Networks in marketing

Published on Author Suchen

Networks are crucial parts of any action taken in a marketplace . [1] Peter Drucker [2] also described the future economy as one of a society of networks. Companies in these networks stand to gain a lot. [3] [4] There are a number of different networks, which have distinct relevance to customers, [4] and marketing initiatives. A network in marketing can be either strategically (eg Business networking ) or completely randomly (eg Referral economy ). Marketing channels and business networks-have-been Referred to, by Achrol & Kotler [3] as:

“Interdependent systems of organizations and relations which are involved in the production of and production of marketing services in the supply of products and services.

Achrol & Kotler [3] stated that these networks are not accepted as such. Suggesting that organizational hierarchy, power and contracts are now exchanged for instruments of relational control. Businesses such as Ford, Procter & Gamble, and General Electric have evolved in much the same. It was not until long ago that they were organized as classic hierarchies. Displaying central control, unified purpose, and complex management structure of many third parties. [3]

Business and marketing networks differ in the amount of connectivity between agents. Some markets, which are more fragmented, have less connectivity between agents than others. On top of this, the level of complexity differs entre various networks, some sccm May and ordered Rather linear, whereas other random and chaotic . As a network develops, the agents or entities form relationships with others, which increases the efficiency of operations. Although, this inevitably adds complexity to other simple networks, and makes them more prone to chaos.

Networks in general

A network is a web of interrelated lines, passages, or edges, intersecting at certain points, nodes, vertices, or places, which can be interlinked with other networks and contain sub networks. [5] Networks have been linked to the branches of mathematics , electronics, biology , and biosocial fields . Studies of inter-organization relations, and its networks, can be traced to early societies. [1]

History

In 1736, Leonhard Euler created graph theory . [6] Graph theory paved the way for network models Such As Barabási Albert’s scale-free networks, luck networks Such As Paul Erdös and Alfréd Rényi, Erdős-Rényi model , qui Applies to random graph theory, and Watts and Strogatz Small-world network , all of which can be accommodated in the marketplace.

With respect to marketing, much of the creation of theories around systems, structure, and the management of business networks, can arguably be attributed to early economists such as John Common, Ronald Coase, and Joseph Schumpter. [1] John Commons, in 1934, took ideas from the fields of law, economics, and psychology, and focused on transactions as a simple unit of analysis. Commons showed how to create a united kingdom and grow to deal with the conflict of interest between the agents and the united nations. [7]Joseph Schumpter, in 1939, focused on the processes underlying industrial organizations and how they have transformed. He showed how to fight for the survival of various types of businesses and networks. [8] Ronald Coase, in 1937, introduced the concept of transaction cost. His research is related to the development of the world of information systems [9] These three economists, Wilkinson stated, [1] have been especially influential in the development of the surrounding systems networks in marketing.

There are a number of notable historic studies, pieces of literature marketing networks. Theodore Macklin, in 1921, published a book called ‘Efficient marketing for agriculture’. He has emphasized the importance of local and regional marketing and the integration of small and medium-sized enterprises. [10] Wilkinson stated that his study can be seen as a precursor for research on marketing and economic evolution and the way of development of markets that enable the steps of economic specialization. [1]Another key study in the field by Ralph Breyer, in 1924. Breyer introduced the thought of marketing flows, depicting marketing frameworks in terms of the flow of electric current through wires, when connections are made. Distinguishing organization unit channels, enterprise channels, business type channels, and channel groups with respect to the number of business actors involved. [11] In 1940’s, there were signs that change was in order. Marketers by the names of Wroe Alderson , and Reavis Cox wrote in 1948, proposing a number of ways that marketing theory could be built upon. Alderson’s research depicted in the development of marketing thought and more specifically the structure and operations of channel networks and marketing institutions.[12] They seek to understand the nature of the work and the role of marketing organizations as they come into play.

These previously mentioned studies and pieces of literature demonstrate the creation of various ideas and thought surrounding networks in marketing. As the years have passed these concepts have developed and evolved, as will be shown.

