Omni-Channel Retailing and Firm Performance from a Customer Lifetime Value Perspective

In the digital era,retailers are keen to find out whether omni-channel retailing helps improve long-term firm performance.In this paper,we employ machine learning techniques on a large consumption data set in order to measure customer lifetime value(CLV)as the basis for determining long-term firm performance,and we provide an empirical analysis of the relationship between omni-channel retailing and CLV.The results suggest that omni-channel retailing may effectively enhance CLV.Further analysis reveals that this process is influenced by heterogeneous consumer requirements and that significant differences exist in the extent to which the omni-channel transition may influence CLV depending on consumer preferences for diversity of commodities,sensitivity to the cost of contract performance,and sensitivity to warehousing costs.Hence,retailers should provide consumers with a complete portfolio of goods and services based on target consumers’heterogeneous requirements in order to increase omni-channel efficiency.

Downtown Retailing Development Under Suburbanization——A Case Study of Beijing

The role of retailing has diminished in the center of cities of Western countries since its heyday in the 1920s. This trend was caused by violent transformations in the economic, social and locational contexts which involve resi- dential suburbanization, as well as new forms of commercial development out of town. As far as transforming China is concerned, the downtown retailing center has also come to turning point of development in the context of suburbaniza- tion. Based on the survey of Beijing residents’ shopping behavior, the present research tends to making clear the actual change and development problem of downtown retailing center. Combining with the macro retailing environment, re- lated influencing factors are further discussed too. Study results show that downtown retailing still plays an important part in resident’s shopping activity. However, with rapid urban sprawl, retailing in urban center has been greatly threatened by booming out-of-town commerce. In the course of such spatial change, the suburbanization of resident, the prevalence of new commercial forms and the change of consumers’ life style all have exerted their own pressure on downtown retailing. But for the special socioeconomic background of development and the support of government policy, it will still keep its vitality of retailing for a long period of time.

Wal-Mart's Corporate Culture and the Suggestions for China's Retailing Industry in Culture-Building

With sales at a quarter of a trillion and over 1.3 million employees,Wal-Mart has been the biggest retailing success ever before.A lot of Wal-Mart’s success was attributed to the strong and pervasive culture at the company.China’s retailing industry should really learn something about corporate culture-building from this excellent enterprise,so that one day it would become a strong competitor both home and abroad in retailing industry.

Sustainable Development and Transition of Traditional Retailing Centers in Beijing from Consumers' Perspective

Based on the consumer questionnaires of the three traditional retailing centers,Qianmen,Wangfujing and Xidan in Beijing,this article analyzes the present features of consumer composition in the three retailing centers.What is more,the evolution course and function transition of traditional retailing centers is revealed based on the changing of consumer composition in different times.Lastly,the renewal method and development trends of traditional retailing centers are discussed based on the evaluation results in consumers'perspective.

Development of Intelligent Garment Coordination and Virtual Try-on System for Fashion Retailing with RFID Technology

Improving customer experience has become a more and more important role in enhancing customer service in fashion retailing business. In this study, a kind of intelligent garment coordination and try-on system for fashion retailing was proposed. Radio Frequency Identification （RFID） technology was used to identify customer and garment item automatically. The intelligent procedure for garment coordination recommendation using Artificial Neural Network （ANN） was developed to imitate fashion designers＇ decision-making on garment coordination. Virtual try-on algorithm based on the customer＇s 2D/mago was accomplished using imagewarping technique. The system architecture and the software framework were also described. The results show that the ＇system is a practical and useful application for fashion retailers.

The Role of New Retailing Formats in the Italian Local Development

In Italy, and particularly in its southern area, super-markets and hyper-markets still represent an expanding retailing format, as they were introduced years later than in other western countries. Today, they have become large retailers capable of influencing local development from an economic, social and urban perspective. The literature concerned with their effects on the local economy has focused on labour markets, price dynamics, and inter-type competition, neglecting their impact on macroeconomic factors such as GDP, value added specific sectors--agriculture, industry and services. This study tries to contribute to fill this gap by empirically investigating associations between key characteristics of these retailers and specific macroeconomic value added factors

