Economics, 1, 93–118.

Carrillo, F. J. (1997). Managing knowledge-based value systems. Journal ofKnowledge Management, 1(4), 280–286.

Carrillo, F. J. (2002). Capital systems: Implications for a global knowledge agenda.Journal of Knowledge Management, 6(4), 379–399.

Carrillo, F. J. (2004). Capital cities: A taxonomy of capital accounts for knowledgecities. Journal of Knowledge Management, 8(5), 28–46.

Casalet, M. (2007). Las nuevas tendencias en la organización y financiamiento de lainvestigación: el caso de México. In J. Basave & M. Rivera (Eds.), Globalizaciónconocimiento y desarrollo: teoría y estrategias de desarrollo en el contexto delcambio histórico mundial Tomo II (pp. 495–525). México, DF: UNAM Press.

Castells, M. (2000). The information age. Oxford: Blackwell Publishers.Castells, M., & Cardoso, G. (2006). The Network society: From knowledge to policy.

Washington, DC, Center for Transatlantic Relations. Retrieved on 10 Jan 2014from <http://www.umass.edu>.

Chaminade, C., & Edquist, C. (2006). From theory to practice. The use of the systems ofinnovation approach in innovation policy. Innovation, science and institutionalchange. Oxford: Oxford University Press (pp. 141–162). Oxford: OxfordUniversity Press.

Chatzkel, J. (2004). Greater Phoenix as a knowledge capital. Journal of KnowledgeManagement, 8(5), 28–46.

Chavez, D. (2013). Capacidades institucionales para el fomento de la innovación: el casode Nuevo Leon. Tesis para obtener el grado de Doctor en Política Pública. EGAPGobierno y Política Pública, Tecnológico de Monterrey. Retrieve from ITESM.

Ciencia, Conocimiento y Tecnología. (2010). El parque de investigación e innovacióntecnológico: un ejemplo. Revista Ciencia, Conocimiento y Tecnología, 104, April30. Monterrey.

Cimoli, M. (2000). Developing innovation systems: Mexico in a global context. London:Routledge.

Consejo Mexiquense de Ciencia y Tecnología. (2011). Experiencias Internacionales deSistemas Estatales de Innovación y mejores prácticas en la creación de AgendasEstatales de Innovación. Estado de México: COMECYT.

Cooke, P., Gomez-Uranga, M., & Etxebarria, G. (1997). Regional innovation systems:Institutional and organisational dimensions. Research Policy, 26(4), 475–491.

Cooke, P., & Memedovic, O. (2003). Strategies for regional innovation systems: learningtransfer and applications. Vienna: United Nations Industrial DevelopmentOrganization.

Dahmen, E. (1988). Development blocks in Industrial Economics. ScandinavianEconomic History Review and Economic History, XXXVI(1), 3–14.

De Bresson, C., & Amesse, F. (1991). Networks of Innovators: A review andintroduction to the issue. Research Policy, 20, 363–379.

De la Mothe, J., & Paquet, G. (1998). Local and regional systems of innovation aslearning socio-economics. In J. De la Mothe & G. Paquet (Eds.), Local and regionalsystems of innovation (pp. 1–16). Boston, Dordrecht and London: KluwerAcademic Publishers.

Donati, P. (2010). Relational sociology: A new paradigm for the social sciences. London:Routledge.

Dvir, R., & Pasher, E. (2004). Innovation engines for knowledge cities: An innovationecology perspective. Journal of Knowledge Management, 8(5), 16–27.

Edquist, C., & Johnson, B. (1997). Institutions and organizations in systems ofinnovation. In C. Edquist (Ed.), Systems of innovation: Technologies, institutionsand organizations (pp. 41–63). London: Pinter Publishers.

Edvinsson, L. (2002). Corporate longitude. Harlow: Pearson Education.Eliasson, G. (1997). Competence Blocks and Industrial Policy in the Knowledge

Based Economy. Stockholm: Department of Industrial Economics andManagement, The Royal Institute of Technology.

Florida, R. (1995). Towards the learning region. Futures, 27(5), 527–536.Foro Consultivo Científico y Tecnológico. (2009). Estadísticas de los sistemas

estatales de innovación 2009 (Vol. 2). México D.F.: FCCyT.Franke, S. (2005). Measurement of social capital. Reference document for public

policy research, development and evaluation. Canada, policy research initiative.Project: Social capital as a public policy tool. Ottawa: Government of Canada.Retrieved on 10 Jan 2014 from <http://www.horizons.gc.ca>.

Fukuyama, F. (2004). State-building: Governance and World order in the 21st century.New York: Cornell University Press.

García, B., Carrillo, J., Rivera, G., Leal, A., & García, C. (2009). Steel and mountainhorizons: Shaping a knowledge-based capital system for Monterrey. In S. Batra& J. Carrillo (Eds.), Knowledge management and intellectual capital: Emergingperspectives (pp. 761–767). New Delhi: Allied Publishers.

Garcia, B. (2010). Rising Northern light: Manchester’s knowledge capital. In K.Metaxiotis, F. J. Carrillo, & T. Yigitcanlar (Eds.), Knowledge-based development for

cities and societies: Integrated multi-level approaches (pp. 296–314). London: IGI-Global.