1960s

Studies around this time had a focus on the economic structure of distribution channels , [1] A significant study by Cox, Goodman, and Fichandler, which was published in the previous research by Stewart, Dewhurst and Field (1939) and examined the distribution in a high level economy. [13] Bert McCammon, in 1963, enriched the field further. He drew from previous literature by Schumpter and Coase, bringing together research and ideas from a number of behavioral sciences exploring the processes of change in in-house systems. [14]

Other developments made in the 1960s were a number of models of channel systems. These models were created to study the many interactions taking place and how they affect performance. Wilkinson cited Forrester’s (1961) models of industrial dynamics and Balderston and Hoggat (1962) models of market processes and fundamental frameworks for following logistic models developed by Bowersox (1972) and his colleagues. [1]

1970s

WROE Alderson’s earlier writings. The first attempts were made to improve the concept of inter-firm relations towards the tail end of the 1970s. Major developments were undertaken by researchers such as Robicheaux. [15] The first marketing channels were created in 1976. [1] Research in this field was very limited in that studies were considered to be successful. Leading researchers to focus on the franchisor franchisee relations were more likely. [1]

1980s

As the 1980s dawned so too did another era of research into networks and its behavioral dimensions. A significant study by Phillips, in 1981, challenged the problem of various informants in inter-firm relations research. [1] Phillips suggests that the perceptions of a relationship differ across different informants in an organization. Putting into question the validity of many studies carried out in the prior years. It also shows that inter-organization relations involve personal relationships and interactions between many people in a company. [16]

Researchers also started to explore additional facets of inter-organizational relationships, combining them with more extensive models of relationships (eg Anderson and Narus [17] ). As Oliver Williamsons in 1975 on the issue of inter-firm governance, sparked interest again on economic theories. [1]

1990s

Literature around the 1990s brought together a number of research traditions. This is when the various types of marketing and marketing have been established. The connection between marketing services and the analysis of relations and networks emerged. There was also a focus on a competing relationship, which caused an eruption of interest in the region of relationships and networks. Furthermore, Researchers began directing more effort to network dimensions, as opposed to isolated dyadic relationship. Moreover, new technology has been used in the study of business networks, allowing for specific issues to be addressed. [1]

The developments made in the last several decades, demonstrated the evolution of pre-existing concepts and models in relation to networks in marketing, first proposed in the 1950s and 60’s. Wilkinson stated that it is necessary for the application of modeling techniques to portray networks in marketing, in order to strengthen current theories with empirical evidence. [1]

2000s to present

Various studies have used a number of methods to study business networks. [18] One such study conducted by Aino Halinen, and Jan-Åke Törnroos, looked at how networks are constructed and how they function in the modern day world. Giving insight into the use of case studies as a method of measurement. [19] Another key study, conducted by Jun, Kim, Kim, and Choi, modeled consumer referrals through use of a small world network. Demonstrating that Watts & Strogatz ‘ Small world network model can be adapted to interpret the initial linear relationship between firms, and consumers, and its subsequent development exhibiting small world properties. [20]A study by Lorenzo Bizzi & Ann Langley (2012). [21]

Examples

Work by Ravi Achrol and Philip Kotler identified several marketing network models. [3]

Layered network

The first model is a layered network. A layered network is a business which includes “an operational layer of cross-functional teams on the one hand and a knowledge creating layer of functional silos on the other hand, connected internally and externally through extensive data bank knowledge and transparent information flows”. [3] An example of this has been implemented by sharp electronics. [22]

Internal marketing networks

The second model proposed is that of internal marketing networks. An internal marketing network is a “firm organized to internal enterprise units that operate as semiautonomous profit centers buying from, selling to, or investing in other internal or external markets” . [3] AC-Rochester is a definitive example according to whom? ] of an internal marketing network. It is one of eight component manufacturing divisions of General Motors, structured as an internal market. It markets its products to Mitsubishi in Japan, Daewoo in Korea and Opel in Europe. [23] Internal marketing networks have many similar properties.[24]

Vertical networks

A vertical network comprised of groups of resource firms specializing in the various products, technologies, or services that constitute the inputs of a particular industry. [3]

Vertical network in marketing often represent monopolies. These would include companies such as Transpower, Kiwi Rail, and the like. These networks display preferential attachment, similar to that of Barabasi-Albert Model.

Small world networks

Watt’s and Strogatz’s used graph theory to create three models depicting water equivalent varying, connectedness, thesis Were named Small world network . A small world network Is a graph in which most nodes are not connected to other networks. These terms have been used in the past (eg Jun, Kim, Kim, & Choi). [20]

If we are to think of this in terms of a business relationship, it is not hard to see where this model becomes applicable. Consider Jun, Kim, Kim, and Choi’s example of consumer referrals. Each node represents a consumer, and the connections represent the relationship one consumer has with another. As more incentive is given for reference to the product of the probability of increasing connection increases. What starts as a regular network, quickly becomes random and complex. This same thing could be applied to a network of firms, middlemen and consumers. With every step in the chain, the value is added to the product, and the cost increases. This increases the incentive for middleman, and better deals. As deals and relationships are forged the network becomes more and more complex and integrated, creating disorder.