Share of Wallet in FMCGs Retailing:Proposing a Conceptual Model

Recent years,the Marketing Science Institute considered marketing performance measurement(MPM)a priority in marketing research and managerial practice.Several contributions on the same topic have been proposed in literature.The ability to measure the marketing performance is considered,a cognitive gap that determined a decrease of marketing relevance within firm and organizations.Based on relevant literature on retailing and an explorative case study,it will be proposed a conceptual and pragmatic model to investigate MPM for a consumer goods retailer.The model is aimed to identify antecedents of“share of purchase”,“share of wallet”,and“share of visit”.An early test of the model has been carried out on three Italian leading chains:Superò,a master franchisee of SMA Spa(owned of 27 small supermarkets under control of the French Auchan Group),Decò-Multicedi(the Group is a multi-channel company based on network of five Ad Hoc cash&carry centers,253 Decòoutlets and three Ayoka pet shops)located in Campania Region.“U2”(the outlets label of Unes Spa,Finiper Group,operating mostly in northern Italy,with a chain of more than 190 direct and franchise supermarkets).

Assessment of Beef Quality Determinants in the Retailing Premises

This study explains how infrastructure and beef processing practices in beef retailing premises (BRPs) are useful for beef purchasing decision. In this respect, features and beef retailing practices were assessed against the questionability of beef that is retailed in least developing countries (LDCs). This assessment was carried out by testing the null hypothesis that hypothesizes that BRPs in Dar es Salaam and Mbeya cities do not comply with the FAO technical requirements. The retailed beef in many BRPs is compromised with the status of the infrastructural development, the situation that may result in the questionability of the consumed beef. The Likert based information regarding 22 beef quality impacting factors (BQIF) from BRPs in Dar es Salaam and Mbeya, respectively, was analyzed with respect to the gaps identified and beef retailing conceptual model. This study is important as it provides general picture in connection to the status of the assessed BQIF in BRPs for the cities in the least developing countries (LDCs). In this regard, the study has shown that the compliance of BRPs in the LDCs’ cities is too weak to meet the infrastructural technical requirements due to existence of more stringent provisions in the developed specifications. The study finally identified the local infrastructural beef quality determinants in LDCs’ BRPs as the gap to be bridged by other studies.

A Two-Level Purchase Problem for Food Retailing in Japan

In this paper, we deal with a purchase problem for food retailing, and formulate a two-level linear programming problem with a food retailer and a distributer. The food retailer deals with vegetables and fruits which are purchased from the distributer;the distributer buys vegetables and fruits ordered from the food retailer at the central wholesale markets in several cities, and transports them by truck from each of the central wholesaler markets to the food retailer’s storehouse. We solve the two-level linear programming problem in which the profits of the food retailer and the distributer are maximized.

Why and how retailing companies in China should operate in low-carbon mode?

Nowadays low-carbon development has become a hot issue of the whole world.This article first introduces the background of low-carbon economy,and then explains the importance of retailing companies in social economy and the reasons why they should operate in low-carbon mode.More specifically,low-carbon operation can not only improve the competitiveness of a retailing company by reducing operation cost and formatting good corporate image,but also benefit the whole society by reducing environment pollution and promoting low-carbon consumption and production.Only by adopting low-carbon operation pattern can retailing companies confront the fierce international competition.To illustrate the above point of view,several cases of famous western retailing companies will be analyzed in this essay.Tesco,Wal-Mart and Carrefour are all typical examples in low-carbon operation because they all have great green and sustainability initiatives.Based on the advanced experiences of the above-mentioned companies,this essay discusses the low-carbon operation ways,putting forward some valuable suggestions on this problem.From a technical perspective,retailing companies should adopt advanced technologies relating to low-carbon operation.On the other hand,management level of retailing companies should be enhanced to ensure the application effect of low-carbon technologies.Retailing companies should improve the ability of internal management to excavate the internal potential and build green supply chain to corporate with strategic partners.Finally,this article gives the conclusion of the whole analysis.

