Innovation Manager, Management Knowledge

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(El Gerente de Innovación, Gerencia de la generación del conocimiento, ..... the major drivers of innovation, Peter Drucker, it can see his seven sources for ...
Quote: Tarazón et al. (2016). Reference: Tarazón C, J. C., Hernández G., G. J., Lee B., C. García G., M. J. & Hernández R., J. G. (2016). Innovation Manager, Management Knowledge Generation, Logistics and some Multicriteria models, Eureka 2016, Torreón, México, 1-13.

Innovation Manager, Management Knowledge Generation, Logistics and some Multicriteria models (El Gerente de Innovación, Gerencia de la generación del conocimiento, Logística y algunos modelos multicriterios) Jean C. Tarazón C1., Gilberto J. Hernández G.2, Carlos Lee B.1, María J. García G.2 & José G. Hernández R.2 1 Universidad Metropolitana, Venezuela. 2 Minimax Consultores C. A., Venezuela.

Abstract In this paper a relationship between business logistics, knowledge management (KM), innovation and multicriteria models is established. For businesses, generation and KM it is very important and they should always be alert to the knowledge generated in their environment. One approach used successfully, it is to harness the full interrelationship of business logistics, with the organization, for use as the driving force of generation and KM. In particular there have been used positions of the Logistic Model Based on Positions (LoMoBaP, [MoLoBaC]) to analyze the generation and KM through them. But the MoLoBaC does not include the Innovation Manager (IM), which is a source of generation of knowledge in the organizations, of there, to make use of it; it is interesting to study the incorporation of the IM to the MoLoBaC. In trying to incorporate the IM to MoLoBaC arise several alternatives and at the same time criteria for study which of them is the convenient. This requires the use of a multicriteria model. From the above, the objective of this research arises: To present some models multicriteria that could be used to choose the best alternative to incorporate the Innovation Manager, understood as a generating entity of knowledge, to the Logistic Model Based on Positions. To achieve this objective, it will use the Integrated-Adaptable Methodology for the development of Decision Support System. Keywords: Generation and knowledge management, Multicriteria models, Innovation Manager (IM), Decision making (DM), Logistic Model Based on Positions (LoMoBaP [MoLoBaC]).

Introduction There are many works in which a close relationship between innovation and knowledge management (KM) are presents (Deitmer, 2011; Gholami et al., 2013; Gichuki, 2014; Issam & Al-Makhadmah, 2015; Jaca et al., 2016; Madeira, Vick & Nagano, 2013; Makhsousi, Sadaghiani & Amiri, 2013; Maracine & Scarlat, 2009; Neumann & Tomé, 2010; Nnabuife, Onwuka & Ojukwu, 2015; Olliver & Ordóñez, 2013; Shang, Lin & Wu, 2009). There are also works that show the relationship between innovation and logistics (Dekker, Bloemhof & Mallidis, 2012; Flint et al., 2005; Marasco, 2008); although in some cases it is done through the Supply Chain (SC) (Mollenkopf et al., 2010). In the same way in the papers presented by De Burgos et al. (2016), García, Hernández & Hernández (2014a), Hernández, García & Hernández (2016) and Jeney et al. (2015), shows a close relationship between logistics and (KM) and reference it is made to a series of papers that discuss the impact that KM has on organizations and where most of them are also related to innovation (Abiodun, 2014; Madeira, Vick & Nagano, 2013; Makhsousi, Sadaghiani & Amiri, 2013; Maracine & Scarlat, 2009; Neumann & Tomé, 2010; Nonaka & von Krogh, 2009; Shang, Lin & Wu, 2009; Wan et al., 2010). On the other hand other works can be mentioned as of Carter & Rogers (2008), that is focuses on the logistics and the KM but, additionally, make slight allusions to

