Determinants of the Intention to Buy Clothes in the Online Stores of the MiPyMe of Perú, Colombia and México

With the recent coronavirus pandemic (Covid-19) online sales of clothing retail have become a necessity to survive in the market. It is for this reason that the objective of the research was to know the purchase intention of clothing by young consumers through the online channel of small and micro companies (MiPyMe) located in the countries of Mexico, Colombia and Peru. To do this, using a structural equations model, it was intended to analyze the relationships between the variables trust, satisfaction, perceived value, quality of interaction and image in the electronic context as antecedent variables of online purchase intention, in accordance with the theoretical framework. 638 surveys were applied to young consumers in Mexico, Colombia and Peru. Sociodemographic characteristics included gender, age, country, and knowledge of a MiPyMe online clothing store. The results reveal that, of the total of young people surveyed, 62.7% stated that they did not know of any online clothing store of a MiPyMe. The contrasting of the hypotheses indicates that the quality of interaction directly and positively influences perceived value, that the image directly and positively influences the satisfaction and purchase intention of the consumer of the MiPyMe of Colombia, Mexico and Peru. These results may be useful for entrepreneurs in this business sector to rethink their online business strategies, as well as for the governments of these nations to promote this sector with training and specialized technical assistance.

The Effect of Business Location on Sales Result in the Traditional Market

Accuracy in choosing a location is one of the factors that determine the success of a business. Entrepreneurs always have a location close to customers in order to provide primary service to customers so that relationships can be maintained properly. The right business location is expected to meet consumer expectations in order to obtain profit, but if there is an error in choosing a business location automatically the maximum profit will not be obtained by the entrepreneur. The purpose of this research was to determine the effect of choosing a business location on sales. The selection of sales locations is very influential on the sales results of traders. Place/location of business is one element of the marketing mix which is very important for the continuity of a business. This type of research includes field research, namely the new market clothing store and the old market in the Rantauprapat. This research is descriptive, because this study seeks to collect existing facts. This research focuses on efforts to reveal a problem and the situation as it is, which is examined is the technique of interviewing and documentation. While the data analysis was carried out using the data obtained in the form of descriptions, then the data were analyzed using inductive thinking. The results of the research indicate that there is a very strong relationship between the place of business and the profit. The place of business has a positive effect on the profits obtained by the trader.

The effect of service marketing mix elements and customer retentiontowards clothing store brands in ChIna

The aim of this paper was to analyse the impact of service marketing mix (promotion, price, place, product, people,process, physical evidence and after sale service) on customer retention towards clothing store brands in China. Basedon the analysis of past literature, it appeared that there were only few studies examining the empirical relation betweenthe two constructs, particularly in the clothing sector in China. A comprehensive survey approach was used to collectdata from a total of 385 customers visiting clothing stores in the middle part of China (Hubei). SPSS and PLS were usedto analyse the obtained data. The findings showed that there were significant positive effects on customer retention inall dimensions of the service marketing mix. Finally, the findings suggested that after-sales service plays an importantrole in impacting the retention of customers. The contribution of this research was supporting the significancerelationship of the marketing mix elements in influencing the retention of customers in the clothing industry with empiricaldata from China.

Smells in Sustainable Environments: The Scented Silk Road to Spending

Humanity's demand for ecological resources and services exceeds what earth can regenerate in that year, creating an urgent need for more sustainable behavior. Here, the focus is on a particular factor that so far has been overlooked in facilitating sustainable behavior, namely smell. The two-fold aim of this study was (i) to investigate whether ambient scent could enhance customers' subjective experience and spending behavior in a sustainable environment, and (ii) to elucidate the affective and cognitive pathways from scent to spending. To test this, a double-blind field experiment was designed where customers of a second-hand clothing store (N = 57) could face one of three conditions: fresh linen scent (pleasant and semantically priming “clean clothing” increasing the products' value), vanilla sandalwood scent (pleasant control odor), or regular store odor (odorless control). Buttressed by prior research, the fresh linen scent was expected to cause the strongest increase in spending behavior due to its positive semantic association with the product (i.e., clean clothing). The results indeed showed that fresh linen scent almost doubled consumer spending vs. the odorless control and the pleasant control odor. Other factors potentially affecting consumer behavior (e.g., weekday, weather, odor awareness) were uncorrelated. Whereas a conceptually-driven mediation analysis showed that only fresh linen scent increased mood and evaluations of the store, staff, and products, these variables did not mediate the relation between scent and spending. An explorative structural equation model suggested cognitive priming to be mainly responsible for increasing consumers' spending in the fresh linen condition by enhancing the general store evaluation. Further support is needed to corroborate the indirect findings that specific scents can follow a “cold” semantic road and a “hot” affective road to spending. At minimum, consumers are no “zombies” that empty their pockets in the presence of whatever odor; the smell needs to have a meaningful link to the (sustainable) context at hand to influence consumer behavior.

