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.

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.

Customer Segment Prediction on Retail Transactional Data Using K-Means and Markov Model

Retailing is a dynamic business domain where commodities and goods are sold in small quantities directly to the customers.It deals with the end user customers of a supply-chain network and therefore has to accommodate the needs and desires of a large group of customers over varied utilities.The volume and volatility of the business makes it one of the prospectivefields for analytical study and data modeling.This is also why customer segmentation drives a key role in multiple retail business decisions such as marketing budgeting,customer targeting,customized offers,value proposition etc.The segmentation could be on various aspects such as demographics,historic behavior or preferences based on the use cases.In this paper,historic retail transactional data is used to segment the custo-mers using K-Means clustering and the results are utilized to arrive at a transition matrix which is used to predict the cluster movements over the time period using Markov Model algorithm.This helps in calculating the futuristic value a segment or a customer brings to the business.Strategic marketing designs and budgeting can be implemented using these results.The study is specifically useful for large scale marketing in domains such as e-commerce,insurance or retailers to segment,profile and measure the customer lifecycle value over a short period of time.

Optimization of Electricity Purchase and Sales Strategies of Electricity Retailers under the Condition of Limited Clean Energy Consumption

In the process of my country’s energy transition,the clean energy of hydropower,wind power and photovoltaic power generation has ushered in great development,but due to the randomness and volatility of its output,it has caused a certain waste of clean energy power generation resources.Regarding the purchase and sale of electricity by electricity retailers under the condition of limited clean energy consumption,this paper establishes a quantitative model of clean energy restricted electricity fromthe perspective of power system supply and demand balance.Then it analyzes the source-charge dual uncertain factors in the electricity retailer purchasing and selling scenarios in the mid-to long-term electricity market and the day-ahead market.Through the multi-scenario analysis method,the uncertain clean energy consumption and the user’s power demand are combined to form the electricity retailer’s electricity purchase and sales scene,and the typical scene is obtained by using the hierarchical clustering algorithm.This paper establishes a electricity retailer’s risk decisionmodel for purchasing and selling electricity in themid-and long-term market and reduce-abandonment market,and takes the maximum profit expectation of the electricity retailer frompurchasing and selling electricity as the objective function.At the same time,in themediumand longterm electricity market and the day-ahead market,the electricity retailer’s purchase cost,electricity sales income,deviation assessment cost and electricity purchase and sale risk are considered.The molecular results show that electricity retailers can obtain considerable profits in the reduce-abandonment market by optimizing their own electricity purchase and sales strategies,on the premise of balancing profits and risks.

More and More Retail Brands Integrate ESG into Development

Recently, Savills and the U.S. Green Building Council released Sustainable Retail-Staying on Track(hereinafter the report), which pointed out that the ranking of the 20-city retailer index in 2022 changed the most in the past five years, but that Shanghai, Beijing, Shenzhen and Chengdu are still among the top four retailers in 2022. The sustainable retail index of coastal cities including Ningbo, Qingdao and Xiamen has greatly improved.

Assessment of the Retail Food Environment Using Integrated GIS and Modified Measures in Wuhan, China

The retail food environment (RFE) has a significant impact on people’s dietary behavior and diet-related outcomes. Although RFE research has received a lot of attention, there are very few studies that shed light on the foodscape and assessment methodologies in the China context. Based on open data obtained from Dianping.com and AutoNavi map, we classified all food outlets into six types. Geographic Information Systems (GIS) techniques were employed to create two network buffer areas (1-km and 3-km) and calculate the absolute measures and relative measures (i.e., mRFEI and Rmix). We modified the calculation of relative measures by adding items and assigning weights. The mean mRFEI using the 1-km and 3-km buffer sizes across the communities were 10.45 and 20.12, respectively, while the mean mRmix of the two buffer sizes were 20.97 and 58.04, indicating that residents in Wuhan have better access to fresh and nutritious food within 3-km network buffers. Residents in urban areas are more likely to be exposed to an unhealthy food environment than those in rural areas. Residents in Xinzhou and Qiaokou districts are more likely to be subjected to unfavorable neighborhood RFE. The open data-driven methods for assessing RFE in Wuhan, China may guide community-level food policy interventions and promote active living by shifting built environments to increase residents’ access to healthy food.

The Transformations of Retail Trade Formats in Europe at the Beginning of the 21st Century

The paper aims at identifying the transformations in trade influenced by the main macroeconomic forces of trade companies in European countries in the 21st century. The author surveys the specialist literature dealing with marketing and trade. On the basis of the research carried out, it has been established that the development of new retail formats （e.g. convenience shops, e-commerce）, which was influenced by the transformations in the macroeconomic environment of companies, was observed. At the same time, retail formats of hybrid character （e.g. discount convenience shops） have appeared and old well-known ones like department stores, supermarkets, or discount shops have strengthened their market position. The knowledge about the issues presented in the following paper has practical implications and can be helpful for managers of trade companies.

Role of 3PL in retail sector in China——Case study:Tesco and LianHua

The role of 3PL in retail sector are explored and analyzed from the view of retailing and 3PL industry. Through the use of literature, market data and other relative information, the problems on both sides are identified by revealing the current application of 3PL in retail sector and the partnership between the retailers and 3PL providers is analyzed. A case study is also introduced in order to identify the difference between west and china on successful 3PL solution for retailers and specify the key fa...

Uniformity Analysis for Index of Retail Price

Using the Hodges Ajne testing method, the uniformity of China retail price index was tested. The result, that population is submitting to uniform distribution, was obtained. The uniformity of CRPI indicates that the general price level is stable in the Ninth Five Year Plan. Finally, the reasons causing the uniformity was analyzed.

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.

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.

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.