innovation. This allows deducing that the three areas: the business logistics, KM and innovation, are necessarily related, what it is possible to see more clearly in works as of Sarkis, Zhu & Lai (2011) and particularly the work of Esper et al. (2010), where the KM plays the role of an integrator of the three fields of knowledge. But it is also interesting to note the works of Brandenburg et al. (2014) and Dekker, Bloemhof & Mallidis (2012), who present the possibility of studying aspects of logistics and Supply Chain Management (SCM) through multicriteria models, which are the other topic of interest in this research. For this work the integrating elements will be mainly logistics and KM. With regard to logistics and KM, the studies presented by De Burgos et al. (2016), García, Hernández & Hernández (2014a), Hernández, García & Hernández (2016) and Jeney et al. (2015) have been made through the Logistic Model Based on Positions (LoMoBaP [MoLoBaC]), which explains the logistics through functions that perform those who play positions related to the same. However among the forty and four positions that integrate the MoLoBaC does not include the Innovation Manager (IM). The latter aspect attracted attention of Tarazón (2016), who proposed to investigate, how it was possible to realize the integration of the IM to the MoLoBaC. In his study Tarazón (2016), found several alternatives, through which it could perform the integration. And when trying to study which of these alternatives was more favorable, a series of criteria emerged, which made the study a multicriteria problem. In this work there will not be carried out the study or selection of the best alternative, nevertheless if it is desirable to present as the models multicriteria they can be of big utility in this type of problems. All of the foregoing arise the objective of this research, which more than a quantitative study is a theoretical approach on the relationship of four areas of knowledge of great importance: Knowledge management, multicriteria models, business logistics and innovation. It stating, from there, the general objective of the work: To present some models multicriteria that could be used to choose the best alternative to incorporate the Innovation Manager, understood as a generating entity of knowledge, to the Logistic Model Based on Positions. This general objective has three specific objectives: - To explain how there works the relation of the Logistic Model Based on Positions (MoLoBaC) with the Knowledge Management (KM). - To present some alternatives for the inclusion of the functions of innovation to the MoLoBaC. - To discuss as it was possible to choose some multicriteria model to select the alternative of incorporation of the functions of innovation to the MoLoBaC. With regard to the limitations and scope, this research will be more qualitative than quantitative and there will not be any field study, but will analyze how a multicriteria model could be used to select the best integration alternative.

Methodology In order to achieve the objectives will follow the Integrated-Adaptable Methodology for the development of Decision Support System (IAMDSS, in Spanish, Metodología Integradora-Adaptable para desarrollar Sistemas de

Apoyo a las Decisiones [MIASAD]) (García, Hernández & Hernández, 2014b), which features include its flexibility and adaptability to different types of research (De Burgos et al., 2016; García, Hernández & Hernández, 2014a; Hernández, García & Hernández, 2016; Jeney et al., 2015; Schwarz et al., 2016), by which they can be used of it, only the steps that are considered to be important, of there, similar to the realized in other works (De Burgos et al., 2016; García, Hernández & Hernández, 2014a; 2014b; Hernández, García & Hernández, 2016; Jeney et al., 2015; Schwarz et al., 2016) only the following steps will follow: a) To define the problem that, as is indicated in the objectives, is to present some models multicriteria that could be used to choose the best alternative to incorporate the Innovation Manager (IM), understood as a generating entity of knowledge, to the Logistic Model Based on Positions (MoLoBaC); b) Elaborate a first prototype, whose first mission is to offer a vision, as complete as possible, of what will be the research and additionally it must allow to identify the users of the final product, that is to say the main readers of this article, which will be all those interested in the processes of innovation, in the generation of knowledge and business logistics, beside the interested in multicriteria models. The second mission of the prototype is to establish the structure of the article, which in addition to the introduction and methodology will consist of three central chapters, in the first one, MoLoBaC and IM will be presented, with more emphasis on the functions of innovation, than the IM itself, in the second chapter will present the relationship between innovation and knowledge management (KM) and in the third chapter will discuss some multicriteria models that could be used to make the selection of the incorporation alternative; culminating these main chapters will be presented some conclusions and recommendations and the references used in the development of the work; c) Obtain data, in this case on innovation, KM, MoLoBaC, and multicriteria models; d) Establish alternatives, which would be the different ways to analyze how to choose the best option to incorporate the functions of the IM to the MoLoBaC; e) Evaluate alternatives, analyze the pros and cons of several multicriteria models, that could be used to analyze the alternatives of incorporation of the functions of the IM to MoLoBaC; f) To select the alternative, according to the previous evaluation and considering the secondary objectives, whether they are tacit or explicit; g) Implementing the best alternative, although no implementation will be done in this work, it should be illustrated how the chosen model can be used to carry out the selection; h) Establishing controls, the mechanisms, that allows to recognize if the solution obtained, continues being valid in the course of the time.

The Logistics Model Based on Positions and the Innovation Manager The Logistics Model Based on Positions (MoLoBaC), is a qualitative-quantitative model that has emerged in academia to facilitate the teaching of business logistics, which is explains through the functions performed by all those who hold positions related to logistics (De Burgos et al., 2016; García, Hernández & Hernández, 2014a; Hernández, García & Hernández, 2016; Jeney et al., 2015; Schwarz et al., 2016; Tarazón, 2016).