Clothing Sales Forecast Considering Weather Information: An Empirical Study in Brick-and-Mortar Stores by Machine-Learning

Reliable sales forecasts are important to the garment industry. In recent years, the global climate is warming, the weather changes frequently, and clothing sales are affected by weather fluctuations. The purpose of this study is to investigate whether weather data can improve the accuracy of product sales and to establish a corresponding clothing sales forecasting model. This model uses the basic attributes of clothing product data, historical sales data, and weather data. It is based on a random forest, XGB, and GBDT adopting a stacking strategy. We found that weather information is not useful for basic clothing sales forecasts, but it did improve the accuracy of seasonal clothing sales forecasts. The MSE of the dresses, down jackets, and shirts are reduced by 86.03%, 80.14%, and 41.49% on average. In addition, we found that the stacking strategy model outperformed the voting strategy model, with an average MSE reduction of 49.28%. Clothing managers can use this model to forecast their sales when they make sales plans based on weather information.

Review of Artificial Intelligence with Retailing Sector

This research service provides an original perspective on how artificial intelligence(AI)is making its way into the retail sector.Retail has entered a new era where ECommerce and technology bellwethers like Alibaba,Amazon,Apple,Baidu,Facebook,Google,Microsoft,and Tencent have raised consumers’expectations.AI is enabling automated decision-making with accuracy and speed,based on data analytics,coupled with selflearning abilities.The retail sector has witnessed the dramatic evolution with the rapid digitalization of communication(i.e.Internet)and;smart phones and devices.Customer is no longer the same as they became more empowered by smart devices which has entirely prevailed their expectation,habits,style of shopping and investigating the shops.This article outlines the Significant innovation done in retails which helped them to evolve such as Artificial Intelligence(AI),Big data and Internet of Things(IoT),Chatbots,Robots.This article further also discusses the ideology of various author on how AI become more profitable and a close asset to customers and retailers.

The Interrelationship between Culture and Capital Structure:Evidence from International Retailers

The present study investigates the influence of cultural factors in 2022 on the capital structure of global retailers.There are sixteen retailers from eight countries in the sample.In recent times,numerous academicians have taken an interest in examining the capital structure and business model of retailers,owing to their swift and consistent growth.However,the fact that the majority of research originates from the retailers’host country gives rise to debate regarding the applicability of the capital structure of said retailers to countries with distinct cultural environments.Consequently,academics have begun to investigate whether the capital structure of multinational retailers is impacted by the diversity of national cultures.

What Slowdown?

China remains a key source of growth and profits for many multinationals In March,Apple opened its largest retail store on the Chinese mainland in Shanghai-the company’s second-largest flagship store after its Fifth Avenue outlet in New York.The new addition brings Apple’s store tally in Shanghai and the Chinese market to eight and 57,respectively,a significant milestone for the company,which opened its first store in China in 2008.

EVENTS CALENDAR

China Sees Rising Retail Sales in Q1 China’s retail sales of consumer goods,a major indicator of the country’s consumption strength,climbed 4.7 percent year on year in the first quarter of 2024.The figure was slightly lower than the 5.5 percent rise registered during the January-February period,according to data from the National Bureau of Statistics(NBS).

我国某城市市售食品中PCDD/Fs污染水平和人群二噁英膳食暴露量研究

The status of PCDDs and PCDFs content in retail foods from a certain area by Isotope Dilution HRGC-HRMS was surveyed and the local population PCDD/Fs exposure from diverse foods and health risk was evaluated.PCDD/Fs was extracted from samples by Soxhlet extraction,concentrated and purified by FMS column chromatograph,carbon column enrichment.Confirmation and quantitative analysis at pg/g level of PCDD/Fs was performed by HRGC/HRMS using multiple ion detection mode(MID).TEQ concentration was calculated by WHO-TEF multiplying by concentration of seventeen PCDD/Fs congener.Median of PCDD/Fs concentration for fish,livestock,poultry,egg,vegetable oil,milk,vegetable totally 100 samples for ten diverse foods didn’t exceed the limit standards by EU.The level of PCDD/Fs for different food in the certain area was lower or comparable to the data reported by developed country in the world.The total weekly intake and monthly intake for local population or national population was 3.44,14.8 WHO-TEQ/kg BW and 1.5,6.42 pg WHO-TEQ/kg BW respectively,the value was lower than the Tolerable Weekly Intake of 14 pg WHO TEQ/kg BW for PCDDs,PCDFs and dioxin-like PCBs established by EU Scientific Committee for Food.The dietary PCDD/Fs intake for local people was higher than national population.And animal food was the dominant contributor to the total dietary intake,which accounted for more than 70 percent.These levels of consumption of diverse food containing typical levels of PCDD/Fs doesn’t present a risk to the health of the local population.But integrative dietary intake could be evaluated including of PCBs intake for population in the future.

