Purpose - The study was AI as exploratory study on artificial intelligence (AI) shopping information services, to explore the possibility of a new business of the distribution industry. For research, we compare to IBM of consumer awareness surveys an AI shopping information service for retailing channel and target goods group. Finally, we present to service scenario for distribution service using AI. Research design, data, and methodology - First, to identify possible the success of the information service shopping using AI, AI technology for the consumer is very important for the acceptance of judgement. Therefore, we explored the possibility of AI information service for business as a shopping. The experimental data were used to interpret the meaning of the relevant literature and the IBM Institute of Business Value (IBV) Report 2015. This research is based on the use of a technical acceptance model (TAM) to determine whether the consumer would adopt the 'AI shopping information service' technology. Step 1 of the process assumes that the consumer adopts AI technology. In step 2, consumers find their preference channels and goods targeted at them as per their preferences. Finally Step 3, we present scenario for 'AI shopping information service' based on the results of Step 1 and 2. Results - Consumers have expressed their high interests in the new shopping information services, especially the on/off line distribution channels can use shopping information to increase the efficiency in provision of goods. Digital channel (such as SNS, online shopping etc.) is especially high value goods such as cars, furniture, and home appliances by displaying it to an appropriate product group. Conclusions - The study reveals the potential for the use of new business models such as 'AI shopping information service' by the distribution industry. We present seven scenario related AI application refer from IBM suggestion, and the findings would enable the distribution industry to approach target consumers with their products, especially high value goods. 'Shopping advisor' is considered to the most effective. In order to apply to the other field of the distribution industry business, which utilizes AI technology, it should be accompanied by additional empirical data analysis should be undertaken.
This study is set out to investigate the factors that influence customers' behavior of choice and switching between online and offline channels, separating the purchase decision into two stages, i.e., information search and purchase. Factors influencing channel choice are found to differ from stage to stage. The main results of this study are as follows. At the information search stage, customers' channel knowledge had impacts on the choice of the channel. Customers are more likely to visit offline bookstores when they have hedonic shopping orientation and higher involvement level with books. On the contrary, customers are more apt to search online when they have a lot of online shopping experiences. At the purchase stage, the results varied according to the search channel. When customers search for information online, the following variables lead to online purchases: online shopping experiences with books, price-focused shopping orientation, and time availability for shopping. Perceived risk made customers purchase offline even though they searched online. In case of offline searching, customers with more convenience-focused, hedonic-focused shopping orientation and less tim availability purchased offline.
Lotte Shopping Co. started its business from Lotte Department Store. From the beginning, Lotte Shopping Co. opened the largest department store and, since then, has expanded its business size through the processes of active developments of its own stores and merges and acquisitions of other companies. Currently, it operates a variety of retail shops such as department stores, discount stores, movies theaters, shopping malls, and supermarkets along with a TV home-shopping station and an online shopping mall. Lotte group, a business conglomerate Lotte Shopping belongs to, has an objective of becoming TOP 10 business group in Asia by 2018. Lotte group declared its vision statements in 2009 and has spent its effort to accomplish the goal. Lotte Shopping is implementing the group-level growth strategy through merges and acquisitions and diverse marketing programs. We will briefly investigate the current situation of Lotte Shopping and will then analyze its 1) entertainment shopping center and multi-channel strategy, 2) global market entry, and 3) education system.
This paper investigates the determinants which influence the intention to adopt the Internet shopping mall in the form of a new B2C by off-line manufacturers or service providers in their design of a channel. The current study purports to provide managerial suggestions for a firm that sets up channel design strategies, with the Internet channel considered. Research findings are as follows: First, the intention to adopt the Internet shopping mall increases as a firm's relative benefits are perceived higher; second, as organizational readiness increases, the intention to adopt the Internet shopping mall increases; third, the intention to adopt the Internet shopping mall decreases as the level of perceived barriers on the Internet increases, and fourth, as the level of perceived social/organizational pressures is higher, the intention to adopt the Internet shopping mall increases. In addition, this paper presents theoretical and practical Implications, given the limits of the current study.
Due to recent proliferation of the mobile shopping channels, customers increasingly tend to purchase using online channel while experiencing physical products in offline shops. This phenomenon requires traditional offline retailers to consider integrating online channels. In this study, we propose strategic options for the traditional offline retailers regarding the online channel integration, and provide corresponding decision models to maximize the expected profits. We also investigate how the strategic options vary with the product characteristics, by categorizing the products based on inventory cost, demand uncertainty, and fitness to the online channels. By analyzing numerical examples we illustrate how the best online channel integration strategy should be differentiated depending on the product categories.
The emergence of the cable television era has spawned the introduction of many new television programming formats such as all-news channels, movie channels, channels catering to cultural events, channels for women, and many others. One of the new programming formats that is expected to have interesting implications for marketing is the home shopping channel. As we have observed in other countries, this new form of distribution may potentially have a major impact on the traditional retail industry. This paper presents a model of home shopping channel viewing behavior. This model is then used to formulate optimal product presentation strategies that may aid managers in the design of home shopping programs. Specifically, by formulating a profit-maximization problem based on tile model, we derive the optimal length of product presentations and explore its properperties through simulating various situations. The discussion of these properties provide insights about making strategic decisions regarding product presentations.