As can be seen in figure 1, at present MoLoBaC is made up of forty-four positions, each identified by a number. These positions are grouped in areas and these in turn in stages. Logistics General Manager Hernández J. y García M. 40

39

Projects Manager

26

Human resources Manager

43

External Relations Manager

33

35

Forecasting Manager

42

Industrial Security Manager

O4

Procure Manager

O3

O1

Layout Manager

O2

Maintenance O9 General M anager

O5

O2 18 21 36

Quality Manager

Customer Service

25 General Manager

Routes Manager

Spare and Equipment 12 Manager

Handling of Materials 24 Manager

32

Fleet Manager

13

Inventory Models Manager

23

Raw Material Manager

31

Packing Manager

21

Stores Manager

Other Inputs Manager

30

Location Manager

Physical Distribution 29 Manager

Major Maintenance O7 Manager

Reverse Logistics

Manager

Other Supply and Services Systems of Information and Networks Stores of the whole organization Compilation and Reception

37

Reliability and S.

O8

Manager

= Supplying = Production = Distribution = Reverse = General = Information

36

O8 19 28 42

Manager

C. and Reception Manager

41

Environmental Manager

R&D 19 General Manager

Syst. of Inform. and Networks

18

Manager

Industrial Design Manager

17

New Technologies Manager

22

Picking Manager

16

Virtual Channel Manager

28

Channels Manager

15

Expansion Manager

27

Expedition Manager

11

Finance Manager

10

Costs Manager

Classification and Use

38 General Manager

Preventive Maintenance

O6

Order Processing

Inventory 14 General Manager

44 General M anager

Transport 34 General Manager

Ethical & Juridical Consultant

M arketing and Selling

20

Manager

Reliability and Substitution Research and Development Distribution channels: Major and Retail Industrial Security and Internal Relations

Fig. 1. Logistic Model Based on Positions (LoMoBaP [MoLoBaC]) The six stages of MoLoBaC are (Hernández, García & Hernández, 2012; 2016): a) Supplying, which is formed by a single area, Procure, which is pure, since it is integrated by positions of only one stage, b) Production, composed of two areas, Maintenance and Inventories, both pure, c) Distribution, composed of four areas: Order Processing, the first of the mixed areas, since it integrates by positions of the stages Production and Distribution; Physical Distribution, other pure area; Transportation, the second mixed area formed by positions of the stages Distribution and General to the company and the area that comes to be the reason of the being of the model, Costumer Service, that also is pure, d) Inverse, formed an unique pure area, Inverse logistic, e) General to the company, composed of three areas: Intrinsic to logistics, Supported by logistic and Supporting logistics, all three areas pure and finally f) General to information, formed by the latter of the areas, which is mixed, Information, since it has positions of the stages General of the company and the own ones of General of information. It can also be seen, in figure 1, that there is no position, directly responsible for innovation. Actually it is not necessary that there is an Innovation Manager (IM) as such, what if is necessary is that the functions relative to this field of knowing are present. So the first thing that must be done is to identify what is the field of performance of

that would be recognized as IM. But as in this work the link between logistics and innovation is set through the Knowledge Management (KM), it will be necessary, to make comments about the innovation processes and KM.

Some comments about Innovation and Knowledge Management As a starting point, it can be said that it is difficult to agree on a definition of innovation. Already in the last century Han, Kim & Srivastava (1998) pointed out that from the point of view of marketing, the term innovation is associated largely to new developments related to the product. They also noted (Han, Kim & Srivastava, 1998) that when speaking of technical innovations refers to the products, services and technology of production processes and are related to the basic activities of productive work, contrasting this definition with administrative innovation, which focuses on the organizational structure and administrative processes, being indirectly related to the basic activities of the work of the organization. At the end of the last decade Dahlander & Gann (2010), through open innovation, let it see that it allows the use of ideas both internal and external, as well as follow internal and external paths to the market, to facilitate its advance, mainly technological. For its part Sarkis, Zhu & Lai (2011) indicate that innovation is communicated through particular channels and between the members of a certain social system and equally they annotate that the innovations arise to tackle organizational and technological problems and that are the response of the organizations to confront the pressures in this sense. This affirmation coincides with the concept of Morris & Sexton (1996) those who express that the innovation refers to the search of creative, unusual or new solutions to the problems and needs. And at the end of their work they indicate (Morris & Sexton, 1996), that innovation can be new in the world, new in the market or be modifications or additions made to the environment of the organization itself, with regard to what is routinely done. But it is important to emphasize the statement of Guthrie & Dawe (2004) that only when that something new or different arrives to be marketed or applied in favor of the community, is when it can be called innovation. This is reinforced by Curtin & Stanwick (2011), with an emphasis on what to add value to organizations and society. Again with Sarkis, Zhu & Lai (2011), which suggest that innovation, can be seen as a process that goes through different phases: initiation, persuasion, planning, adoption and confirmation. For his part Tarazón (2016) affirms that the innovation process generates benefits, growth, organizational changes and continuous improvements. From a social point of view Pedraza & Velásquez (2013) see the innovation associated with the development of any country and affirms that to speak of economic development is to speak of the capacity to innovate. For their part Ollivier & Ordóñez (2013) highlight four types of innovations in companies: in the Product, including services here, in the Process, in Marketing and in the Organization of the company as a whole. In the book of Hattori & Wycoff (2004) it is read that innovation is a set of thoughts, principles and practices, skills, tools and techniques that arise when it believes in a better future. And these authors (Hattori & Wycoff, 2004) say that innovation is people implementing new ideas that create value. This last definition, as already mentioned, implies that there is no innovation, if no value is created and in addition, it should be remembered that innovation is associated with marketing or improvements in marketing.

