scholarly journals A Framework for Online Social Network Volatile Data Analysis: A Case for the Fast Fashion Industry

2020 ◽  
Vol 26 (1) ◽  
pp. 127-155
Author(s):  
Anoud Hani ◽  
Feras Al-Obeidat ◽  
Elhadj Benkhelifa ◽  
Oluwasegun Adedugbe
Keyword(s):  
Data Mining ◽  
Consumer Satisfaction ◽  
Online Social Network ◽  
Current Data ◽  
Fashion Industry ◽  
Fast Fashion ◽  
Specific Product ◽  
Data Mining Techniques ◽  
Fashion Products ◽  
Slow Fashion

Consumer satisfaction is an important part for any business as it has been shown to be a major factor for consumer loyalty. Identifying satisfaction in products is also important as it allows businesses alter production plans based on the level of consumer satisfaction for a product. With consumer satisfaction data being very volatile for some products due to a short requirement period for such products, current consumer satisfaction must be identified within a shorter period before the data becomes obsolete. The fast fashion industry, which is part of the fashion industry, is adopted as a case study in this research. Unlike slow fashion, fast fashion products have short shelf lives and their retailers must be able to react swiftly to consumer demands. This research aims to investigate the effectiveness of current data mining techniques when used to identify consumer satisfaction towards fast fashion products. This is carried out by designing, implementing and testing a software artefact that utilises data mining techniques to obtain, validate and analyse fast fashion social data, sourced from Twitter, to identify consumer satisfaction towards specific product types. In addition, further analysis is carried out using a sentiment scaling method adapted to the characteristics of fast fashion.

Hijabista willingness to accept premium pricing: an analytical study of the effect of social and self-identity on hijab fashion brands satisfaction

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alshaimaa Bahgat Alanadoly ◽  
Suha Fouad Salem
Keyword(s):  
Willingness To Pay ◽  
Product Design ◽  
Consumer Satisfaction ◽  
Willingness To Accept ◽  
Fashion Industry ◽  
Content Type ◽  
Self Identity ◽  
Fashion Products ◽  
Practical Implications ◽  
Brand Satisfaction

Purpose This paper aims to study the predictors influencing hijabista satisfaction towards Hijab fashion brands and their willingness to pay premium pricing as fashion consumers. The effects of product design, product quality, social and self-identity have been studied in relation to product, and brand satisfaction is believed to have led to acceptance of premium pricing. Various factors have been studied and analysed to provide a better understanding of Hijab fashion consumer behaviour. Design/methodology/approach Data were collected by using online structured surveys distributed within the area of Shah Alam City in Malaysia. Convenience sampling was used in defining the 223 target respondents, and the collected data was analysed using Smart-PLS Software. Findings The results highlighted that product design has the largest influence on the willingness of hijabistas in paying premium prices, followed by products that reflect their social-identity while communicating their religious obligations and commitments. Communicating one’s self-identity was also found not to have a significant impact which relates to the importance of the religious and social commitments on hijabista purchasing choices rather than their own self-conceptual image. Practical implications This paper provides insights on the factors that affect hijabista satisfaction towards Hijab fashion products and brands. Conclusions provided are very relevant to the practices of the fashion industry, and in particular, for designers to understand the needs of this large and significant segment of the fashion market. Originality/value Hijab fashion is a growing segment in the fashion industry, and it has been gaining recent global attention. Designers need to be more aware of the requirements of this segment of the fashion market. This research focusses on Hijab consumer satisfaction and how this reflects their willingness to pay premium prices for chosen products and brands. Factors such as product design and quality, along with social and self-identity, were studied in connection with hijabista willingness to accept premium pricing. Such connections and terms have not been covered in previous literature.

