Shopping orientation segments: exploring differences in store patronage and attitudes toward retail store environments among female apparel consumers

Moye, Letecia N.; Kincade, Doris H.

doi:10.1046/j.1470-6431.2003.00260.x

Cited by 82 publications

(73 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Based on these findings, four levels of sophistication in demand sensing are summarized in Table 5. Segmenting stores according to the demand pattern is a common practice [56] and influences how stocks are deployed. Depending on the granularity, three levels of sophistication are identified in deploying stock according to segmentation (Table 6).…”

Section: Demand Sensing and Segmentationmentioning

confidence: 99%

An Exploration of Big Data Practices in Retail Sector

Aktaş

Meng²

2017

Logistics

View full text Add to dashboard Cite

Connected devices, sensors, and mobile apps make the retail sector a relevant testbed for big data tools and applications. We investigate how big data is, and can be used in retail operations. Based on our state-of-the-art literature review, we identify four themes for big data applications in retail logistics: availability, assortment, pricing, and layout planning. Our semi-structured interviews with retailers and academics suggest that historical sales data and loyalty schemes can be used to obtain customer insights for operational planning, but granular sales data can also benefit availability and assortment decisions. External data such as competitors' prices and weather conditions can be used for demand forecasting and pricing. However, the path to exploiting big data is not a bed of roses. Challenges include shortages of people with the right set of skills, the lack of support from suppliers, issues in IT integration, managerial concerns including information sharing and process integration, and physical capability of the supply chain to respond to real-time changes captured by big data. We propose a data maturity profile for retail businesses and highlight future research directions.

show abstract

Section: Demand Sensing and Segmentationmentioning

confidence: 99%

An Exploration of Big Data Practices in Retail Sector

Aktaş

Meng²

2017

Logistics

View full text Add to dashboard Cite

show abstract

“…Moye and Kincade (2003) [20] segmented American female apparel consumers, and found that members in the higher income group pursue their ability and reputation, but members in the lower income group Sustainability 2017, 9, 1012 3 of 12 look for bargains or do not hesitate to make a purchase if they like the good. These groups choose different kinds of stores as well.…”

Section: Shopping and Leisure Behaviors By Gender Age And Incomementioning

confidence: 99%

Spatial Homophily of Commercial Areas: The Case of Seoul

Kim

Choi

2017

Sustainability

View full text Add to dashboard Cite

This paper attempts to answer the question of whether or not "segregation", or at least "differentiation", takes place in commercial areas in terms of "spatial homophily". Based on the 2010 Household Travel Survey data in the Seoul metropolitan area, we first identify Seoul's top 20 destinations for weekend shopping and leisure trips. Then, using traveler information regarding gender, age, and income, we calculate the percentage of female visitors, as well as the average and the coefficient of variation of age and income, for each destination. These statistics are employed to identify which groups and which shopping and leisure activity centers are characterized distinctively by spatial homophily. As a result, it is proved that "differentiation" takes place in commercial areas in terms of "spatial homophily". Moreover, paying attention to the "Old Age, Low Income" cluster in the old downtown area, we can raise the possibility of "segregation" in commercial areas.

show abstract

“…In particular, fashionshopping orientation is a general purchasing behavior form encompassing psychological and behavioral aspects that appear when purchasing fashion items (Choi, 2015;Kim & Rhee, 2004;Lee & Ku, 2011;Park & Na, 2003). It provided the additional insight for the customer behavior pattern and was treated as an important variable influencing fashion store patronage as well as fashion product and store choice (Moye & Kincade, 2003).…”

Section: Fashion-shopping Orientationmentioning

confidence: 99%

The Influence of Shopping Orientation on Difficulty Discarding and Disposal Behavior of Fashion Products

Park¹,

Choo²,

Ku³

2016

SFTI

View full text Add to dashboard Cite

: Due to the rapid expansion of fashion, consumers easily purchase fashion products, the period of wearing apparel is shortened, and the occurrence of clothes piling up in the closet is increasing. In order to induce and suggest rational consumption and disposal actions, research focused on the factors influencing difficulty discarding and disposal behavior toward a fashion product is needed. Thus, this study considered fashion-shopping orientation as a variable affecting difficulty discarding and disposal behavior toward fashion products. A total of 325 questionnaires were collected, and 11 were discarded due to partial responses or missing data. Finally, a total of 314 survey questionnaires were analyzed. Frequency, exploratory factor, reliability, and multiple regression analyses were employed for data analysis using SPSS 23.0. The study results were as follows. First, hedonic and economic shopping orientation positively affected difficulty discarding a fashion product, whereas rational shopping orientation negatively affected difficulty discarding a fashion product. Second, hedonic, economic, and conspicuous shopping orientation positively affected reuse behavior among disposal behavior toward a fashion product. Third, trend-seeking and convenient shopping orientation positively influenced handover behavior. Fourth, economic and conspicuous shopping orientation positively affected separation discard behavior. The results of this study provide various guidelines for manufacturers and retailers of fashion products.

show abstract

Shopping orientation segments: exploring differences in store patronage and attitudes toward retail store environments among female apparel consumers

Cited by 82 publications

References 19 publications

An Exploration of Big Data Practices in Retail Sector

An Exploration of Big Data Practices in Retail Sector

Spatial Homophily of Commercial Areas: The Case of Seoul

The Influence of Shopping Orientation on Difficulty Discarding and Disposal Behavior of Fashion Products

Contact Info

Product

Resources

About