PENGARUH KEPERCAYAAN KONSUMEN, KUALITAS PRODUK DAN PERSEPSI HARGA TERHADAP KEPUTUSAN PEMBELIAN DI FLAMINGGO COLLECTION

The purpose of this study is to determine the effect of consumer trust, product quality, and price perceptions on purchasing decisions at the Flaminggo Collection. The Analysis technique of this research was conducted using component-based SEM method using Partial Least Square approach. The basis used for hypothesis testing on PLS is resampling with bootest strapping developed by Geisser and Stone. The variable are Consumer trust (X1), Product quality (X2), Price perception (X3), and Purchase Decision (Y). The primary data in this study was by distributing questionnaires to flaminggo collection consumers. It involved 60 respondents with aged 16-33 years. Secondary data used in this study is data obtained from Flaminggo Collection for the last 6 years (2014-2020). The results of the analysis show that Consumer Trust can play an important role in Purchasing Decisions at the Flaminggo Collection because the higher consumer trust, the higher the purchasing decision at the clothing store. Product quality can play an important role in the Flaminggo Collection because the higher the quality of the product, the higher the purchasing decision at the clothing shop. Price perception can play an important role in purchasing decisions at the Flaminggo Collection because the higher the price perception, the higher the purchasing decision at the clothing store. Keywords: consumer trust, product quality, price perception, and purchase decision.

Effect of Service Quality on Service Value and Customer Retention for Clothing Store Brands in China

An increasing number of new Chinese clothing store brands are selling and offering similar products and services and consequently clothing store brand providers must compete to survive in this industry. They need to focus on customers’ special needs and preferences to maintain and retain a long-term relationship. The objective of this study is thus to examine the relationship between service quality and customer retention for clothing store brands in China, and the mediated effect of service value in the relationship between service quality and customer retention for clothing store brands in China. A quantitative research for data collection was implemented. As many as 385 questionnaires were collected by the professor, PhD students, MSc students and BSc students of different nationalities in China. The data was analysed using SmartPLS and SPSS software. Customer perception of the quality of a service product in all sizes has a beneficial effect on customer retention. Service value affects customer retention positively. Practical implications for the target market of the clothing sector should be focused on young individuals aged 36 to 45 years, holding a Master’s degree and earn more than €1,000/month. Findings indicated significant and direct relationships between service quality, service value and customer retention. It was also found that service value has a full mediated effect. This study will be of interest to the clothing store brands in understanding how service quality is essential for maintaining a long-term relationship with customers.

An effective recommender system based on personality traits, demographics and behavior of customers in time context