From all of the above, for this work, without pretending to give a universal concept, there will be admitted as innovation any change, invention or creative process, which should add value to the organizations or to the society as whole, on having modified current aspects, which improve the commercialization of the products and with it, the quality of life. One had already mentioned that many authors have studied the relation between innovation and the Knowledge Management (KM). Even it is possible to affirm that the innovation is intrinsically related to the effective creation, management and diffusion of the knowledge (Rice, 2011). Following this close relationship between innovation and KM and taking as a source to who is considered one of the major drivers of innovation, Peter Drucker, it can see his seven sources for innovation (Drucker, 2011): 1. The Unexpected, in it respect both successes and failures, 2. The Incongruent, between the present reality and the reality as it is assumed or should be, 3. The Process needs, those are generally associated with production commitments, 4. Structural changes, those are whether in industry or in the market, 5. Demography, variations, those are not only in population growth or decline, but in any other demographic aspect, such as distribution, 6. Perception, mood and meaning, it is the sense or mood with which things are perceived and 7. New knowledge, it include both scientific and non-scientific. And this last source for innovation, establishes a clear bridge between innovation and KM. Besides Drucker (2011) said that there is usually a time, sometimes extensive, between the generation of knowledge and its conversion into innovation. But reducing this gap in the time since knowledge is produced, until it is put into practice, in many cases it is achieved, only, through a good KM and this, in turn, is only possible if the organization, as a whole, is prepared for it. Another aspect that can be highlighted is the relationship between innovation and science, as expressed Gessler (2003): Innovation in science requires new ways of seeing the world, new ways of seeing old theories and data. It requires recognizing the complexity and new forms of knowledge and seeing what has not been seen before. Equally it is necessary to emphasize the affirmation of Damiano (2011), that the search of new knowledge is innovative for definition. Also it is important to attract attention in the cycle KM-Innovation-KM (Gichuki, 2014), where the KM allows and facilitates the appearance of innovation and this in turn protects the loss of KM and thus in a constant cycle. In relation to the KM, in this work, already it appeared the Logistics Model Based on Positions (MoLoBaC), on which has arisen an extensive line of research, in which the positions or areas of this model are used, to study how knowledge can be generated and managed in an organization. Evidence from these studies is found in De Burgos et al., (2016), García, Hernández & Hernández, (2014a; 2014b), Hernández, García & Hernández (2016) and Jeney et al. (2015) and in works, related to this subject, cited by them, especially the initial work (Hernández, García & Hernández, 2012). For all these works are followed the model SECI or spiral model of Nonaka, Toyama & Konno (2000), following the scheme created by Barreto (2012). This model analyzes KM in four processes: Socialization, Externalization, Combination and Internalization (SECI), which are happening through a continuous spiral following the steps of tacit-explicit-tacit knowledge and under a suitable environment, called Ba (Nonaka, Toyama & Konno, 2000).

