Identifying the Antecedents of Children's Market Using Neural Network

2020 ◽  
pp. 1109-1136
Author(s):  
Jony Haryanto ◽  
Luiz Moutinho
Keyword(s):  
Neural Network ◽  
Autobiographical Memory ◽  
Network Topology ◽  
Brand Loyalty ◽  
Methodological Approach ◽  
Age Group ◽  
Research Subjects ◽  
Emotional Bonding ◽  
Brand Relationship ◽  
Fuzzy Logic Analysis

Chapter 5 explores the main features contributing towards the formation of living brand among children within the age 10 to 12-year-old by using a fuzzy logic analysis. From this methodological approach, several interesting insights emerge with regard to children's consumer behaviour, especially the factors of future anticipation, ritual, and autobiographical memory in the priming of the development of a living brand. In this chapter, we are going to expand on the discussion by identifying the antecedents of a successful product using Indonesian market segment from the same age group as the research subjects in Chapter 6. Some of the important elements for success in the children's segment that we identify here include brand personality, brand trust, and brand salience, particularly on how each of them affect brand relationship. When combined with autobiographical memory and buying habituation, this emotional bonding results in brand loyalty. Finally, we utilised a neural network topology in order to fully understand the antecedents of brand loyalty construction within the children's market.

Identifying the Antecedents of Children's Market Using Neural Network

2016 ◽  
pp. 128-163
Keyword(s):  
Neural Network ◽  
Autobiographical Memory ◽  
Network Topology ◽  
Brand Loyalty ◽  
Methodological Approach ◽  
Age Group ◽  
Research Subjects ◽  
Emotional Bonding ◽  
Brand Relationship ◽  
Fuzzy Logic Analysis

Chapter 5 explores the main features contributing towards the formation of living brand among children within the age 10 to 12-year-old by using a fuzzy logic analysis. From this methodological approach, several interesting insights emerge with regard to children's consumer behaviour, especially the factors of future anticipation, ritual, and autobiographical memory in the priming of the development of a living brand. In this chapter, we are going to expand on the discussion by identifying the antecedents of a successful product using Indonesian market segment from the same age group as the research subjects in Chapter 6. Some of the important elements for success in the children's segment that we identify here include brand personality, brand trust, and brand salience, particularly on how each of them affect brand relationship. When combined with autobiographical memory and buying habituation, this emotional bonding results in brand loyalty. Finally, we utilised a neural network topology in order to fully understand the antecedents of brand loyalty construction within the children's market.

A Better Understanding of Children's Market

2016 ◽  
pp. 103-127
Keyword(s):  
Fuzzy Logic ◽  
Autobiographical Memory ◽  
Old Age ◽  
Brand Loyalty ◽  
Brand Personality ◽  
Age Group ◽  
Brand Trust ◽  
Brand Relationship

Back in Chapter 4, we propose a model which attempts to encapsulate the antecedents of a brand relationship and subsequently its influence towards brand loyalty. The findings suggest that brand personality, brand trust, and brand salience are important antecedents to create a brand relationship in the children's market. Meanwhile, brand loyalty was identified as the consequence of a brand relationship, autobiographical memory, and habituation. In this chapter, we are going to expand this discussion by measuring variables concerning future anticipation, ritual, autobiographical memory, and living brand using fuzzy logic on children within the 10-12 years old age group who are assumed to be mature enough to understand and reply to simple direct questions. Ultimately, we would like to see whether the two constructs of future anticipation and ritual are (among) the antecedents of a living brand.

Creating Sustainable Product

2016 ◽  
pp. 164-194
Keyword(s):  
Network Topology ◽  
Brand Loyalty ◽  
Success Factors ◽  
Principal Component ◽  
Ml Estimation ◽  
Latent Constructs ◽  
Emotional Bonding ◽  
Brand Relationship ◽  
Confirmatory Factor ◽  
Sustainable Product

In Chapter 6, we have identified the antecedents of a successful product using Indonesian market segment from children the age of 10 to 12-year-old. The important elements that we identify in this chapter include brand personality, brand trust, and brand salience, especially on how each of them affects brand relationship. When combined with autobiographical memory and buying habituation, this emotional bonding results in brand loyalty. We then used neural network topology to fully comprehend the antecedents of brand loyalty within the children's market. To further elaborate on the success factors to support product longevity, we are going to replicate the conceptual framework from Chapter 7, but because of the strong and dominant latent constructs present in the model, we use a statistical equation modelling approach in this chapter. We also conduct exploratory principal component analysis (varimax rotation) and reliability analysis, followed by a confirmatory factor analysis (CFA) by utilising LISREL 8.73 with maximum-likelihood (ML) estimation on the scales as developed by Joreskog and Sorbom (1993).

