Transnational Flow of Chinese and UK Fashion Discourse: Analyses of Digital Platforms and Online Shopping in China

2021 ◽  
pp. 1-14
Author(s):  
Anthony Fung
Keyword(s):  
Online Shopping ◽  
Digital Platforms

scholarly journals TRAINING FOR IMPROVING SKILL ON USING PLATFORM DIGITAL FOR TRAINEE OF STUDENT DEVELOPMENT PROGRAMME

2020 ◽  
Vol 8 (3) ◽  
pp. 338
Author(s):  
Zainal Abidin ◽  
Alim Harun Pamungkas
Keyword(s):  
Student Development ◽  
Public Interest ◽  
Online Shopping ◽  
Business Management ◽  
Development Programme ◽  
Qualitative Approach ◽  
Marketing Concept ◽  
Development Programs ◽  
Digital Platforms ◽  
Training Activities

The problems faced as a necessity for implementing entrepreneurial development programs are: (1) business management towards a better direction, so as to reduce the risk of business loss due to efficiency; (2) the increasing public interest in shopping using digital platforms (online shopping) demands a more efficient product marketing concept; (3) empowerment of communities around the business location so that it can assist the production and marketing processes and can become an alternative for business activities that support the economy of the surrounding communities. The method used is a qualitative approach as initial data from research which is realized through training activities for students. Ten students who were targeted were the participants of the training activities. The results obtained are: (1) training on the use of digital platforms for business management; (2) training on the use of digital platforms for business promotion; and (3) training for establishment and empowerment of community business groups.

scholarly journals PERAN KEPERCAYAAN DAN SIKAP TERHADAP MOBILE SHOPPING UNTUK MENINGKATKAN NIAT PEMBELIAN ULANG

2020 ◽  
Vol 15 (2) ◽  
pp. 307-319
Author(s):  
Ken Sudarti ◽  
Annissa Aprilia Sari
Keyword(s):  
Artificial Intelligence ◽  
Millennial Generation ◽  
Industrial Revolution ◽  
Online Shopping ◽  
Sampling Technique ◽  
Perceived Usefulness ◽  
Digital Platforms ◽  
Central Java ◽  
Mobile Shopping ◽  
The World

The world has now entered the era of the Industrial Revolution 4.0, where in this era the world was colored by artificial intelligence (artificial intelligence), genetic engineering, nanotechnology, innovation, and changes that occurred rapidly had an impact on the economy, industry, government, and politics. Industry 4.0 is more likely to lead to business activities using digital platforms such as mobile shopping, e-commerce, marketplaces, and so on. The characteristic of online shopping is that it must be simple and fun, and with a very varied platform can increase its own trust in consumers to shop online. This study aims to develop the concept of a business platform that can affect the perceived usefulness and perceived enjoyment of the millennial generation in online shopping. This concept focuses on one's repurchase intention to do online shopping which is influenced by the existence of so many business platforms and provide different services. The population used is characteristic of the millennial generation in Central Java. This sampling technique using purposive sampling method. The samples used amounted to more than 100 millennials in Central Java, and who frequently use business platforms/applications in online shopping. Data analysis techniques using regression with SPSS

scholarly journals Digital In-Store Shopping

2018 ◽  
Vol 2 (1) ◽  
pp. 44-48
Author(s):  
Diogo Barbosa
Keyword(s):  
Online Shopping ◽  
Digital Platforms ◽  
Support Device ◽  
Retail Chains

In a world where online shopping and digital interactions are growing constantly, one must be aware of their consequences for retail and how it can benefit from this. Big retail chains are keeping up with the phenomena by reinventing its way to attract more shoppers, either by creating very complete online portals or by bringing technology to its physical spaces.This paper brings some data on how consumers are using digital platforms for buying goods while inside a physical store. It concludes that a growing number of consumers are using mobile as an in-store support device as well as retailers are using it to attract consumers to stores.The paper also shares some data from a small inquiry made to Portuguese users about their use of mobile for in-store shopping purposes.