It was also discussed, the possibility of including the functions related to the innovation process to MoLoBaC (Tarazón, 2016) and from it arise the alternatives of incorporation of the same. The first option, the most natural one, is to create a new manager, the Innovation Manager (IM), but this would imply a structural modification of the model, so other alternatives should also be explored. A second alternative, would be to distribute the functions of innovation processes between each one of the forty and four present posts and other possible alternative would be to integrate the functions of innovation to a few of the current positions or include in a single position and for the latter two cases, the main positions to consider because of their special characteristics, would be: the New Technologies manager (NTM) (17), the Research & Development manager (R&DM) (19), the Projects manager (PrM) (39) and the Customer service general manager (CSM) (44). The NTM because although not all the innovations have to be technological, many of them could be under its scope and in the MoLoBaC, this position is a clear candidate to participate in the whole process of technology transfer (Tarazón, 2016); the R&DM, in the MoLoBaC it is seen as an element of liaison and support of the entire research and all new development that is done in the organization (Hernández et al., 2014; Tarazón, 2016), in addition is the immediate supervisor of the NTM; the PrM, because for the MoLoBaC is a meta manager, which is involved in all the projects that the organization undertake (Barreto, 2012) and the CSM, because this is the position of closure of the MoLoBaC and its main function is to direct all efforts of the organization toward the end customer (Hernández, García & Hernández, 2012) and it was commented that innovation must have a marketing function. In the Tarazón (2016) work, were used as alternatives the R&DM (19), the NTM (17) and to create a new position the Innovation manager (IM) (45), in reality would not have to be the position 45, since it would necessarily modify the structure of MoLoBaC. After a conscientious analysis Tarazón (2016) presented as possible criteria for the selection: Criteria related to the development of products of innovation, Criteria related to the intelligence of the market and Criteria related to the process of innovation, to these three main criteria, were associated a series of secondary criteria: Development of tests, Development of prototypes, Analysis of results of studies with consumers, Handling of the process of innovation, Execution of multifunctional meetings and Evaluation of opportunities of innovation. Analyzing the criteria presented by Tarazón (2016), but remembering that for this work, the concern is focused on seeing the best way of incorporating the functions of innovation into the MoLoBaC, it was decided for this investigation to propose other different criteria, which will be presented in the next section. Having presented the situation to study, where it has a series of alternatives and a set of criteria that would allow them to be evaluated, it is possible to see that is facing a problem multicriteria, by which, next, there will be realized a brief discussion of possible multicriteria models, that could be used to select the best alternative of incorporation of the functions of innovation to the MoLoBaC.

Multicriteria models that could be used to choose the alternative of incorporating the innovation functions into MoLoBaC The number of multicriteria models that exist is very broad, however in this paper only four of them will be discussed, for two simple reasons, the first that were studied by Tarazón (2016) in his work and the second that two of them are the most used (Analytical Hierarchical Process [AHP] and Analytical Network Process [ANP]) (Hernández, García & Hernández, 2014; Saaty, 2008; 2010; Saaty & Vargas, 2006) and two of them are the easiest to implement (Matrixes Of Weighing with Multiplicative factors [MOWwMf] and Multiattribute Model with Multiplicative factors [MMwMf]) (García & Hernández, 2011). As already explained, in this work no quantitative analysis will be done, nor will it lead to the selection of a model or set of models. Only some general comments will be made, of the four models (AHP, ANP, MOWwMf and MMwMf) that were taken as candidates to select the alternative of incorporating the functions of innovation to MoLoBaC. As explained in the previous section, after a thorough analysis it was decided to take into consideration the following alternatives and criteria. Alternatives: 1. An Innovation manager (IM), 2. All the positions of the MoLoBaC, 3. The Research and Development manager (R&DM), 4. The Projects manager (PrM), 5. The Customer service manager (CSM), 6. The R&DM and the PrM, 7. The R&DM and the CSM, 8. The PrM and the CSM and 9. The R&DM, the PrM and the CSM. Criteria: 1. That facilitates the studies of Knowledge Management (KM), 2. Minimal disruption of the model, 3. Facility to individualize the functions of innovation, 4. Clarity in the moment to study each of the functions, 5. Consistency with the rest of the model, 6. Possibilities to be able to differentiate each function, 7. Affinity of all functions that belong to a position, 8. Avoid large number of functions in each of the positions and 9. Minimal dispersion of the information. Although there is no discussion about the reasons that motivated the choice of alternatives that were finally considered, if it is necessary to clarify why was discarded the New Technologies manager (NTM), in order not to direct innovations to a single area and additionally, because this manager would be covered by the R&DM who is his immediate supervisor. Presented all this information only remains to do some very brief comments about each one of the mentioned models and some very general comments that it allows to have an idea of the strengths and weaknesses of each one of them to carry out the selection, of the best alternative, of the nine proposals, following the criteria that were determined. AHP.- It is a technique based on paired comparisons and helps to prioritize criteria and alternatives. And although it has been frequently criticized for its failures from a quantitative point of view, and it can even be doubted that it is a Decision Making Model (MDM), is one of the techniques that most figure in the literature, when speaking of multicriteria problems (Hernández, García & Hernández, 2014).

ANP.- Can be considered an improvement of the AHP and its main differentiation and characteristic is that it allows decision making of alternatives whose elements interact with respect to the criteria to be evaluated (Saaty, 2010; Tarazón, 2016). Unfortunately, when solving a problem with ANP is made use of AHP, so in a certain way are inherited the quantitative faults of this. MOWwMf.- They are, as its name implies, a simply arrangement of rows and columns, which is used to value alternatives through a set of weighted criteria (García & Hernández, 2011). MMwMf.- They are those models that are designed to obtain the utility of alternatives through the valuable attributes, which should be evaluated as components of the criteria. In any case the final result is an additive model very easy to implement (García & Hernández, 2011). As a final point of this work, to have a little more clear vision of the weaknesses and strengths, of the four models, in the table 1, will present some characteristics that must have a good multicriteria model to offer robustness in the solutions that can present. Table 1. Characteristics of a good multicriteria model. Characteristics Facility of creation of the model Facility of implementation Literature that supports it Is it possible to know if the select solution is good? Does it depend on the alternatives?