Giddens, A. (2002). Runaway World. How globalization is reshaping our lives. London:Profile Books.

Glatz, H., & van Tulder, R. (1989). Ways out of the International Restructuring Race?Project Proposal, Annex, B. Amsterdam: University of Amsterdam.

Gobierno de Nuevo Leon. (2004). Programa estratégico de ciencia, tecnología einnovación. Retrieved on 10 Jan 2014 from <http://www.nl.gob.mx>.

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology,78(6), 1360–1380.

Grindle, M. S. (Ed.). (1997). Getting good government. Capacity building in the publicsectors of developing countries (Harvard Institute for International Development).Cambridge, MA: Harvard University Press.

Hall, J. S. (2002). Reconsidering the connection between capacity and governance.Public Organization Review: A Global Journal, 2(1), 23–43.

Hamdouch, A. (2008). Conceptualizing Innovation Clusters and Networks. InInternational Conference on Innovation Networks: Forum The Spirit of InnovationIII. Tacoma-Seattle, Washington, 14–16 June.

Hobday, M., Rush, H., & Tidd, J. (2000). Innovation in complex products and systems.Research Policy, 29(7–8), 793–804.

Honeywill, R. (2010). What is an Intelligent City? How we live, work and play ischanging. Retrieved, May 6, 2013, Available from: http://rosshoneywill.com/articles/what-is-an-intelligent-city/.

Instituto Mexicano para la Competitividad. (2012). Índice de CompetitividadUrbana 2012. El municipio: una institución diseñada para el fracaso.Propuestas para la gestión profesional de las ciudades. México D.F.: IMCO.

Israel, A. (1987). Institutional development: Incentives to performance. Baltimore, MD:Johns Hopkins University Press.

Johnson, B. (1992). Institutional learning. In B. A. Lundvall (Ed.), National innovationsystems: Towards a theory of innovation and interactive learning (pp. 23–46).London: Pinter Publishers.

Katz, B., & Bradley, J. (2013). The metropolitan revolution: How cities and metros arefixing our broken politics and fragile economy. New York: Brookings InstitutionPress.

Lundvall, B. A. (1992). National Systems of innovation. Towards a theory of innovationand interactive learning. London: Pinter Publishers.

Lundvall, B.A. (2004). National Innovation Systems: analytical concept anddevelopment tool. In 10th Anniversary Summer Conference on Dynamics ofindustry and innovation: organizations, networks and systems. Copenhagen,Denmark, June 27–29, 2005.

Lundvall, B. A., & Borrás, S. (1998). The globalising learning economy: Implications forinnovation policy. Brussels: Commission of the EU.

Lundvall, B. A., & Johnson, B. (1994). The learning economy. Journal of IndustryStudies, 1(2), 23–42.

Malecki, E. (1997). Technology and economic development: The dynamics of local,regional, and national change. University of Illinois at Urbana-Champaign’sAcademy for Entrepreneurial Leadership Historical Research Reference inEntrepreneurship.

Manley, K. (2002). The Systems approach to innovation systems. AustralasianJournal of Information Systems, 9(2), 19–33.

Manley, K. (2008). Frameworks for Understanding Interactive Innovation Processes.Queensland University of Technology. Retrieved on 10 Jan 2014 from <http://www.construction-innovation.info>.

Marceau, J. (1995). A Networked Nation or a Complex Issue? Reshaping industryanalysis. Journal of Industry Studies, 2(2), 19–33.

Mendoza, X., & Vernis, A. (2008). The changing role of governments and theemergence of the relational state. Corporate Governance, 8(4), 389–396.

Morgan, P. (2006). The concept of capacity. Maastricht: European Centre forDevelopment Policy Management.

Nauwelaers, C., & Reid, A. (1995). Innovative regions? A comparative review ofmethods of evaluating regional innovation potential european innovationmonitoring system. Luxembourg: Directorate General XIII EuropeanCommission 10-20.

Nelissen, N. (2002). The administrative capacity of new types of governance. PublicOrganization Review, 2(1), 5–22.

Nelson, R., & Winter, S. G. (1982). An Evolutionary Theory of Economic Change.Cambridge, MA: Belknap Press.

Niosi, J. (2000). Canada’s national system of innovation. Montreal: McGill-Queen’sUniversity Press.

Niosi, J. (2010). Building national and regional innovation systems: Institutions foreconomic development. Cheltenham, UK: Edward Elgar Publishing.

Organization for Economic Co-operation and Development. (1997). Nationalinnovation systems. Paris: OECD.

Organization for Economic Co-operation and Development. (2009). Review ofInnovation Policy: Mexico. Paris: OECD.

Ospina, S. B. (2002). Construyendo capacidad institucional en América Latina: elpapel de la evaluación. VII Congreso Internacional del CLAD sobre la reforma delEstado y de aa Administración Pública. Lisboa, Portugal, Octubre. Retrieved on 10Jan 2014 from <http://www.geolatina.net>.