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.

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.

Pricing decision of green supply chain under the game competition of duopolistic retailers

In order to evaluate the impact of green production introduced by the manufacturer and study the competitive strategy between two retailers,four strategic models among diverse retailers,i.e.,Cournot,Stackelberg and two cases of collusion,are constructed.The optimal decision is obtained by the game theory and numerical analysis.The results indicate that the manufacturer's marginal profitability is no less than that of the two retailers.However,due to the manufacturer's green cost,the downstream profitability of the supply chain may exceed the upstream manufacturer's profitability.The retailers'Cournot behavior causes the manufacturer to acquire the highest profitability and set the highest green level.However,there is an opposite result in collusion.Two retailers will choose Cournot pricing when the consumer's green sensitivity is higher than a threshold.When consumers are more sensitive to the price difference of products,retailers prefer collusion,and then choose the Stackelberg behavior.Manufacturers'profitability will increase as competition among retailers intensifies.Proper competition allows two duopolistic retailers to acquire a higher profitability.

Research on the Mechanism of Retail Strategy Influencing Consumer Behavior Intention——Based on Empirical Analysis of Domestic Luxury Cosmetics Brands

This is a research on the mechanism of retail strategy mix and consumer behavior intention,and psychological impact on consumer attitude, consumer purchase decision-making model and its components are conducted firstly. Next, retail strategy, merchandise strategy, and store strategy, contained in the retail management theory, are adopted as other important variables to measure the impact on consumer attitudes. And then, the key factors of retail strategy mix are identified by means of Focus Group (FG). In addition, the hypothetical model of retail strategy mix and consumer behavior intention for domestic luxury cosmetic brands is established to understand the relationship between the two factors. Finally, empirical researches are conducted on consumers and retailers of luxury cosmetics brands. And some advice are given on retail strategy mix's influence on the consumer behavior intentions, aiming to enlighten domestic luxury cosmetic enterprises to improve performance by the integrated use of retail strategy mix.

Identifying the Geography and Determinants of O2O Online Retailers in Megacity in Central China:A Case Study of Zhengzhou City

In recent years,O2O e-commerce,represented by online group-buying,has developed vigorously,which had significant impacts on urban commercial space.Zhengzhou City is a rising national central city in China,and its e-commerce development level is ahead,but relevant researches are rare.Therefore,the data of online retailers of Meituan.com was collected and combined with Baidu map and Baidu heat map data.Then,we adopted the methods such as spatial statistics and geodetector to explore the geography and determinants of O2O online retailers in Zhengzhou urban area.The main conclusions are 1)The spatial development of O2O online retailers is characterized by significant global high-value agglomeration.2)The agglomeration areas of different types of O2O online retailers are different.Most of them are concentrated in the old urban area within the Third Ring Road of Zhengzhou City,forming five comprehensive agglomeration areas.3)The areas with the high e-commerce development level are mainly concentrated in the northeast and southwest of the x-shaped region formed by the intersection of Lianyungang-Lanzhou and Beijing-Guangzhou railways.Erqi Square and Guomao 360 Plaza are at the highest development level,followed by Zhongyuan Wanda Plaza and Daxue Middle Road.The development level at other areas is relatively low.4)Zhengzhou’s O2O commercial pattern is highly dependent on physical business.The population distribution,especially the population distribution during the nightlife period,plays a vital role in its spatial development,followed by accessibility.The influences of physical distance are slightly larger than that of time cost,but the difference between them is little.In addition,travelling costs have the least impact.This paper could provide certain references for urban commercial planning.

MANAGING HUMAN RESOURCES FOR RETAIL SERVICE QUALITY

This study examines the management of service qua lity in fashion retail operation. The human resources processes leading to external service quality are consolidated into a quality management framework. With reference to the framework, the factors, their importance and relationships within each process are established by the responses of practicing salespersons. A clear picture of the underlying management mechanisms leading to strong sales forces and service quality are produced. Retail management is required to better establish and manage the human resource.

Investing and Pricing with Supply Uncertainty in Electricity Market:A General View Combining Wholesale and Retail Market

Renewable energy,such as wind and solar energy,may vary signifi cantly over time and locations depending on the weather and the climate conditions.This leads to the supply uncertainty in the electricity(power) market with renewable energy integrated to power grid.In this paper,electricity in the market is classified into two types:stablesupply electricity(SSE) and unstablesupply electricity(USE).We investigate the investment and pricing strategies under the electricity supply uncertainty in wholesale and retail electricity market.In particular,our model combines the wholesale and retail market and capture the dominant players,i.e.,consumers,power plant(power operator),and electricity supplier.To derive the market behaviors of these players,we formulate the market decision problems as a multistage Stackelberg game.By solving the game model,we obtain the optimal,with closedform,wholesale investment and retail pricing strategy for the operator.We also obtain the energy supplier's best price mechanism numerically under certain assumption.We fi nd the price of SSE being about 1.4 times higher than that of USE will benefi t energy supplieroptimally,under which power plant's optimal strategy of investing is to purchase USE about 4.5 times much more than SSE.

Retail二次物流配送系统在运输环节的应用及实践

为提高市场响应速度、扩大市场竞争优势、降低物流成本,借助信息技术对成品油物流供应链进行优化被埃克森美孚、BP、道达尔、雪佛龙等许多全球著名石油公司所采用,并在全球范围内迅速推广和使用。二次配送是成品油销售供应链中的重要环节,是经营的核心。二次配送优化,可以优化并有效降低加油站库存;建立销售预测体系并预测未来数天加油站销售量;建立油品补货模型计算不同车辆送货窗口;建立优化调度模型,优化调度运输,提高运输资源利用率,二次配送优化在运输环节意义重大。