AHP It can need some work

The four models to compare ANP MOWwMf In general requires a Very easy lot of work

MMwMf Easy

It needs some work

Requires a lot of work

Very easy

Easy

Very abundant

Abundant

Very scarce

Slightly scarce

No. Only hierarchy

No. The solution is not clearly justified

Yes

Yes

Completely

Completely

No

No

Does it depend on the decision taker?

Yes. It can reach a different result to change the decision maker

Yes. It can reach a different result to change the decision maker

No

No

Can different levels be interrelated?

No

Yes

Not directly

Not directly

Does requires the use of experts?

Yes. It can reach different results when changing the experts

Yes. It can reach different results when changing the experts

Recommended to define the model, but it is not dependent on them for the evaluation

Recommended to define the model, but it is not dependent on them for the evaluation

Need for specialized software

In general it is necessary the use of Expert Choice

In general it is necessary the use of Super Decisions

No. Are resolved in an Excel worksheet

No. Are resolved in an Excel worksheet

Not in a direct way

Not in a direct way

Yes. The model does not depend on the alternatives

Yes. The model does not depend on the alternatives

By relying on alternatives, it requires redoing much of the work

By relying on alternatives, it requires redoing much of the work

Yes, alternatives at all times. The criteria very easily

Yes, alternatives at all times. The criteria very easily

Ability to handle a large number of alternatives Does it can incorporate, modify or delete criteria and alternatives?

Without intending to make judgments, since it was not the objective of this work, with the comments emptied in table 1, it has a clear idea of the strengths and weaknesses, which speak of the robustness of the different models selected. With this information it can go directly to submit some conclusions and recommendations.

Conclusions and recommendations In this work are presented and related four very important areas of the business activity and of human knowledge: business logistics, knowledge management (KM), innovation and multicriteria models. Using KM and business logistics as linking elements, relations were obtained of: the KM and the innovation, the innovation and the logistics, the KM and the logistics, the logistics and the multicriteria models and finally a clear relation between four topics in study. The relationship between innovation and the KM was made in such a way theoretical, through the specialized literature. The relationship between logistics and KM was made through the Logistics Model Base don Positions (MoLoBaC), since through their positions it can study the KM of an organization. MoLoBaC was also used to establish a relationship between logistics and innovation, since it was possible to study the incorporation of the functions of innovation to this model. And finally, when it presenting the alternatives of incorporating the innovation functions to the MoLoBaC, it arise the possibility of using multicriteria models. Thus is established a relation between the four areas of knowledge under study. To make some brief comments on four multicriteria models, that could be used to select the best alternative for the incorporation of the functions of innovation to MoLoBaC, it finished of to comply with the specific objectives and the overall objective of the work. Of there a few recommendations can arise, the first would be to complete this study, making a quantitative assessment, to detect which must be the chosen alternative. And a more general recommendation would be to deepen the study of the relationship between these four important areas of knowledge: the innovation, the KM, the logistics and the multicriteria models.

References Abiodun, B. (2014). Comparative analysis of the challenges of generic engineering logistics to humanitarian logistics in disaster response and relief support in South Africa, Master dissertation, University of Johannesburg, Johannesburg, South Africa. Barreto O., E. A. (2012). Gestión del conocimiento a través del Gerente de Proyectos de un modelo logístico, Disertación Maestría en Administración, mención Gerencia de empresas, Universidad Metropolitana, Caracas, Venezuela. Brandenburg, M., K. Govindan, J. Sarkis & S, Seuring (2014). Quantitative models for sustainable supply chain management: Developments and directions, European Journal of Operational Research, 233(2), 299-312. Carter, C. R. & D. S. Rogers (2008). A framework of sustainable supply chain management: Moving toward new theory, International Journal of Physical Distribution & Logistics Management, 38(5), 360-387.

