scholarly journals Big Data Contribution in Desktop and Mobile Devices Comparison, Regarding Airlines’ Digital Brand Name Effect

2021 ◽  
Vol 5 (4) ◽  
pp. 48
Author(s):  
Damianos P. Sakas ◽  
Nikolaos Th. Giannakopoulos
Keyword(s):  
Big Data ◽  
Mobile Devices ◽  
Cognitive Mapping ◽  
Agent Based Modeling ◽  
Marketing Strategies ◽  
Digital Marketing ◽  
Brand Name ◽  
Agent Based ◽  
Exploratory Model ◽  
Observation Period

Rising demand for optimized digital marketing strategies has led firms in a hunt to harvest every possible aspect indicating users’ experience and preference. People visit, regularly through the day, numerous websites using both desktop and mobile devices. For businesses to acknowledge device’s usage rates is extremely important. Thus, this research is focused on analyzing each device’s usage and their effect on airline firms’ digital brand name. In the first phase of the research, we gathered web data from 10 airline firms during an observation period of 180 days. We then proceeded in developing an exploratory model using Fuzzy Cognitive Mapping, as well as a predictive and simulation model using Agent-Based Modeling. We inferred that various factors of airlines’ digital brand name are affected by both desktop and mobile usage, with mobile usage having a slightly bigger impact on most of them, with gradually rising values. Desktop device usage also appeared to be quite significant, especially in traffic coming from referral sources. The paper’s contribution has been to provide a handful of time-accurate insights for marketeers, regarding airlines’ digital marketing strategies.

scholarly journals Harvesting Crowdsourcing Platforms’ Traffic in Favour of Air Forwarders’ Brand Name and Sustainability

2021 ◽  
Vol 13 (15) ◽  
pp. 8222
Author(s):  
Damianos P. Sakas ◽  
Nikolaos Th. Giannakopoulos
Keyword(s):  
Data Analytics ◽  
Cognitive Mapping ◽  
Brand Name ◽  
Web Data ◽  
Factors Affecting ◽  
Agent Based ◽  
Data Prediction ◽  
Last Stage ◽  
Prediction And Simulation ◽  
Exploratory Model

In the modern digitalised era, the total number of businesses and organisations utilising crowdsourcing services has risen, leading to an increase of their website traffic. In this way, there is plenty of space for marketers and strategists to capitalise big data from both their own and the crowdsourcer’s websites. This can lead to a comprehension of factors affecting their brand name, sustainability (gross profit) and consequently visitor influence. The first of the three staged contexts, based on web data, includes the retrieval of web data analytics and metrics from five air forwarding and five crowdsourcing websites in 210 observation days. At stage two, we deployed a diagnostic-exploratory model, through Fuzzy Cognitive Mapping (FCM), and in the last stage, an Agent-Based Model is deployed for data prediction and simulation. We concluded that crowdsourcing referral traffic increases air forwarders’ top 3 keywords volume, and decreases social traffic and total keywords volume, which then boosts their global web rank and gross profit. The exact opposite results occur with crowdsourcing search traffic. To sum up, the contribution of this paper is to offer realistic and well-informed insights to marketers about SEO and SEM strategies for brand name and profit enhancement, based on harvesting crowdsourcing platform traffic.

scholarly journals The Effects of Cryptocurrency Trading Websites on Airlines’ Advertisement Campaigns

2021 ◽  
Vol 16 (7) ◽  
pp. 3099-3119
Author(s):  
Damianos P. Sakas ◽  
Nikolaos T. Giannakopoulos ◽  
Dimitrios P. Reklitis ◽  
Thomas K. Dasaklis
Keyword(s):  
Statistical Analysis ◽  
Cognitive Mapping ◽  
Positive Impact ◽  
Marketing Strategies ◽  
Digital Marketing ◽  
Stage Model ◽  
Web Analytics ◽  
Factors Affecting ◽  
Agent Based ◽  
Agent Based Modelling

In future years, airline companies will be leaning more and more towards cryptocurrencies to implement their digital marketing strategies as leaders seek to gain an understanding of the factors affecting airlines’ visibility parameters. Cryptocurrency investment websites are currently experiencing rising demand, making them an appropriate site for paid advertisements. The above factors suggest the need for airlines to harvest cryptocurrency investment and platform users in their favour. To this end, it can be beneficial for airlines’ web promotions to link certain web analytics metrics to cryptocurrency trading site metrics. For research purposes, web analytics data were monitored and gathered for 2 consecutive years from 10 globally leading cryptocurrency trading companies and 10 airline websites. A three-stage model was adopted by the authors. In the first stage, statistical analysis was implemented using cryptocurrency and airline metrics, followed by fuzzy cognitive mapping and agent-based modelling stages. The findings of the study indicate that engagement with cryptocurrency trading websites has a positive impact on airline websites’ global ranking and visibility parameters. The outcomes of this research provide noteworthy digital marketing strategies which can be addressed by airline companies to increase their website visitors and optimise visibility parameters with the assistance of cryptocurrency trading websites.

scholarly journals The Impact of Organic Traffic of Crowdsourcing Platforms on Airlines’ Website Traffic and User Engagement

2021 ◽  
Vol 13 (16) ◽  
pp. 8850
Author(s):  
Damianos P. Sakas ◽  
Dimitrios P. Reklitis
Keyword(s):  
Cognitive Mapping ◽  
Marketing Strategies ◽  
Digital Marketing ◽  
Diagnostic Model ◽  
User Engagement ◽  
Factors Affecting ◽  
Agent Based ◽  
Second Stage ◽  
Micro Level ◽  
The Impact