Hubs

‘Hubs’ or ‘connectors’ are important aspects of this issue. [25] A hub in a network is a consequence of a Power Law, where a small number of nodes or actors in a network have a disproportionately large number of links to other nodes in the network. A Power Law in a market system for instance, but there are many actors in the world, which is a small number have a huge amount of network contacts in their ‘rolodex’ and can easily facilitate communication between two separated actors. The idea that a network has a large number of links, which have a large number of links and ensure that a network has full contact and eases the complexity of this. [26]One of the first empirical observations of hubs or connectors in social sciences experimentation cam about Stanley Milgram’s Small world experiments, the first of which takes place in 1967. Of the 64 letters which made it through the stated destination, 60% of them went through the same four people, and a further experiment of a similar nature when 24 letters got through, 16 of them went through the same last person as a connection. [27] Hubs are distinctive components of network systems and their understanding of a better understanding of network function and behavior can be attained. [28]Barabási states that hubs dominate the networks of high-level networks and high-level clustering. The presence of hubs in a market can be an important aspect of new product adoption and diffusion rates, by utilizing hubs when bringing a product to market producers can generate more ‘buzz’ and reach a greater target audience with improved efficiency through the use of hubs and their large amount of connections across a network. [29]In terms of hubs acting as facilitators of diffusion, they can take many forms. One example of this is a celebrity endorsement in a marketing campaign for a product, the celebrity acts by their fame and the perception of their favorite celebrities. producer. [29] [30]The links involved with the hubs of a small number of small businesses that are clustered due to similarities. However, while the interconnectedness of a network may be much greater, it may also be important for them to keep track of each other. information flow become strained. [31]

Strong vs. Weak ties and their relative importance

The concepts of weak and strong ties in a marketing and social sciences context to the intensity of the relationships between members of a network. The strength of a tie to Professor Mark Granovettercan be analyzed by a combination of; the amount of time, the intimacy and mutual confiding, and the reciprocal services between those which the tie exists. A strong tie relationship exhibits high levels of the afore mentioned attributes and in a relationship between two parties which is a strong tie there is assumed to be mutual benefit for both parties involvement in the relationship. Strong ties are often found in highly dense groups of nodes that share many similarities and connections within the groups. Thus removing one or two strong parts in a group does not affect the information distribution through the group. [32]Weak ties refer to the relationships that are present or not. Where strong ties require a high level of commitment and other factors? Nor do they require similar interests in a network, but they do not have the same effect. They link groups or clusters together in the clusters and enable the flow of information in the cluster. The idea that removing strong ties from a network The concept of bridgesis central to this idea. A bridge is a connection which acts as the only way to get information between. Due to the nature of bridges strong links are not able to be bridges to the interconnected nature of strong ties in a community and the presence of alternate connections to facilitate lateral diffusion . Conversely weak links can be bridges because they are often the links between groups or nodes, but it is important to note that they are weak links, thus em. [32]An example of how weak can be achieved by reaching larger audiences is shown by Rapoport and Horvath’s 1961 study of a high school in Michigan. [33]857 students were asked to rank their best friends from 1 (best friend) to 8 (associate). The results of the survey showed that they were a small minority of the students, where they were seen to be more important than others. In this example, the strong links have been known to those who have had greater access to information. Through utilizing weak links available in the marketplace, it may be possible to expand or tap into different markets through utilizing a weak link and diversify.target audience or group who would find it appropriate.

Complexity

Complexity in networks is related to the concept of the elements of the A complex system is a system composed of interconnected parts that can be accessed by the system as a whole, but when viewing the individual components of the system their potential is not visible (or obvious ). A complex system is a highly structured system, which shows structure with a number of variations. It is very sensitive to initial conditions and small alterations to these can results in different situations, there are a number of pathways and evolutions which’butterfly’s wings’ are able to affect. A complex system is one that by design or function is difficult to understand and verify. There are multiple simultaneous interactions by actors and components which lead to an overall output of a system. [34]It is important in this context that it is important to know that it is important to know that it is important to know that it is important to know that it is important to consider it. It is also important to recognize the potential of a complex market, where they are also complex systems themselves. The market must be viewed as a whole to understand the sum of the parts and analyze emerging behaviors. The many aspects of complex systems mean that they are unpredictable and involve aspects of chaos and non-linearity and lead in small-world phenomena. [35]