Curtin, P. & J. Stanwick (2011). Overview, in Curtin, Stanwick & Beddie (Ed), Fostering enterprise: the innovation and skills nexus–research readings, National Centre for Vocational Education Research (NCVER): Australia, 1017. Dahlander, L. & D. M. Gann (2010). How open is innovation?, Research policy, 39(6), 699-709. Damiano Jr., R. J. (2011). What is Innovation?, Innovations: Technology & Techniques in Cardiothoracic & Vascular Surgery, 6(2), 65. De Burgos J., J., M. J. García G., G. J. Hernández G. & J. G. Hernández R. (2016). Generation and Management Knowledge. A View from the Manager of Packing, Proceedings ICIL2016, AGH University of Science and Technology in Krakow, Krakow, Poland, 32-44. Deitmer, L. (2011). Building up the innovative capabilities of workers, in Curtin, Stanwick & Beddie (Ed), Fostering enterprise: the innovation and skills nexus–research readings, National Centre for Vocational Education Research (NCVER): Australia, 38-51. Dekker, R., J. Bloemhof & I. Mallidis (2012). Operations Research for green logistics - An overview of aspects, issues, contributions and challenges, European Journal of Operational Research, 219(3), 671-679. Drucker, P. (2011). Innovation and entrepreneurship, AudioTech BusinessBook Summaries, USA. Esper, T. L., A. E. Ellinger, T. P. Stank, D. J. Flint & M. Moon (2010). Demand and supply integration: a conceptual framework of value creation through knowledge management, Journal of the Academy of Marketing Science, 38(1), 5-18. Flint, D. J., E. Larsson, B. Gammelgaard & J. T. Mentzer (2005). Logistics innovation: A customer value-oriented social process, Journal of Business Logistics, 26(1), 113-147. García G., M. J. & J. G. Hernández R. (2011). Multiattribute Model with Multiplicative Factors and Matrixes Of Weighing and the Problem of the Potable Water, in R. Espín, J. Marx & A. Racet (Eds.), Towards a Transdisciplinary Technology for Business Intelligence, Gathering Knowledge Discovery, Knowledge Management and Decision Making, Shaker: Germany, 364-374. García G., M. J., G. J. Hernández G. & J. G. Hernández R. (2014a). Knowledge management through the Material Handling Manager, In Dukic (Ed.), Proceedings ICIL’2014, University of Zagreb, Zagreb, Croatia, 264-272. García G., M. J., G. J. Hernández G. & J. G. Hernández R. (2014b). A Methodology of The Decision Support Systems applied to other projects of Investigation, In Mehdi K. (Ed.), Encyclopedia of Information Science and Technology, Third Edition: Hershey, PA: IGI Global, V3, 1978-1990. Gessler, N. (2003). Evolving Artificial Cultural Things-That-Think and Work by Dynamical Hierarchical Synthesis, in Proceedings of Association for the Advancement of Artificial Intelligence. Gholami, M. H., M. N. Asli, S. Nazari-Shirkouhi & A. Noruzy (2013). Investigating the influence of knowledge management practices on organizational performance: an empirical study, Acta Polytechnica Hungarica, 10(2), 205-216. Gichuki, M. (2014). Achieving competitive advantage through knowledge management practices by the hotels in the coastal region, Kenya, Dissertation Master of Business Administration, University of Nairobi, Nairobi, Kenya. Guthrie H. & S. Dawe (2004). Overview, in Dawe S. (Ed), Vocational education and training and innovation. Research readings, Australian National Training Authority (ANTA): Australia, 10-19.

Han, J. K., N. Kim & R. K. Srivastava (1998). Market orientation and organizational performance: is innovation a missing link?, The Journal of marketing, 62(4), 30-45. Hattori, R. A. & J. Wycoff (2004). Innovation training, American Society for Training and Development, USA. Hernández, J. G., M. J. García & G. J. Hernández (2012). Dynamic knowledge: Diagnosis and Customer Service, in N. Delener (Ed.), Service Science Research, Strategy, and Innovation: Dynamic Knowledge Management Methods. IGI Global: USA, 547-573. Hernández G., J. J., M. J. García G., G. J. Hernández G. & J. G. Hernández R. (2014). Fantastic Sports and the Research and Development Manager of the Logistic Model Based on Positions, in Dukic G. (Ed), ICIL 2014 Conference Proceedings, Croatia, University Zagreb, 250-257. Hernández R., J. G., M. J. García G. & & G. J. Hernández G. (2014). Shelter Selection with AHP Making Use of the Ideal Alternative, in Mehdi K. (Ed.), Encyclopedia of Information Science and Technology, Third Edition: Hershey, PA: IGI Global, V3, 2003-2015. Hernández R., J. G., M. J. García G. & G. J. Hernández G. (2016). Logistics, Marketing and Knowledge Management in the Community of Consumers, in S. Buckley, G. Majewski & A. Giannakopolus (Ed), Organizational Knowledge Facilitation through Communities of Practice in Emerging Markets, IGI Global: USA, 242-268. Issam, D. O. M. A. A. & M. Al-Makhadmah (2015). The Influence of Knowledge Management on Organizational Performance in Service Organizations in Jordan, Information and Knowledge Management, 5(12), 42-48. Jaca, C., M. Zárraga-Rodriguez, E. Viles & M. J. Álvarez (2016). Exploring Information Capability and its Role in Innovation, Revista de Globalización, Competitividad y Gobernabilidad, 10(1), 66-81. Jeney, A., J. G. Hernández, M. J. García & G. J. Hernández (2015). Generation and Knowledge Management through the System information and network Manager, In Delener N. et al. (Eds.), Reading Book GBATA 2015: GBATA, 244-251. Madeira, L. M. M., T. E. Vick & M. S. Nagano (2013). Directions of scientific literature in knowledge management from the perspective of their relationships with innovation, information and technology management, Transinformação, 25(2), 167-174. Makhsousi, A., J. Sadaghiani & M. Amiri (2013). Investigating different cultural factors on establishment of knowledge management in educational organization, Management Science Letters, 3(2)2, 581-586. Maracine, V. & E. Scarlat (2009). Dynamic Knowledge and Healthcare Knowledge Ecosystems, The Electronic Journal of Knowledge Management, 7(1), 99-110. Marasco, A. (2008). Third-party logistics: A literature review, International Journal of Production Economics, 113(1), 127-147. Mollenkopf, D., H. Stolze, W. L. Tate & M. Ueltschy (2010). Green, lean, and global supply chains, International Journal of Physical Distribution & Logistics Management, 40(1/2), 14-41. Morris, M. H. & D. L. Sexton (1996). The concept of entrepreneurial intensity: Implications for company performance, Journal of Business Research, 36(1), 5-13.