Genotypic Characterization of Methicillin-resistant Staphylococcus aureus Isolated from Pigs and Retail Foods in China

Objective To investigate the genotypic diversity of Methicillin-resistant Staphylococcus aureus （MRSA） isolated from pigs and retail foods from different geographical areas in China and further to study the routes and rates of transmission of this pathogen from animals to food. Methods Seventy-one MRSA isolates were obtained from pigs and retail foods and then characterized by multi-locus sequencing typing （MLST）, spa typing, multiple-locus variable number of tandem repeat analysis （MLVA）, pulsed-field gel electrophoresis （PFGE）, and antimicrobial susceptibility testing. Results All isolated MRSA exhibited multi-drug resistance （MDR）. Greater diversity was found in food-associated MRSA （7 STs, 8 spa types, and 10 MLVA patterns） compared to pig-associated MRSA （3 STs, 1 spa type, and 6 MLVA patterns）. PFGE patterns were more diverse for pig-associated MRSA than those of food-associated isolates （40 vs. 11 pulse types）. Among the pig-associated isolates, CC9-ST9-t899-MC2236 was the most prevalent clone （96.4%）, and CC9-ST9-t437-MC621 （20.0%） was the predominant clone among the food-associated isolates. The CC9-ST9 isolates showed significantly higher antimicrobial resistance than other clones. Interestingly, CC398-ST398-t034 clone was identified from both pig- and food-associated isolates. Of note, some community- and hospital-associated MRSA strains （t030, t172, t1244, and t4549） were also identified as food-associated isolates. Conclusion CC9-ST9-t899-MC2236-MDR was the most predominant clone in pigs, but significant genetic diversity was observed in food-associated MRSA. Our results demonstrate the great need for improved surveillance of MRSA in livestock and food and effective prevention strategies to limit MDR-MRSA infections in China.

The impact of FinTech start-ups on incumbent retail banks’share prices

Background:This study aims to clarify the role of FinTech digital banking start-ups in the financial industry.We examine the impact of the funding of such start-ups on the stock returns of 47 incumbent US retail banks for 2010 to 2016.Methods:To capture the importance of FinTech start-ups,we use data on both the dollar-volume of funding and number of deals.We relate these to the stock returns with panel data regression methods.Results:Our results indicate a positive relationship exists between the growth in FinTech funding or deals and the contemporaneous stock returns of incumbent retail banks.Conclusions:Although these results suggest complementarity between FinTech and traditional banking,we note that our results at the banking industry level are not statistically significant,and that the coefficient signs for about one-third of the banks are negative,but not statistically significant.Since the FinTech industry is young and our sample period short,we cannot rule out that our findings are spurious.

Impact of Shipping Distance on Online Retailers' Sales:A Case Study of Maiyang on Tmall

Many studies have qualitatively explained that information and communication technology(ICT) has loosened the restrictions of distance and space on retailers' sales. Few empirical studies, however, have explored the impact of shipping distance on online retailers' sales. This study examined the Maiyang(M-Y) store on Tmall in China as a case study to investigate the relationship between shipping distance and sales. The results showed that sales volume in 2014 at the county level did not strictly obey the distance decay law. The shipped distance of high-priced commodities may not be much longer than that of low-priced commodities. Within the scope of investigation, the relationships between income, cost, and net profit curves do not follow central place theory. Goods have neither thresholds nor ranges. The key factor in the spatial discrepancy of sales is the size of market. The impact of shipping distance on sales is not as strong as that of traditional retailers in Information Era.

Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network

This paper establishes a short-term prediction model of weekly retail prices for eggs based on chaotic neural network with the weekly retail prices of eggs from January 2008 to December 2012 in China.In the process of determining the structure of the chaotic neural network,the number of input layer nodes of the network is calculated by reconstructing phase space and computing its saturated embedding dimension,and then the number of hidden layer nodes is estimated by trial and error.Finally,this model is applied to predict the retail prices of eggs and compared with ARIMA.The result shows that the chaotic neural network has better nonlinear fitting ability and higher precision in the prediction of weekly retail price of eggs.The empirical result also shows that the chaotic neural network can be widely used in the field of short-term prediction of agricultural prices.