Chaos Theory

Chaos Theory studies the behavior of dynamical systems that are highly sensitive to initial conditions. Chaos Theory Applied to marketing offers an alternative explanation for the complex, Apparently disorderly patterns of behavior over time in marketing systems are qui Observed in phenomena Such As dirty, inventories, brand shares and prices. [36] Marketing systems are identified as being nonlinear in nature because they fail to satisfy the superposition principle(outputs are not directly proportional to inputs) Even though the rules governing the behavior of the system are known, it is impossible to make accurate long-term predictions of the system. This happens even though marketing systems are fully deterministic . Traditional explanations of marketing behavior typically involves random sampling of randomly occurring or inherently stochastic processes to account for complex dynamics within marketing systems. [36]

Chaos Theory explains at least a component of disorderly market behavior in terms of deterministic feedback mechanisms reflected in the rules governing system members’ behavior and interactions. This feedback is non-linearity and occurs in two forms: (1) the reinforcing growth effect of positive feedback; and (2) the damping effect of negative feedback. Chaos theory also offers alternative explanations for the existence of various types of marketing institutions as ‘disequilibrium mechanisms’ designed to buffer or reduce the effects of complex dynamics. [36] These include inventory-holding intermediaries, financial intermediaries, insurance agencies, and ordering systems. Finally, Chaos Theory can explain and predict structural change and evolution in marketing systems. [36]

The application of chaos theory to marketing systems can lead to new ways of coping with or avoiding these chaotic patterns of behavior.

Marketing Models with Chaos Properties

Chaos is present in several popular marketing models of product diffusion, market or brand share and market evolution. [37] The transition from order to chaos can be demonstrated in this simple nonlinear equation, representing the market evolution, under plausible assumptions of interdependence of actions and / or variables:

{\ displaystyle N_ {t + 1} = rN_ {t} [(K-N_ {t}) / K]}[37]

The rate of growth, {\ displaystyle rN_ {t}}, will be exponential as entry far exceeds exit. [38] Eventually, the number of firms in the industry ({\ displaystyle N_ {t}}) approaches the capacity ({\ displaystyle K}) and growth slows. Growth becomes negative overcrowding occur, which may be reflected by, for example, price competition and competitive promotional activities. Eventually this competition will drive profit below threshold levels. The value{\ displaystyle r}The degree of non-linearity in the model and the critical determinant of the pattern of market evolution. [38] Stable equilibrium occurs at values ​​of less than 2, periodic and bifurcation patterns{\ displaystyle r} exceeding 2 and chaos occurs at values ​​of {\ displaystyle r}greater than 2.57. [36] [39]