Neural network approach to understanding the children’s market

2015 ◽  
Vol 49 (3/4) ◽  
pp. 372-397 ◽  
Author(s):  
Jony Oktavian Haryanto ◽  
Manuela Silva ◽  
Luiz Moutinho
Keyword(s):  
Neural Network ◽  
Autobiographical Memory ◽  
Brand Loyalty ◽  
Age Groups ◽  
Future Research ◽  
Future Market ◽  
Neural Network Approach ◽  
Developed Country ◽  
Content Type ◽  
Market Driving

Purpose – This study aims to explore the main features contributing towards the formation of brand loyalty among children, using a neural network topology. Design/methodology/approach – The paper used an exploratory study using a semi-structured interviewed with children, psychologist and head of the school. This paper uses survey to collect data and analysed using artificial neural networks (ANNs). Findings – Several interesting insights emerge in respect of children’s consumer behavior and, in particular, the factors of emotional authenticity, brand partnerships, brand relationship, brand salience and brand personality in the priming of children’s brand loyalty emerge as important factors. Research limitations/implications – This research uses data from Indonesia which is considered as a developing country. Further research is required in the developed country context, as this may present different perspectives. Furthermore, the sample in this study consists of children aged between 10 and 12 years, but there are many age groups into which children can be divided, e.g. below 3 years; 3-5 years; 6-8 years; 9-12 years and even 13-15 years. Hence, future research needs to include these different groups of children to gain a more complete picture of the children’s market. Practical implications – A children’s market-driving strategy really should be related with the “grass roots” needs of the segment. Hence, marketers ought to spend two or three days in the company of children and continually update themselves in respect of what is happening in those children’s rapidly changing world. Additionally, marketers need to relate all their marketing activities to the building of autobiographical memory. All events, promotions and other marketing strategies should be integrated to ensure that autobiographical memory really underpins a future market as the children of the present become adults of the future. Originality/value – The study contributes to the existing literature and appreciation of the various factors and the inter-relationships between them that have relevance for product longevity in the children’s market.

Is Brand Loyalty Really Present in the Children's Market?

2016 ◽  
pp. 69-102
Keyword(s):  
Autobiographical Memory ◽  
Brand Loyalty ◽  
Adam Smith ◽  
Market Performance ◽  
Consumer Perception ◽  
Reference Groups ◽  
Brand Relationship ◽  
Key Concepts ◽  
The Future

In Chapters 2 and 3, we have discussed about consumer perception on future anticipation to understand the trends for customer's potential needs and wants in the future by incorporating and analysing various key concepts such as reference groups, autobiographical memory, brand relationship, and market performance. We have also established that a better understanding of future anticipation could ultimately develop consumer's brand loyalty. In this chapter, we are going to focus on brand loyalty in the children's market, which is very challenging but also poses great potential. Specifically, this chapter attempts to identify factors which are recognised as the antecedents of brand loyalty in the children's market. The study conducted in this chapter was co-authored with Luiz Moutinho (Adam Smith School of Business, University of Glasgow, Scotland) and Arnaldo Coelho (Faculty of Economics, University of Coimbraw, Portugal).

Exploring Success Factors in the Children's Market

2014 ◽  
Vol 56 (6) ◽  
pp. 757-782 ◽  
Author(s):  
Jony Oktavian Haryanto ◽  
Luiz Moutinho
Keyword(s):  
Brand Loyalty ◽  
Success Factors ◽  
The Body ◽  
Body Of Knowledge ◽  
Brand Relationship

The potential of the child segment offers an immense opportunity for marketers to explore. In the ever more dynamic and ever changing children's market, the identification and ability to optimise the factors that can preserve product dominance are key to product longevity. This paper attempts to identify those factors that can influence the success of products in the children's market. We focus on identifying the antecedents of brand relationship and brand loyalty for the children's market. It is hoped that this study will contribute to the body of knowledge, and build understanding between the factors and their interrelations so that, in the end, product longevity in the children's market is finally achieved.