scholarly journals MILLENNIAL CUSTOMER LOYALTY IN ONLINE SHOPPING ON DIGITAL PLATFORMS: A PERSPECTIVE OF NET PROMOTER SCORE

2021 ◽  
Vol 22 (2) ◽  
pp. 162-175
Author(s):  
Slamet Slamet ◽  
Findi Dia Finalia Sari ◽  
Indrayati Indrayati ◽  
Ilya Azmala
Keyword(s):  
Statistical Analysis ◽  
Customer Loyalty ◽  
Online Shopping ◽  
Digital Platforms ◽  
Digital Platform ◽  
Net Promoter Score ◽  
Net Promoter ◽  
Single Question ◽  
Descriptive Statistical Analysis

This study maps and analyses the customer loyalty level, namely, the Millennials aged 23-38 shopping online through digital platforms in 2020. The study's objects include, Bukalapak.com, Shopee.co.id, Tokopedia.com, Bibbli.com, Lazada.co.id, Carrefour.co.id, Indomaret.com, Zalora.co.id, Tiket.com, Traveloka.com, Gojek.com, Grab.com, and Gopay.com. The survey was conducted in Malang City and Regency, Indonesia. The instrument used was a questionnaire containing the respondent's profile and a single question about the willingness to offer recommendations to friends or colleagues. The questionnaire was circulated using Google Forms through WhatsApp and email. Furthermore, descriptive statistical analysis was used to describe the data in percentage, while the Net Promoter Score (NPS) method was used to determine customer category. The results showed that most consumers using the digital platform were in the Detractor (46.15%), including Lazada.co.id (NPS=-1.30%), Tiket.com (NPS-1.80%), Carrefour.co.id (NPS=-3.66%), Zalora.co.id (NPS=-3.68%), Bukalapak.com (NPS=-12.03), and Blibli.com (NPS=-18.13%). It means those platforms have disloyal consumers due to poor service. The second level is in the Passive category (38.46%), including Gojek.com (NPS=39.48%), Traveloka.com (NPS=32.92%), Tokopedia.com (NPS=23.82%), Gopay.com (NPS=23.4%), and Indomaret.com (NPS=22.91%). It means their services are satisfactory. Only 15.38% of consumers are in the Promoter, namely Shopee.co.id (NPS=53.86%) and Grab.com (NPS=56.32%). The services of these platforms are excellent, and their customers are very loyal. Thus, based on the NPS method, digital platform users in Indonesia are mostly Detractor and Passive users, very few in the Promoter category.

An old friend is better than two new ones? Approaches to market research in the context of digital transformation for the antitrust laws enforcement

2020 ◽  
pp. 37-55 ◽  
Author(s):  
A. E. Shastitko ◽  
O. A. Markova
Keyword(s):  
Business Models ◽  
Rapid Development ◽  
Digital Transformation ◽  
Market Definition ◽  
Type I ◽  
Type Ii ◽  
Digital Platforms ◽  
Advantages And Disadvantages ◽  
Pass Through ◽  
Type Ii Errors

Digital transformation has led to changes in business models of traditional players in the existing markets. What is more, new entrants and new markets appeared, in particular platforms and multisided markets. The emergence and rapid development of platforms are caused primarily by the existence of so called indirect network externalities. Regarding to this, a question arises of whether the existing instruments of competition law enforcement and market analysis are still relevant when analyzing markets with digital platforms? This paper aims at discussing advantages and disadvantages of using various tools to define markets with platforms. In particular, we define the features of the SSNIP test when being applyed to markets with platforms. Furthermore, we analyze adjustment in tests for platform market definition in terms of possible type I and type II errors. All in all, it turns out that to reduce the likelihood of type I and type II errors while applying market definition technique to markets with platforms one should consider the type of platform analyzed: transaction platforms without pass-through and non-transaction matching platforms should be tackled as players in a multisided market, whereas non-transaction platforms should be analyzed as players in several interrelated markets. However, if the platform is allowed to adjust prices, there emerges additional challenge that the regulator and companies may manipulate the results of SSNIP test by applying different models of competition.

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