With airline companies increasingly relying on crowdsourcing websites to deploy their digital marketing strategies, marketeers and strategists seek to acquire an understanding of the factors affecting airlines’ organic traffic and user engagement. Such an understanding is acquired through the consideration of variables that influence a company’s organic traffic and user engagement and their correlation to each other. A three-stage data-driven analysis is used to examine the correlation between the foregoing variables and to consider strategies that can be implemented to optimize organic traffic and user engagement. The first section gathers data from five airline companies’ websites and five crowdsourcing websites over an interval of 180 days. The second stage creates an exploratory diagnostic model, through Fuzzy Cognitive Mapping, to visually illustrate the cause-and-effect correlations between the examined metrics. Finally, a predictive micro-level agent-based model simulates optimization strategies that can be used to improve organic traffic and user engagement. The results of this study, reveal that crowdsourcing organic traffic increases airline websites’ user engagement through paid campaigns, while a limited correlation was found to exist between the average duration of a user to organic traffic. The results of this study provide tangible digital marketing strategies which can be used by airline companies to improve the influence of their digital marketing strategies on their users.

scholarly journals Agent-based modeling and life cycle dynamics of COVID-19-related online collective actions

2021 ◽  
Author(s):  
Gang Zhang ◽  
Hao Li ◽  
Rong He ◽  
Peng Lu
Keyword(s):  
Big Data ◽  
Life Cycle ◽  
Evolutionary Dynamics ◽  
Life Cycles ◽  
Agent Based Modeling ◽  
Macro Level ◽  
Collective Actions ◽  
Agent Based ◽  
Individual Behaviors ◽  
Micro Level

AbstractThe outbreak of COVID-19 has greatly threatened global public health and produced social problems, which includes relative online collective actions. Based on the life cycle law, focusing on the life cycle process of COVID-19 online collective actions, we carried out both macro-level analysis (big data mining) and micro-level behaviors (Agent-Based Modeling) on pandemic-related online collective actions. We collected 138 related online events with macro-level big data characteristics, and used Agent-Based Modeling to capture micro-level individual behaviors of netizens. We set two kinds of movable agents, Hots (events) and Netizens (individuals), which behave smartly and autonomously. Based on multiple simulations and parametric traversal, we obtained the optimal parameter solution. Under the optimal solutions, we repeated simulations by ten times, and took the mean values as robust outcomes. Simulation outcomes well match the real big data of life cycle trends, and validity and robustness can be achieved. According to multiple criteria (spans, peaks, ratios, and distributions), the fitness between simulations and real big data has been substantially supported. Therefore, our Agent-Based Modeling well grasps the micro-level mechanisms of real-world individuals (netizens), based on which we can predict individual behaviors of netizens and big data trends of specific online events. Based on our model, it is feasible to model, calculate, and even predict evolutionary dynamics and life cycles trends of online collective actions. It facilitates public administrations and social governance.

scholarly journals Big data-drive agent-based modeling of online polarized opinions

2021 ◽  
Author(s):  
Peng Lu ◽  
Zhuo Zhang ◽  
Mengdi Li
Keyword(s):  
Big Data ◽  
Life Cycle ◽  
Evolutionary Dynamics ◽  
Life Cycles ◽  
Agent Based Modeling ◽  
Mobile Internet ◽  
Real Case ◽  
Agent Based ◽  
Individual Behaviors ◽  
Life Cycle Process

AbstractUnder the mobile internet and big data era, more and more people are discussing and interacting online with each other. The forming process and evolutionary dynamics of public opinions online have been heavily investigated. Using agent-based modeling, we expand the Ising model to explore how individuals behave and the evolutionary mechanism of the life cycles. The big data platform of Douban.com is selected as the data source, and the online case “NeiYuanWaiFang” is applied as the real target, for our modeling and simulations to match. We run 10,000 simulations to find possible optimal solutions, and we run 10,000 times again to check the robustness and adaptability. The optimal solution simulations can reflect the whole life cycle process. In terms of different levels and indicators, the fitting or matching degrees achieve the highest levels. At the micro-level, the distributions of individual behaviors under real case and simulations are similar to each other, and they all follow normal distributions; at the middle-level, both discrete and continuous distributions of supportive and oppositive online comments are matched between real case and simulations; at the macro-level, the life cycle process (outbreak, rising, peak, and vanish) and durations can be well matched. Therefore, our model has properly seized the core mechanism of individual behaviors, and precisely simulated the evolutionary dynamics of online cases in reality.

scholarly journals The Contribution of Social Simulation in the Advancement of Marketing Issues and Challenges

2013 ◽  
Vol 5 (1) ◽  
pp. 19-31
Author(s):  
Mario Gonzalez-Fuentes
Keyword(s):  
State Of The Art ◽  
Holistic Approach ◽  
Agent Based Modeling ◽  
Marketing Strategies ◽  
Social Simulation ◽  
Future Research ◽  
Agent Based ◽  
Research Opportunities ◽  
Computer Scientists ◽  
The One

For some years now, marketers have been praising for a more holistic approach of a company’s marketing efforts across all areas. However, traditional models show serious limitations to address the complexities of managing all of a company’s touch points with a customer. Agent-based modeling (ABM) has opened the door to explore the unfolding behaviors and outputs of an increasingly connected and interactive marketplace. The contribution of this paper is twofold. On the one hand, it provides researchers with a state-of-the-art repository for this strand of research. This facilitates the identification of relevant gaps in the literature and future research avenues. Second, it contributes to assess the way ABM has improved our understanding of the dynamics of markets and its participants when marketing strategies are implemented. Both goals aim at showing the various ways that social simulation has expanded our understanding of marketing and the future research opportunities for both, marketing and computer scientists.

Sign in / Sign up

Export Citation Format

Share Document