Incremental Discovery of Fuzzy Functional Dependencies

2011 ◽  
pp. 615-633 ◽  
Author(s):  
Shyue-Liang Wang ◽  
Ju-Wen Shen ◽  
Tuzng-Pei Hong
Keyword(s):  
Data Mining ◽  
Relational Databases ◽  
Search Algorithm ◽  
Current Data ◽  
Research Interest ◽  
Functional Dependencies ◽  
Incremental Search ◽  
Data Mining Techniques ◽  
Analysis Technique ◽  
Mining Algorithms

Mining functional dependencies (FDs) from databases has been identified as an important database analysis technique. It has received considerable research interest in recent years. However, most current data mining techniques for determining functional dependencies deal only with crisp databases. Although various forms of fuzzy functional dependencies (FFDs) have been proposed for fuzzy databases, they emphasized conceptual viewpoints and only a few mining algorithms are given. In this research, we propose methods to validate and incrementally search for FFDs from similarity-based fuzzy relational databases. For a given pair of attributes, the validation of FFDs is based on fuzzy projection and fuzzy selection operations. In addition, the property that FFDs are monotonic in the sense that r1 ? r2 implies FDa(r1) ? FDa(r2) is shown. An incremental search algorithm for FFDs based on this property is then presented. Experimental results showing the behavior of the search algorithm are discussed.

scholarly journals Slow Fashion in a Fast Fashion World: Promoting Sustainability and Responsibility

Laws ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 24
Author(s):  
Mark K. Brewer
Keyword(s):  
Corporate Responsibility ◽  
Fashion Industry ◽  
Environmental Footprint ◽  
Fast Fashion ◽  
Production Methods ◽  
Corporate Behavior ◽  
High Street ◽  
Slow Fashion ◽  
Detrimental Impact ◽  
Corporate Personality

Through its rapid production methods that supply the latest catwalk styles almost instantaneously to the high street, the fast fashion model has revolutionized the fashion industry, while generating a significant carbon footprint and a host of social concerns. Yet, the law is either slow or ineffective in promoting sustainability in a world obsessed with image and social connectivity, while outdated notions of companies continue to dominate the legal academy. This chapter initially examines the fashion industry’s environmental footprint. Then, it examines the rise of the fast fashion model and law’s inadequacy to prevent the model from undermining intellectual property rights or effectively address the model’s detrimental impact on environmental and social sustainability. The chapter then challenges traditional notions of corporate personality, calling for more responsible corporate behavior and greater legal scrutiny. Finally, the chapter considers various issues to enhance ethical behavior in companies, arguing that the slow fashion movement provides an alternative paradigm to the fast fashion model, since the slow fashion movement connects suppliers and producers more closely with consumers, thereby enhancing sustainability and corporate responsibility.

Data Mining Techniques for Distributed Denial of Service Attacks Detection in the Internet of Things

2016 ◽  
pp. 275-334 ◽  
Author(s):  
Pheeha Machaka ◽  
Fulufhelo Nelwamondo
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Denial Of Service ◽  
Current Data ◽  
The Internet ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Data Mining Techniques ◽  
The Internet Of Things

This chapter reviews the evolution of the traditional internet into the Internet of Things (IoT). The characteristics and application of the IoT are also reviewed, together with its security concerns in terms of distributed denial of service attacks. The chapter further investigates the state-of-the-art in data mining techniques for Distributed Denial of Service (DDoS) attacks targeting the various infrastructures. The chapter explores the characteristics and pervasiveness of DDoS attacks. It also explores the motives, mechanisms and techniques used to execute a DDoS attack. The chapter further investigates the current data mining techniques that are used to combat and detect these attacks, their advantages and disadvantages are explored. Future direction of the research is also provided.

scholarly journals Faktor pendorong purchase intention produk sustainable fashion pada UMKM

2021 ◽  
Vol 21 (1) ◽  
pp. 35-44
Author(s):  
Rike Penta Sitio ◽  
Rosita Fitriyani ◽  
Anggun Pesona Intan
Keyword(s):  
Purchase Intention ◽  
Research Method ◽  
Quantitative Research ◽  
Research Data ◽  
Fashion Industry ◽  
Fast Fashion ◽  
Fashion Products ◽  
Consumer Purchase Intention ◽  
Sustainable Fashion ◽  
Mediator Variable

The creative fashion industry is one of the sources of economic strength in great demand by businessman and consumers, such as MSMEs. The purpose of this study was to examine the effect of consumer knowledge on purchase intention in MSMEs sustainable fashion products with trust as a mediator variable. The research method will use quantitative research. The samples obtained were 257 consumers of Indonesian MSMEs fast fashion products and used the Qualtrics electronic questionnaire. This research data is from perception data for sustainable fashion knowledge variables, trust, and purchase intention in MSMEs sustainable fashion products. The data were processed using SPSS to test the validity, reliability, regression analysis, and mediation test using JASP. The results obtained are that consumers who know sustainable fashion will make these consumers more confident in sustainable fashion MSMEs products and ultimately increase consumer purchase intention in MSMEs sustainable fashion products. So, it is very important for MSMEs engaged in the sustainable fashion business to educate consumers about the meaning of sustainable fashion and the practice of MSMEs in a sustainable fashion.