CHARACTERISTICS OF PATIENTS WITH BRAIN INJURY DUE TO LAND TRAFFIC ACCIDENTS TREATED AT NINH BINH PROVINCIAL GENERAL HOSPITAL IN 2018

2021 ◽  
Vol 62 (5) ◽  
Author(s):  
Luong Xuan Hien ◽  
Nguyen Quoc Tien ◽  
Tran Thi Phuong
Keyword(s):  
Brain Injury ◽  
General Hospital ◽  
Medical Records ◽  
Traffic Accidents ◽  
Brain Injuries ◽  
First Aid ◽  
Temporal Region ◽  
Age Group ◽  
Research Subjects ◽  
Broken Bones

This was an epidemiological study through a retrospective review of 215 medical records of patients with brain injury due to land traffic accidents treated at Ninh Binh Provincial General Hospital. Theresults showed that the majority of research subjects were male, accounting for 80.5%; The age group with higher prevalence of accidents was under 30 years old, accounting for 31.2%; The agegroup of 50-59 years old was at lower prevalence of accidents accounting for 15.8%. The time of the higher chance of occurring accident was between 4p.m and 11p.m daily. The majorityof traffic accidents occurred when riding motorbikes and electric bicycles (82.3%). About 75.0% of the victims received first aid with a gauze bandage; 5.4% of them had broken bones fixed. Amongthe brain injuries, 34.4% of the victims suffered from frontal trauma; 29.3% had unilateral cerebral hemisphere injury, 24.2% had temporal region injury, 15.8% had occipital region injury, and 8.4% ofvictims had parietal injury. More than half of the study subjects (53.5%) were hospitalized for 7-10 days. The rate of patients who have been discharged from the hospital with improved symptoms was81.4%; and 14.9% of patients were transferred to higher level hospitals.

scholarly journals On Synchronizing Coupled Retinogeniculocortical Pathways: A Toy Model

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
B. L. Mayer ◽  
L. H. A. Monteiro
Keyword(s):  
Neural Network ◽  
Visual Cortex ◽  
Corpus Callosum ◽  
Neuronal Activity ◽  
Network Topology ◽  
Cerebral Hemisphere ◽  
State Transition ◽  
Regular Lattice ◽  
Visual Cortices

A Newman-Watts graph is formed by including random links in a regular lattice. Here, the emergence of synchronization in coupled Newman-Watts graphs is studied. The whole neural network is considered as a toy model of mammalian visual pathways. It is composed by four coupled graphs, in which a coupled pair represents the lateral geniculate nucleus and the visual cortex of a cerebral hemisphere. The hemispheres communicate with each other through a coupling between the graphs representing the visual cortices. This coupling makes the role of the corpus callosum. The state transition of neurons, supposed to be the nodes of the graphs, occurs in discrete time and it follows a set of deterministic rules. From periodic stimuli coming from the retina, the neuronal activity of the whole network is numerically computed. The goal is to find out how the values of the parameters related to the network topology affect the synchronization among the four graphs.

scholarly journals Learners Demographics Classification on MOOCs During the COVID-19: Author Profiling via Deep Learning Based on Semantic and Syntactic Representations

2021 ◽  
Vol 6 ◽  
Author(s):  
Tahani Aljohani ◽  
Alexandra I. Cristea
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Prediction Models ◽  
Short Term Memory ◽  
Methodological Approach ◽  
High Accuracy ◽  
Directional Model ◽  
Textual Representations ◽  
The One

Massive Open Online Courses (MOOCs) have become universal learning resources, and the COVID-19 pandemic is rendering these platforms even more necessary. In this paper, we seek to improve Learner Profiling (LP), i.e. estimating the demographic characteristics of learners in MOOC platforms. We have focused on examining models which show promise elsewhere, but were never examined in the LP area (deep learning models) based on effective textual representations. As LP characteristics, we predict here the employment status of learners. We compare sequential and parallel ensemble deep learning architectures based on Convolutional Neural Networks and Recurrent Neural Networks, obtaining an average high accuracy of 96.3% for our best method. Next, we predict the gender of learners based on syntactic knowledge from the text. We compare different tree-structured Long-Short-Term Memory models (as state-of-the-art candidates) and provide our novel version of a Bi-directional composition function for existing architectures. In addition, we evaluate 18 different combinations of word-level encoding and sentence-level encoding functions. Based on these results, we show that our Bi-directional model outperforms all other models and the highest accuracy result among our models is the one based on the combination of FeedForward Neural Network and the Stack-augmented Parser-Interpreter Neural Network (82.60% prediction accuracy). We argue that our prediction models recommended for both demographics characteristics examined in this study can achieve high accuracy. This is additionally also the first time a sound methodological approach toward improving accuracy for learner demographics classification on MOOCs was proposed.

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