We analyze intermediation business processes that enable companies to use multiple
distribution channels for expanding their market horizon of potential customers that are
interested in purchasing their products and/or services. These distribution channels are
represented by sequences of intermediation transactions supported by usually
self-interested middle-agents that enable the connection of the providers with the end
costumers. We propose a new formal model of network-structured intermediation business
processes represented as Directed-Acyclic-Graphs. Using this model we obtained sound
theoretical results of collectively profitable intermediation transactions. This paves the
way for further proposal of optimal pricing strategies of the participating agents in
semi-competitive environments.
AhujaR.K., MagnantiT.L. and
OrlinJ.B.,
Network Flows: Theory, Algorithms, and Applications,
Pearson, 1993.
2.
BădicăC., BudimacZ., BurkhardH.-D. and
IvanovićM.,
Software agents: Languages, tools, platforms,
Computer Science and Information Systems8(2)(2011),
255–298. doi: 10.2298/CSIS110214013B
3.
BădicăA. and BădicăC.,
FSP and FLTL framework for specification and verification of
middle-agents, Applied Mathematics and Computer Science21(1) (2011),
9–25. doi: 10.2478/v10006-011-0001-6
4.
BădicăC., IlieS.,
MuscarA., BădicăA., SanduL., SboraR., GanzhaM. and PaprzyckiM.,
Distributed agent-based online auction system,
Computing and Informatics33(3) (2014),
518–552. http://www.cai.sk/ojs/index.php/cai/article/view/2216
5.
BădicăA., BădicăC., IvanovićM. and BuligiuI.,
Collective Profitability and Welfare in Selling-Buying Intermediation
Processes. Computational Collective Intelligence. ICCCI Part II.
Lecture Notes in Computer Science, 9876,
Springer, Cham,
2016, pp. 14–24. doi: 10.1007/978-3-319-45246-32
6.
BădicăA., BădicăC., IvanovićM. and LogofătuD.,
Collective Profitability of DAG-Based Selling-Buying Intermediation
Processes. Intelligent Distributed Computing XII. 12th International Symposium on
Intelligent Distributed Computing, IDC 2018. Studies in
Computational Intelligence, 798, Springer,
Cham, 2018, pp.
414–424. doi: 10.1007/978-3-319-99626-4_3
7.
BoujelbenM.K.,
GicquelC. and
MinouxM., A
distribution network design problem in the automotive industry: MIP formulation and
heuristics. Computers and Operations Research, 52, Part
A, Elsevier, 2014, pp.
16–28. doi: 10.1016/j.cor.2014.07.007
8.
CookK.S. and EmersonR.M.,
Power, equity and commitment in exchange networks,
American Sociological Association43 (1978), 721–739, doi:
10.2307/2094546
9.
DeckerK., SycaraK. and WilliamsonM.,
Middle-Agents for the Internet, Proceedings of
the 15th International Joint Conference on Artificial Intelligence (IJCAI’97),
Nagoya, Aichi, Japan, Vol. 1, pp.
1997, 578–583.
10.
DignumV., TranierJ. and DignumF.,
Simulation of intermediation using rich cognitive agents,
Simulation Modelling Practice and Theory38(10) (2010),
1526–1536. Elsevier.
10.1016/j.simpat.2010.05.011
11.
DinesL.L.,
Systems of linear inequalities, Annals of
Mathematics, Second Series20(3) (1919),
191–199. Mathematics Department,
Princeton, doi: 10.2307/1967869
12.
(Gyula)
FarkasJ., Über die
theorie der einfachen ungleichungen, Journal für die Reine und
Angewandte Mathematik124(124) (1902),
1–27. doi: 10.1515/crll.1902.124.1
13.
GaleottiA. and CondorelliD.,
Strategic Models of Intermediation Networks, In:
BramoulléY., GaleottiA. and RogersB., (Eds.)
The Oxford Handbook of the Economics of Networks,
Oxford University Press Chater 27, 2016,
pp. 733–753. doi: 10.1093/oxfordhb/9780199948277.013.16
14.
CoriaJ.A.G., Castellanos-GarzónJ.A.
and CorchadoJ.M.,
Intelligent business processes composition based on multi-agent
systems, Expert Systems with Applications41(4) (2014),
1189–1205. Part 1.
Elsevier. doi: 10.1016/j.eswa.2013.08.003
15.
HolzhauserM.,
KrumkeS.O. and
ThielenC.,
Budget-constrained minimum cost flows, Journal of
Combinatorial Optimization31(4) (2016),
1720–1745. Springer. doi:
10.1007/s10878-015-9865-y
16.
JacksonM.O.,
Social and Economic Networks, Princeton
University Press, 2010.
17.
JehleG.A. and RenyP.J.,
Advanced Microeconomic Theory, Third
Edition. Pearson Education Limited,
2011.
18.
JenningsN.R. and
WooldridgeM.,
Applications of Intelligent Agents, In: JenningsN.R. and
WooldridgeM.J., (eds.):
Agent Technology, Springer Berlin
Heidelberg, 1998, pp. 3–28.
doi: http://dl.acm.org/citation.cfm?id=277789.277799
19.
KanterR.M.,
Collaborative advantage: The art of alliances,
Harvard Business Review72(4) (1994),
96–108.
20.
KerinR.A., HartleyS.W. and
RudeliusW.,
Marketing (12th Edition).
McGraw-Hill Education,
2014.
21.
KrantonR.E. and
MinehartD.F.,
A theory of buyer-seller networks, The American
Economic Review91(3) (2001),
485–508, American Economic
Association, doi: 10.1257/aer.91.3.485
LaudonK.C. and TraverC.G.,
E-Commerce 2014 (10th Edition).
Pearson, 2010.
24.
LeonF. and BădicăC., An
optimization web service for a freight brokering system, Service
Science9(4) (2017),
324–337. Informs. doi: 10.1287/serv.2017.0191
25.
ManeaM.,
Intermediation and resale in networks, Journal of
Political Economy126(3) (2018),
1250–1301. The University of Chicago
Press. doi: 10.1086/697205
26.
NagurneyA. and KeK.,
Financial networks with intermediation: Risk management with variable
weights, European Journal of Operational Research172(1) (2006),
40–63. Elsevier,
10.1016/j.ejor.2004.09.035
27.
NaultB.R. and DexterA.S.,
Agent-intermediated electronic markets in international freight
transportation, Decision Support Systems41(4) (2006),
787–802. Elsevier,
10.1016/j.dss.2004.10.008
28.
NguyenN.T.,
Inconsistency of knowledge and collective intelligence,
Cybernetics and Systems39(6) (2008),
542–562. Taylor &
Francis, doi: 10.1080/01969720802188268
29.
PatilH.,
Buyer-seller networks with demand shocks and
intermediation, Review of Economic Design15(2) (2011),
121–145, Springer, doi:
10.1007/s10058-009-0097-4
30.
PosladS.,
Specifying protocols for multi-agent systems interaction,
ACM Transactions on on Autonomous and Adaptive Systems2(4) (2007), Article 15,
ACM. doi: 10.1145/1293731.1293735
31.
SiedlarekJ.-P.,
Intermediation in Networks, Federal
Reserve Bank of Cleveland, working paper no.
15–18, 2015.
32.
SpulberD.F.,
Market Microstructure: Intermediaries and the Theory of the
Firm, Cambridge University Press,
1999.