Application of Data Mining Algorithms in Determination of Voting Tendencies in Turkey

2021 ◽  
pp. 134-149
Author(s):  
Ali Bayır ◽  
Sevinç Gülseçen ◽  
Gökhan Türkmen
Keyword(s):  
Data Mining ◽  
Current Data ◽  
Data Set ◽  
Data Mining Techniques ◽  
Human Behaviors ◽  
Political Sciences ◽  
Data Mining Algorithms ◽  
Number Of Factors ◽  
Mining Algorithms

Political elections are influenced by a number of factors such as political tendencies, voters' perceptions, and preferences. The results of a political election could also be based on specific attributes of candidates: age, gender, occupancy, education, etc. Although it is very difficult to understand all the factors which could have influenced the outcome of the election, many of the attributes mentioned above could be included in a data set, and by using current data mining techniques, undiscovered patterns can be revealed. Despite unpredictability of human behaviors and/or choices involved, data mining techniques still could help in predicting the election outcomes. In this study, the results of the survey prepared by KONDA Research and Consultancy Company before 2011 elections in Turkey were used as raw data. This study may help in understanding how data mining methods and techniques could be used in political sciences research. The study may also reveal whether voting tendencies in elections could be a factor for the outcome of the election.

Data Mining Techniques for Distributed Denial of Service Attacks Detection in the Internet of Things

2020 ◽  
pp. 561-608
Author(s):  
Pheeha Machaka ◽  
Fulufhelo Nelwamondo
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Denial Of Service ◽  
Current Data ◽  
The Internet ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Data Mining Techniques ◽  
The Internet Of Things

This chapter reviews the evolution of the traditional internet into the Internet of Things (IoT). The characteristics and application of the IoT are also reviewed, together with its security concerns in terms of distributed denial of service attacks. The chapter further investigates the state-of-the-art in data mining techniques for Distributed Denial of Service (DDoS) attacks targeting the various infrastructures. The chapter explores the characteristics and pervasiveness of DDoS attacks. It also explores the motives, mechanisms and techniques used to execute a DDoS attack. The chapter further investigates the current data mining techniques that are used to combat and detect these attacks, their advantages and disadvantages are explored. Future direction of the research is also provided.

scholarly journals Consumer Attitude towards Sustainability of Fast Fashion Products in the UK

2021 ◽  
Vol 13 (4) ◽  
pp. 1646 ◽  
Author(s):  
Bo Zhang ◽  
Yaozhong Zhang ◽  
Peng Zhou
Keyword(s):  
Consumer Attitude ◽  
Purchase Decisions ◽  
Fashion Industry ◽  
Online Questionnaire ◽  
Fast Fashion ◽  
Affective Component ◽  
Gender Culture ◽  
Fashion Products ◽  
Policy Interventions ◽  
The Uk

This paper attempts to provide an up-to-date depiction and analysis of the consumer’s attitude towards sustainability of fast fashion products in the UK. Four related strands of literature are reviewed to establish a tri-component model of attitude (ABC), i.e., Affective, Behavioural and Cognitive. A wide set of determinants for attitude is identified, including income, price, gender, culture, religion, age, etc. Based on this conceptual framework, an online questionnaire is designed and sent to university students and alumni in the UK, returning 128 valid responses. Both descriptive statistics and regression analysis (oprobit) are employed to shed light on the three components of attitude towards sustainability. It is found that cognitive and behavioural components converge across cultures and religions, but the affective component remains significantly diverse. Employment status contributes to the awareness, decision and feeling of sustainability features, but gender only matters for purchase decisions. In general, there is an improved cognitive and affective awareness of sustainability, but this does not automatically translate to purchase behaviour. Policy interventions like taxes and subsidies are still needed to foster sustainability in the fast fashion industry.

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