PurposeImproving the performance of recommender systems (RSs) has always been a major challenge in the area of e-commerce because the systems face issues such as cold start, sparsity, scalability and interest drift that affect their performance. Despite the efforts made to solve these problems, there is still no RS that can solve or reduce all the problems simultaneously. Therefore, the purpose of this study is to provide an effective and comprehensive RS to solve or reduce all of the above issues, which uses a combination of basic customer information as well as big data techniques.Design/methodology/approachThe most important steps in the proposed RS are: (1) collecting demographic and behavioral data of customers from an e-clothing store; (2) assessing customer personality traits; (3) creating a new user-item matrix based on customer/user interest; (4) calculating the similarity between customers with efficient k-nearest neighbor (EKNN) algorithm based on locality-sensitive hashing (LSH) approach and (5) defining a new similarity function based on a combination of personality traits, demographic characteristics and time-based purchasing behavior that are the key incentives for customers' purchases.FindingsThe proposed method was compared with different baselines (matrix factorization and ensemble). The results showed that the proposed method in terms of all evaluation measures led to a significant improvement in traditional collaborative filtering (CF) performance, and with a significant difference (more than 40%), performed better than all baselines. According to the results, we find that our proposed method, which uses a combination of personality information and demographics, as well as tracking the recent interests and needs of the customer with the LSH approach, helps to improve the effectiveness of the recommendations more than the baselines. This is due to the fact that this method, which uses the above information in conjunction with the LSH technique, is more effective and more accurate in solving problems of cold start, scalability, sparsity and interest drift.Research limitations/implicationsThe research data were limited to only one e-clothing store.Practical implicationsIn order to achieve an accurate and real-time RS in e-commerce, it is essential to use a combination of customer information with efficient techniques. In this regard, according to the results of the research, the use of personality traits and demographic characteristics lead to a more accurate knowledge of customers' interests and thus better identification of similar customers. Therefore, this information should be considered as a solution to reduce the problems of cold start and sparsity. Also, a better judgment can be made about customers' interests by considering their recent purchases; therefore, in order to solve the problems of interest drifts, different weights should be assigned to purchases and launch time of products/items at different times (the more recent, the more weight). Finally, the LSH technique is used to increase the RS scalability in e-commerce. In total, a combination of personality traits, demographics and customer purchasing behavior over time with the LSH technique should be used to achieve an ideal RS. Using the RS proposed in this research, it is possible to create a comfortable and enjoyable shopping experience for customers by providing real-time recommendations that match customers' preferences and can result in an increase in the profitability of e-shops.Originality/valueIn this study, by considering a combination of personality traits, demographic characteristics and time-based purchasing behavior of customers along with the LSH technique, we were able for the first time to simultaneously solve the basic problems of CF, namely cold start, scalability, sparsity and interest drift, which led to a decrease in significant errors of recommendations and an increase in the accuracy of CF. The average errors of the recommendations provided to users based on the proposed model is only about 13%, and the accuracy and compliance of these recommendations with the interests of customers is about 92%. In addition, a 40% difference between the accuracy of the proposed method and the traditional CF method has been observed. This level of accuracy in RSs is very significant and special, which is certainly welcomed by e-business owners. This is also a new scientific finding that is very useful for programmers, users and researchers. In general, the main contributions of this research are: 1) proposing an accurate RS using personality traits, demographic characteristics and time-based purchasing behavior; 2) proposing an effective and comprehensive RS for a “clothing” online store; 3) improving the RS performance by solving the cold start issue using personality traits and demographic characteristics; 4) improving the scalability issue in RS through efficient k-nearest neighbors; 5) Mitigating the sparsity issue by using personality traits and demographic characteristics and also by densifying the user-item matrix and 6) improving the RS accuracy by solving the interest drift issue through developing a time-based user-item matrix.

Inventory and Sales Information System Design on Clothing Store (Case Study: X Fashion, Jakarta)

The progress of time continually accompanied by the development of technology. It leads to the competition among industries that require them to have superiority to attract more consumers. X Fashion is one of the fashion industries which sells various apparel products for people in the sale of large or small scale. The business processes of X Fashion is procuring products, managing inventory, sales, and managing finance. A lot of variations and number of products in the store are not in balance with a good management because all forms of recording are done manually. It causes potential error so that the information disseminated is inaccurate. Based on this consideration, a research is conducted as inventory and sales information system design on X Fashion clothing store to identify business process also to design an inventory and sales information system on X Fashion clothing store. The method used is Systems Development Life Cycle which consists of systematic steps for developing, designing, and maintaining the system to meet the needs of users, including supervision, recording, and reporting. Information system is designed to provide stock data, expense, and income reports automatically. Testing of the system includes system testing, function testing, learnability, logic testing, memorability, and measurement of satisfaction. Based on the test results, the information system was stated feasible and can be used to support business processes on X Fashion clothing store. Suggestions for further research on information system design are development of system design in order to be compatible on smartphone, also an addition of brief information on every control or using user guide in order to describe system function

Rancang Bangun Sistem E-commerce Clothing Store dan Modul Custom Design Lab Terintegrasi

Kemudahan akses internet saat ini dan faktor kemudahan dalam mengembangkan sebuah website E-commerce menjadi alternatif yang laris bagi para penggiat bisnis di dunia internet. Toko baju online adalah salah satu jenis bisnis E-commerce yang banyak bermunculan di dunia internet saat ini. Penerapan E-commerce pada bisnis ini dapat menangani proses perdagangan yang terdiri dari proses pemesanan, pembelian, pembayaran, hingga pengiriman barang. Kustomisasi pemesanan terhadap barang yang dipesan juga menjadi salah satu nilai tambah yang dapat ditawarkan kepada calon konsumen. Adanya modul yang disebut dengan Custom Design Lab dapat menjadi solusi terhadap permintaan tersebut. Modul ini dalam implementasinya akan diintegrasikan dengan sistem E-commerce yang ada sehingga proses perdagangan yang ada juga berlaku pada sistem preorder tersebut. Pengembangan website E-commerce ini menggunakan framework PyroCMS sebagai aplikasi dasar dengan melakukan konfigurasi pada beberapa modulnya. Fokus utama dari penelitian ini adalah dihasilkannya sebuah situs E-commerce yang sudah merepresentasikan proses bisnis online secara umum dan juga sudah memiliki fitur Custom Design Lab untuk kustomisasi pemesanan produk.