Padilla-Perez, R., Vang, J., & Chaminade, C. (2009). Regional innovation systems indeveloping countries: integrating micro and meso-level capabilities. InLundvall, Joseph, Chaminade, & Vang (Eds.), Handbook of innovation systemsand developing countries: Building domestic capabilities in a global setting(pp. 140–182). Cheltenham, UK: Edward Elgar Publishing.

Pavlakovich-Kochi, V., Morehouse, B. J., & Walst-Walter, D. (2004). ChallengedBorderlands: Transcending Political and Cultural Boundaries. Abingdon: Ashgate.

5646 B.C. Garcia, D. Chavez / Expert Systems with Applications 41 (2014) 5636–5646

Porter, M. (1990). The Competitive Advantage of Nations. New York: Free Press.Programa de Naciones Unidas para el Desarrollo (PNUD) (2009). Informe sobre desarrollo

humano Jalisco 2009: Capacidades institucionales para el desarrollo humano local.México DF: PNUD. Retrieved on 12 Nov 2013, Available from: http://www.undp.org.mx/DesarrolloHumano/estatales/images/01IDHJAL_intro.pdf.

PricewaterhouseCoopers (PWC) (2006). Cities of the future. Retrieved on 12 Nov2013, Available from: http://www.pwc.com/gx/en/government-public-services/issues-trends/index.jhtml.

Pyke, F., Becattini, G., & Sengenberger, S. (1990). Industrial Districts and Inter-firmCooperation in Italy. Geneva: International Institute for Labour Studies.

Ratti, R., Bramanti, A., & Gordon, R. (1997). The Dynamics of Innovative Regions.England: Ashgate.

Scheel, C. (2011). Innovacities: In search of breakthrough innovations producingworld-class performance. International Journal of Knowledge-Based Development,2(4), 372–388.

Sen, A. (1999). Development as freedom. New York: Knopf.Shearmur, R. (2012). Are cities the font of innovation? A critical review of the

literature on cities and innovation. Cities, 29(1), 9–18.Stewart, T. (1997). Intellectual capital: The new wealth of organisations. New York:

Doubleday-Currency.Tobelem, A. (1992). Institutional Capacity Analysis and Development System (ICADS).

Operation Manual. Washington DC: World Bank, Public Sector ManagementDivision. Technical Department. Latin American and the Caribbean Region.

United Nations Development Programme (UNDP). (1997). Capacity assessment anddevelopment: In a systems and strategic management context. New York: UNPD.

van Tulder, R., & Junne, R. (1988). European Multinationals in Core Technologies.Chichester: Wiley.

Villasana, M. (2011). Technology policy and drivers for university – IndustryInteractions: A grounded theory approach to biotechnology in Nuevo Leon,Mexico (Ph.D. thesis in Public Policy). Monterrey, Mexico: ITESM.

Walters, D., & Lancaster, G. (2000). Implementing value strategy through the valuechain. Management Decision, 38(3), 160–178.

Wenger, E. (2009). Social learning capability: Four essays on innovation and learning insocial systems. Retrieved on 10 Jan 2014 from <http://wenger-trayner.com>.

Wolfe, D. A. (2009). Introduction: Embedded clusters in a global economy. EuropeanPlanning Studies, 17(2), 179–187.

Wolfe, D. A. (2002). Social capital and cluster development in learning regions. In J.A. Holbrook & D. Wolfe (Eds.), Knowledge, clusters and regional innovation:Economic development in Canada (pp. 11–38). Montréal: McGill QueensUniversity Press.

Wolfe, D. A. (2004). The role of higher education in regional innovation and clusterdevelopment. In G. Jones, P. McCarney, & M. Skolnick (Eds.), Creating Knowledge,Strengthening Nations: The Changing Role of Higher Education (pp. 167–194).Toronto: University of Toronto Press.

Work Foundation. (2005). The Ideopolis: Knowledge city consortium researchproject. Retrieved on 10 Jan 2014 from <http://www.theworkfoundation.com>.

World Bank Institute. (2008). Mexicos transition to a knowledge-based economy:Challenges and opportunities. Washington, DC: WBI Press.

World Bank Institute. (2009). The capacity development results framework: A strategicand results-oriented approach to learning for capacity development. Washington:WBI Press.

Yigitcanlar, T. (2009). Planning for knowledge-based development: Globalperspectives. Journal of Knowledge Management, 13(5), 228–242.

Yigitcanlar, T. (2010). Making space end place for the knowledge economy:Knowledge-based development of Australian cities. European Planning Studies,18(11), 1769–1786.

Yigitcanlar, T., & Lonnqvist, A. (2013). Benchmarking knowledge-based urbandevelopment performance. Results from the international comparison ofHelsinki. Cities, 31(1), 357–369.

Yigitcanlar, T., O’Connor, K., & Westerman, C. (2008). The making of knowledgecities: Melbourne’s knowledge-based urban development experience. Cities,25(2), 63–72.

Zucker, L. G., Darby, M. R., & Brewer, M. B. (1999). Intellectual capital and the birthof US biotechnology enterprises: National Bureau of Economic Research. In J.Niosi (Ed.), Regional systems of innovation: Market pull and government push.Montréal: McGill-Queen’s University Press.