Journal of the Korean Society of Clothing and Textiles
/
v.44
no.1
/
pp.141-158
/
2020
This study examines age differences with respect to consumers' clothing purchase behavior. First, the differences of age groups were investigated according to clothing purchase behavior, which include purchase item, purchase price, purchase channel, information resources, purchase frequency, and monthly clothing expenditures. Second, the differences of segmented groups by age variable were investigated according to clothing purchase behaviors after segmenting consumers by clothing shopping orientation. An on-line survey was conducted from July 2 to July 10, 2019, and 500 data were collected from adults aged 20s to 60s who had bought their own clothes within one year. Data were analyzed by descriptive statistics, factor analysis, reliability analysis, chi-squared test, ANOVA and Duncan-test using SPSS 21.0. This findings showed that there were significant differences in purchase item, purchase price, purchase channel, purchase frequency, and information resources according to age group. As a result of segmentation by shopping orientation, consumers were classified into three groups of high shopping involvement, low shopping involvement, and economic pursuit. In addition, there were partly significant differences in clothing purchase behavior according to classified groups by age variable.
In this study, we determined the characteristics and importance of market maven to today's fashion retailers. Market maven is defined as an individual who is highly involved in the marketplace and takes a role as an information diffuser. In order to identify market maven, a total of 415 data were collected from 30-40 consumers who purchased fashion items from the various types of retailers. The data were divided into three groups based on the average score of summated market maven's scale, and the high group was referred to as "market mavens." Results suggested that the market mavens existed in the fashion retailing market and presented the differences from the other two groups. The market maven group spent more and purchased more fashion items than the other groups. With respect to shopping behavior, the market maven group was more likely to browse and bargain hunt when shopping, and showed higher mean scores on impulse buying and overall satisfaction. In addition, market maven tended to purchase fashion items from different types of retailers including online channel. Accordingly, market mavens seemed to present common characteristics with heavy browser, recreational shopper, and/or multi-channel shopper. Market mavens showed shopping enjoyment characteristics when searching for market-related information from various retailers, hence this segment should be the essential target market in the multi-channel retailing environment.
With the advent of a wide variety of Internet shopping malls, consumers can choose a best appealing shopping mall from among the Bricks-and-Clicks and Pure-Player malls. Pure-Players launched their operation grandiosely with the early stage of Internet use in 1995. However, after the burst of Dot-com company bubbles in 1997, Pure-Players introduce various types of business models to meet potential needs of consumers. While Pure-Players suffer skeptical views from market analysts as well as consumers, traditional offline companies learned important lessons from Dot-com companies collapse phenomena, and expanded their business channels into online in the name of Bricks-and-Clicks. Nowadays, Bricks-and-Clicks successfully establish in the market as one of reliable business partners among consumers. Therefore, it is no surprise that recent competitions between Bricks-and Clicks and Pure-Players become fiercer than ever to attract potential customers to their websites. In this situation, consumers can choose a shopping mall to their best satisfaction. Consumers can enjoy both offline and online options for shopping because Bricks-and Clicks provide both offline and online channels to consumers, which is compared with Pure-Players offering only online channel. Offline channel is unique in providing consumers with chances to touch and feel target products and services. Meanwhile, online channel is considered very viable and convenient shopping options for consumers. In this respect, it is easily assumed that consumers will show different online shopping behavior when they have to choose either Bricks-and-Clicks mall or Pure-Player mall for the sake of shopping. Remaining research issue in this case is how much consumers' schema would influence online shopping behavior between Bricks-and-Clicks and Pure-Players. Basically, schema is a framework for synthetic information recognition that individual consumers have and is very characteristic in that it focuses not on fragmentary facts but on the combination of various causes affecting results. Consumers' schema is closely represented by trust, structural assurance, and perceived relative advantage towards a specific type of shopping mall. In literature, there exist a lot of studies comparing Bricks-and-Clicks and Pure-Players. However, there is no study to pursue the analysis of consumer behaviors comparing Bricks-and Clicks and Pure-Players from the schema perspective. Therefore, this study aims to investigate this research gap. Empirical analysis is adopted by garnering valid questionnaires from 514 Internet shopping mall users. 237 were mainly using Bricks-and-Clicks for shopping, while 277 were found to visit Pure-Players for shopping. PLS was applied to analyze the survey data to verify the proposed research hypotheses. Findings from the empirical test results are as follows. First, consumers perceive more trust and relative advantage in Pure-Players, comparing with Bricks-and-Clicks. This result is against widely-accepted perception that Bricks-and-Clicks would be perceived by consumers as more trustworthy and relatively advantageous because they have offline reputation and stores. Therefore, it becomes more obvious that Internet is becoming daily necessaries, and consumers increasingly feel very comfortable in using the Internet for their own personal purposes. Second, consumers have firm faith in transaction safety, regardless Bricks-and-Clicks and Pure-Players. This seems due to the fact that most of shopping malls showing dubious transaction safety have no place in the market. In a nutshell, empirical results tell us that Pure-Players will grow very much in the future, to the extent that consumers perceive no difference in comparison with Bricks-and-Clicks. Besides, consumers' schema accumulated through trust and perceived relative advantage plays crucial role in determining consumer behavior.
This study is a food shopping experience of omni-channel. Food threats and healthy living concerns bring different channels in led to increase reasonable way such as various demand. Omni-channels should be premised on understanding customer behavior as well as empirical user types in which considerations including the value of experience and understanding consumer behavior. Online survey result showed that, (1)offline food shopping, major retail store with quality, buy fresh food directly 2~3 times a month (2)online food shopping, e-commerce site with costs, buy fruits & nuts 2~3 times a month. After in-depth interview with eight high quality participants, I analyzed needs for food shopping experience in regard to the four steps food purchasing journey then derived a persona with integral value 'health' and 'diet'. It is classified into two types. One is the primary persona, family and health oriented, considering household money 'saving', and other is secondary persona, work and personal oriented, looking forward to 'automatic supply'. The result of this study provided an insight that help us explore ways to resolve function and services in the context of a healthy and balanced diet for improving food shopping experience of omni-channel.
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