References

  1. ^ Jump up to:m Wilkinson, I. (2001). A History of Network and Channels Thinking in Marketing in the 20th Century. Australasian Marketing Journal (AMJ), 9 (2), 23-52.
  2. Jump up^ Drucker, P (1993) Post Capitalist Society. Oxford: Butterworth.
  3. ^ Jump up to:h Achrol, RS, & Kotler, P. (1999). Marketing in the Network Economy. The Journal of Marketing, 63, 146-163.
  4. ^ Jump up to:b Gordon, AW (1999). Network effects in marketing. Marketing Research, 11 (3), 36.
  5. Jump up^ search networking,http://searchnetworking.techtarget.com/definition/network
  6. Jump up^ Leonhard Euler’s solution to the Konigsberg Bridge Problem. http://mathdl.maa.org/mathDL/46/?pa=content&sa=viewDocument&nodeId=1310&bodyId=1452
  7. Jump up^ Commons, J. (1934) Institutional Economics. New York: MacMillan.
  8. Jump up^ Schumpter, J (1939) Business Cycles. New York: McGraw-Hill.
  9. Jump up^ Coase, RH (1 January 1937). “The Nature of the Firm”. Economica . 4(16): 386-405. doi : 10.2307 / 2626876 . JSTOR  2626876 – via JSTOR.
  10. Jump up^ Macklin, T (1921) Efficient marketing for Agriculture. New York: Ferris
  11. Jump up^ Breyer, R (1924) The marketing institution. New York: McGraw-Hill.
  12. Jump up^ Alderson, Wroe; Cox, Reavis (January 1, 1948). “Towards a Theory of Marketing”. Journal of Marketing . 13 (2): 137-152. doi : 10.2307 / 1246823 . JSTOR  1246823 .
  13. Jump up^ Cox, R., Fichandler, TC, & Goodman, CS (1965). Distribution in a high-level economy. Englewood Cliffs: NJ, Prentice Hall.
  14. Jump up^ McCammon Jr., Bert C.1963. Alternative Explanations of Institutional Change and Channel Evolution. In Stephen A. Greyser ed. Toward Scientific Marketing. Chicago: American Marketing Association 477-90.
  15. Jump up^ Robicheaux, RA (1976). A General Model for Understanding Channel Member Behavior. Journal of Retailing, 52 (4), 13.
  16. Jump up^ Phillip, LW (1981). A methodological note on organizational analysis in marketing. JMR, Journal of Marketing Research (pre-1986), 18 (000004), 395.
  17. Jump up^ Anderson, JC, & Narus, JA (1984). A Model of the Distributor’s Perspective of Distributor-Manufacturer Working Relationships. The Journal of Marketing, 48 (4), 62-74.
  18. Jump up^ *Giesler, Markus (2012). “How Doppelgänger Brand Images Influence the Market Creation Process: Longitudinal Insights from the Rise of Botox Cosmetic”. Journal of Markeing . 76 (6): 55-68. doi : 10.1509 / jm.10.0406.
  19. Jump up^ Halinen, A., & Törnroos, J.-Å. (2005). Using case methods in the study of contemporary business networks. Journal of Business Research, 58 (9), 1285-1297.
  20. ^ Jump up to:b Jun, T., Kim JY, Jun Kim, B., & Choi, Y. (2006). Consumer referral in a small world network. Social Networks, 28 (3), 232-246.
  21. Jump up^ Bizzi, L., & Langley, A. (2012). Studying processes in and around networks. Industrial Marketing Management, 41 (2), 224-234.
  22. Jump up^ Nonaka, I. (2007). The knowledge-creating company. Harvard Business Review, 85 (7-8), 162-162. http://hbr.org/2007/07/the-knowledge-creating-company/ar/1
  23. Jump up^ Snow, CC, Miles, RE, & Coleman, HJ (1992). “Managing 21st century network organizations”. Organizational Dynamics, 20 (3), 5-20.
  24. Jump up^ “Network Marketing Basics Tips” . Retrieved 2017-07-05 .
  25. Jump up^ Goldenberg, Jacob; Lowengart, Oded; Shapira, Daniel (2009). “Integrating the Social Network to Diffusion Modeling and Evaluation of the Value of Hubs in the Adoption Process”. SSRN Electronic Journal . doi : 10.2139 / ssrn.1526490 .
  26. Jump up^ Bornholdt, S., Schuster, HG 2005. Handbook of Graphs and Networks: From the Genome to the Internet, Weinheim.
  27. Jump up^ Travers, J., Milgram, S (1969) An Experimental Study of the Small World Problem. Sociometry, 32, 425-443.
  28. Jump up^ Barabasi, A. 2002. Linked: The New Science of Networks, United States, Perseus Publishing.
  29. ^ Jump up to:b Delre SA, Jager, W., Bijmolt, HAT & Janssen, M. 2010. Will it spread or not? The effects of social influence and network topology on innovation diffusion. Journal of Product Innovation Management, 27, 267-282.
  30. Jump up^ Roll, M. 2011. Branding celebrities, brand endorsements, brand leadership. Available :(http://www.venturerepublic.com/resources/branding_celebrities_brand_endorsements_brand_leadership.asp.
  31. Jump up^ Gladwell, M. 2000. The Tipping Point: How Little Things Can Make A Big Difference. United States of America, Little Brown.
  32. ^ Jump up to:b Granovetter, MS (1973). The Strength of Weak Ties. American Journal of Sociology, 78, 1360-1380.
  33. Jump up^ Rapoport, A., Horvath, WJ 1961. A Study of a Large Sociogram. Behavioral Science, 6, 279-291.
  34. Jump up^ Mathews, KM, White, MC & Long, RG (1999). Why Study the Complexity Sciences in the Social Sciences? Human Relations, 52, 439-462.
  35. Jump up^ Uzzi, B., Amaral, LA & Reed-Tsochas, F. (2007). Small-world networks and management science research: a review. European Management Review, 4, 77 – 91.
  36. ^ Jump up to:e Hibbert, B. Wilkinson, IF (1994). Chaos Theory and the Dynamics of Marketing Systems. Journal of the Academy of Marketing Science, 22 (3), 218-233.
  37. ^ Jump up to:b Lambkin, M., Day, GS (1989). Evolutionary Processes in Competitive Markets: Beyond the Product Life Cycle. Journal of Marketing, 53 (3), 4-20.
  38. ^ Jump up to:b Doherty, N., Delener, N. (2001). Chaos Theory: Marketing & Management Implications. Journal of Marketing Theory and Practice, 9 (4), 66-75.
  39. Jump up^ Gleick, J. 2008. Chaos: Making a New Science, New York, USA, Penguin.