The research aims to identify the actors involved in the technology transfer system in Agriculture technopark and analyze the potential of alliances or conflicts to achieve the goals. The analysis was carried out through a survey methodology. Data were obtained through interviews using questionnaires and focus group discussions on a group of informants selected according to specific criteria. MACTOR analysis is used to analyze the relationship between actors and actors-goals in technology transfer in ATP. The analysis results show that the actors playing a dominant role are the local government, the ATP manager, partner farmer groups, and researchers/extension workers. The four chief actors have the potential for an alliance to achieve system goals. Otherwise, actors such as universities, startups, and suppliers have the opportunity to cause several dreams to become divergent due to differences in interests. To conclude, the involvement of actors in the ATP technology transfer system is very much dominated by several actors in the driving subsystem, whereas the support subsystem is passive. The balance of the power of the actors will be obtained if the driving subsystem reduces its dominance by establishing mutually beneficial partnerships with actors in the supporting subsystem.

1.
IAARD
.
General Guidelines for the establishment and Development of Agriculture Science and Technology Park (TSTP) [Internet]. Edisi 2016
.
Suryana
A
,
Yufdy
MP
,
Rana
G.
, editors
.
Jakarta: Badan Litbang Pertanian
;
2016
.
78
p. Available from http://www.litbang.pertanian.go.id/download/414/file/Pedoman-Umum-TSP-dan-TTP.pdf
2.
Kharabsheh
R.
Critical Success Factors of Technology Parks in Australia
.
Int J Econ Financ [Internet].
2012
;
4
(
7
):
57
66
. Available from: http://www.ccsenet.org/journal/index.php/ijef/article/view/18320
3.
Grimble
R
,
Wellard
K.
Stakeholder methodologies in natural resource management: A review of principles, contexts, experiences and opportunities
.
Agric Syst.
1997
;
55
(
2
):
173
93
.
4.
Franco-Trigo
L
,
Marqués-Sánchez
P
,
Tudball
J
,
Benrimoj
SI
,
Martínez-Martínez
F
,
Sabater-Hernández
D.
Collaborative Health Service Planning: A Stakeholder Analysis With Social Network Analysis To Develop A Community Pharmacy Service
.
Res Soc Adm Pharm [Internet].
2020
;
16
(
2
):
216
29
. Available from: https://doi.org/10.1016/j.sapharm.2019.05.008
5.
Alsos
GA
,
Hytti
U
,
Ljunggren
E.
Stakeholder Theory Approach To Technology Incubators.
Int J. Entrep Behav Res.
2011
;
17
(
6
):
607
25
.
6.
Bendahan
S
,
Camponovo
G
,
Pigneur
Y
.
Multi-Issue Actor Analysis: Tools And Models For Assessing Technology Environments
.
J Decis Syst.
2004
;
13
(
2
):
223
53
.
7.
Rees
GH
,
MacDonell
S.
Data Gathering For Actor Analyses: A Research Note On The Collection And Aggregation Of Individual Respondent Data For MACTOR
.
Futur Stud Res J Trends Strateg.
2017
;
9
(
1
):
115
37
.
8.
Mangifera
L
,
Isa
M.
Development Model Of Creative Industries: An Application Of MACTOR
.
KnE Soc Sci.
2019
;
3
(
14
):
360
.
9.
Elmsalmi
M
,
Hachicha
W.
Risk Mitigation Strategies According To The Supply Actors’ Objectives Through MACTOR Method.
2014 Int Conf Adv Logist Transp ICALT
2014. 2014
;
362
7
.
10.
Godet
M.
Actors’ moves and strategies: The MACTOR Method. An Air Transport Case Study. Futures
.
1991
;
23
(
6
):
605
22
.
11.
Boumaour
A
,
Grimes
S
,
Brigand
L
,
Larid
M.
Integration Process And Stakeholders’ Interactions Analysis Around A Protection Project: Case Of The National Park Of Gouraya, Algeria (South-Western Mediterranean)
.
Ocean Coast Manag [Internet].
2018
;
153
(August 2017):
215
30
. Available from: https://doi.org/10.1016/j.ocecoaman.2017.12.031
12.
Fetoui
M
,
Frija
A
,
Dhehibi
B
,
Sghaier
M
,
Sghaier
M.
Prospects For Stakeholder Cooperation In Effective Implementation Of Enhanced Rangeland Restoration Techniques In Southern Tunisia
.
Rangel Ecol Manag.
2020
;
This content is only available via PDF.
You do not currently have access to this content.