Public relations as a complex decision-based practice

2019 ◽  
Vol 8 (3) ◽  
pp. 265-279
Author(s):  
Anke Osswald

This article considers public relations through the prism of decision-making. Decisions can be regarded as a way of dealing with complexity. In the following, two approaches to decisions and complexity are discussed. The first is an actor-based prescriptive approach, which focuses on decision-making as a means of managing environmental complexity. There are different tools and techniques that support public relations managers in finding adequate responses. The second is a descriptive approach, which is more interested in the ways in which such tools and techniques contribute to the complex decision process itself. In accordance with Niklas Luhmann’s systems theory, public relations decisions are regarded as a specific form of communication that (a) emphasizes the selectivity of the process by specifying particular public relations options or choices, (b) attributes this selection to a ‘decision-maker’ (e.g. a public relations manager) while simultaneously presuming strategic intent with respect to public perception, and (c) engages the past and future in a specific way. A decision-based approach that builds on communication may thus contribute to a more detailed understanding of public relations practice. Such an approach raises, among others, questions concerning strategic public relations options or the participation of digital entities as ‘decision-makers’. With its focus on decisions as communications, it furthermore links the field of public relations research to schools of thought such as CCO (communicative constitution of organizations) and strategy as practice.

Author(s):  
NINA RADUHA

Natov koncept strateških komunikacij, ki je osrednja tema prispevka, je v Sloveniji in Slovenski vojski premalo poznan in uporabljen pojem, še manj je znana njegova vsebina. Pogosto je napačno razumljen in enačen s strateškimi odnosi z javnostmi. Ni direktivno sprejet in uveden v procese odločanja in načrtovanja, vendar v ospredje vedno bolj prihaja zavedanje, da je nujen, in sicer z vsemi svojimi zmogljivostmi in na vseh ravneh delovanja, kot eden ključnih načinov celovitega pristopa k učinkovitemu reševanju kriz v svetu in vedno bolj tudi v domačem okolju. Cilj pisanja je na diplomatski in vojaški ter taktični in strateški ravni spodbuditi zavedanje o nujnosti, pomembnosti in uporabnosti koncepta strateških komunikacij v sodobnem informacijskem času. S predstavitvijo teoretičnega okvira, vsebine in resničnih implikacij koncepta strateških komunikacij v praksi drugih držav, zavezniških in nasprotnikovih sil želimo s prispevkom poiskati zanimanje in pot do stvarne uvedbe in uporabe koncepta v slovenskem okolju. Analitični pregled stanja v Slovenski vojski in širše pokaže, da se sistem še ne zaveda nujnosti uvajanja koncepta v uporabo, čeprav bi se moral. V sklepu so zato zapisani izhodišča in podlaga za gradnjo obravnavanega koncepta v našem okolju, ki bodo predvsem v SV in na Ministrstvu za obrambo, pa tudi širše v slovenskem okolju, temelj za razpravo o oblikovanju nujnih odgovorov na izzive sodobnega varnostnega okolja. In Slovenia and the Slovenian Armed Forces, NATO's Strategic Communication's Concept, which is the main topic of this article, is a little known and used term, while its contents is even less known. It is often misunderstood and compared to strategic public relations. It has not been regulated and incorporated into the decision-making and planning processes. However, the awareness of its paramount importance is coming more and more to the fore. It is needed with all its capabilities and at all levels of operation as one of the key ways of adopting a comprehensive approach to an effective resolution of crisis worldwide and, more and more, in Slovenia. The aim of this article is to encourage the awareness on the urgency, importance and usefulness of the concept of strategic communication in the modern information era. By presenting the theoretical framework, contents and actual implications of the strategic communications concept in the practice of other nations, allied and adversary forces, we aim at ascertaining interest and way to actually implement and apply the concept in Slovenia. According to the analytical overview of the situation in the Slovenian Armed Forces and beyond, the system is not yet aware of the urgency of implementing the concept, although it should be. The conclusion thus includes the platform and foundation for the formulation of the discussed concept in Slovenian environment, which will serve as the basis for the Slovenian Armed Forces, the Ministry of Defence and other institutions to discuss the formulation of urgent responses to the challenges posed by the modern security environment


2021 ◽  
Vol 10 (6) ◽  
pp. 403
Author(s):  
Jiamin Liu ◽  
Yueshi Li ◽  
Bin Xiao ◽  
Jizong Jiao

The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods.


2021 ◽  
Vol 1 ◽  
pp. 2701-2710
Author(s):  
Julie Krogh Agergaard ◽  
Kristoffer Vandrup Sigsgaard ◽  
Niels Henrik Mortensen ◽  
Jingrui Ge ◽  
Kasper Barslund Hansen ◽  
...  

AbstractMaintenance decision making is an important part of managing the costs, effectiveness and risk of maintenance. One way to improve maintenance efficiency without affecting the risk picture is to group maintenance jobs. Literature includes many examples of algorithms for the grouping of maintenance activities. However, the data is not always available, and with increasing plant complexity comes increasingly complex decision requirements, making it difficult to leave the decision making up to algorithms.This paper suggests a framework for the standardisation of maintenance data as an aid for maintenance experts to make decisions on maintenance grouping. The standardisation improves the basis for decisions, giving an overview of true variance within the available data. The goal of the framework is to make it simpler to apply tacit knowledge and make right decisions.Applying the framework in a case study showed that groups can be identified and reconfigured and potential savings easily estimated when maintenance jobs are standardised. The case study enabled an estimated 7%-9% saved on the number of hours spent on the investigated jobs.


2021 ◽  
Vol 35 (2) ◽  
Author(s):  
Nicolas Bougie ◽  
Ryutaro Ichise

AbstractDeep reinforcement learning methods have achieved significant successes in complex decision-making problems. In fact, they traditionally rely on well-designed extrinsic rewards, which limits their applicability to many real-world tasks where rewards are naturally sparse. While cloning behaviors provided by an expert is a promising approach to the exploration problem, learning from a fixed set of demonstrations may be impracticable due to lack of state coverage or distribution mismatch—when the learner’s goal deviates from the demonstrated behaviors. Besides, we are interested in learning how to reach a wide range of goals from the same set of demonstrations. In this work we propose a novel goal-conditioned method that leverages very small sets of goal-driven demonstrations to massively accelerate the learning process. Crucially, we introduce the concept of active goal-driven demonstrations to query the demonstrator only in hard-to-learn and uncertain regions of the state space. We further present a strategy for prioritizing sampling of goals where the disagreement between the expert and the policy is maximized. We evaluate our method on a variety of benchmark environments from the Mujoco domain. Experimental results show that our method outperforms prior imitation learning approaches in most of the tasks in terms of exploration efficiency and average scores.


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