Neumann, G. & E. Tomé (2010). Functional Concept for a Web-Based Knowledge Impact and IC Reporting Portal, Electronic Journal of Knowledge Management, 8(1), 119-128. Nnabuife, E. K., E. M. Onwuka & H. S. Ojukwu (2015). Knowledge Management And Organizational Performance In Selected Commercial Banks In Awka, Anambra State, 9igeria, IOSR Journal of Business and Management, 17(8, I), 25-32. Nonaka, I., R. Toyama & N. Konno (2000). SECI, Ba and leadership: A unified model of dynamic knowledge creation, Long Range Planning, 33, 5-34. Nonaka, I. & G. von Krogh (2009). Tacit knowledge and knowledge conversion: Controversy and advancement in organizational knowledge creation theory, Organization Science, 20(3), 635-652. Ollivier F., J. O. & A. Ordóñez P. (2013). La influencia de la Gestión del conocimiento en la Innovación en empresas Mexicanas, en XVIII Congreso Internacional de Contaduría y Administración e Informática, Anfeca, México. Pedraza A., E. M & J. A. Velázquez C. (2013). Oficinas de Transferencia Tecnológica en las Universidades como Estrategia para Fomentar la Innovación y la Competitividad: Caso: Estado de Hidalgo, México, Journal of technology management & innovation, 8(2), 221-234. Rice, J. (2011). Innovation in the modern economy, in Curtin, Stanwick & Beddie (Ed), Fostering enterprise: the innovation and skills nexus–research readings, National Centre for Vocational Education Research (NCVER): Australia, 18-27. Saaty, T. L. (2008). Decision making with the analytic hierarchy process, International Journal Services Sciences 1(1), 83-98. Saaty, T. L. (2010). Principia Mathematica Decernendi: Mathematical Principles of Decision Making, RWS Publications, USA. Saaty, T. L. & L. G. Vargas (2006). Decision Making with the Analytic 9etwork Process. Economic, Political, Social and Technological Applications with Benefits, Opportunities, Costs and Risks, Springer, USA. Sarkis, J., Q. Zhu & K. Lai (2011). An organizational theoretic review of green supply chain management literature, International Journal of Production Economics, 130(1), 1-15. Schwarz I., L. M. T. M. Schwarz I., M. J. García G., G. J. Hernández G. & J. G. Hernández R. (2016). Social Impact of Restrictions on Inventory Management, Proceedings ICIL2016, AGH University of Science and Technology in Krakow, Krakow, Poland, 272-282. Shang, S. S. C., S. Lin & Y. Wu (2009). Service innovation through dynamic knowledge management, Industrial Management & Data Systems, 109(3), 322-337. Tarazón C., Jean C. (2016). El Gerente de Innovación del Modelo Logístico Basado en Cargos: Posible inclusión al modelo y su funcionalidad en una comercializadora de aperitivos, Disertación Ingeniería de Producción, Universidad Metropolitana, Caracas, Venezuela. Wan, J., H. Zhang, D. Wan & D. Huang (2010). Research on knowledge creation in software requirement development, Journal of Software Engineering & Applications, 3, 487-494.