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.

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.

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.

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.

Decision-Making of a Single Supplier and Multiple Loss-Averse Retailers under Partial Trade Credit

Under partial trade credit,suppliers usually require retailers to pay a fraction of the purchase cost immediately when ordering and the remaining payment is deferred at the end of the sales period.Considering a supply chain consisting of a risk-neutral supplier and multiple loss-averse retailers,we develop models under partial trade credit.We analyze the optimal decisions of a supplier and retailers under decentralized decision-making.The study shows that there is a unique Nash equilibrium among the retailers,and the optimal total order quantity of retailers increases as the delayed payment ratio increases and as the degree of retailers'competition increases,but decreases with an increase in the loss aversion.Numerical studies are conducted to demonstrate the solution procedures and the effects of the parameters on decisions and profits.

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.

Properties of Nash Equilibrium Retail Prices in Contract Model with a Supplier, Multiple Retailers and Price-Dependent Demand

Recently, price contract models between suppliers and retailers, with stochastic demand have been analyzed based on well-known newsvendor problems. In Bernstein and Federgruen [6], they have analyzed a contract model with single supplier and multiples retailers and price dependent demand, where retailers compete on retail prices. Each retailer decides a number of products he procures from the supplier and his retail price to maximize his own profit. This is achieved after giving the wholesale and buy-back prices, which are determined by the supplier as the supplier’s profit is maximized. Bernstein and Federgruen have proved that the retail prices become a unique Nash equilibrium solution under weak conditions on the price dependent distribution of demand. The authors, however, have not mentioned the numerical values and proprieties on these retail prices, the number of products and their individual and overall profits. In this paper, we analyze the model numerically. We first indicate some numerical problems with respect to theorem of Nash equilibrium solutions, which Bernstein and Federgruen proved, and we show their modified results. Then, we compute numerically Nash equilibrium prices, optimal wholesale and buy-back prices for the supplier’s and retailers’ profits, and supply chain optimal retailers’ prices. We also discuss properties on relation between these values and the demand distribution.

Dual-channel fiber-optic surface plasmon resonance sensor with cascaded coaxial dual-waveguide D-type structure and microsphere structure

To address the restriction of fiber-optic surface plasmon resonance(SPR) sensors in the field of multi-sample detection, a novel dual-channel fiber-optic SPR sensor based on the cascade of coaxial dual-waveguide D-type structure and microsphere structure is proposed in this paper. The fiber sidepolishing technique converts the coaxial dual-waveguide fiber into a D-type one, and the evanescent wave in the ring core leaks, generating a D-type sensing region;the fiber optic fused ball push technology converts the coaxial dual waveguides into microspheres, and the stimulated cladding mode evanescent wave leaks, producing the microsphere sensing region. By injecting light into the coaxial dual-waveguide middle core alone, the sensor can realize single-stage sensing in the microsphere sensing area;it can also realize dual-channel sensing in the D-type sensing area and microsphere sensing area by injecting light into the ring core. The refractive index measurement ranges for the two channels are 1.333–1.365 and 1.375–1.405, respectively, with detection sensitivities of 981.56 nm/RIU and 4138 nm/RIU. The sensor combines wavelength division multiplexing and space division multiplexing technologies, presenting a novel research concept for multi-channel fiber SPR sensors.

Online Grocery Brick and Mortar Retailers.State of the Art in Italy,But Is It a Profitable Strategy?

In contemporary entrepreneurial environment based on customer retention,the growth of the Internet has pushed the most dynamic businesses to compete in the electronic market.The recent evolvement of the Internet as a new major distribution channel has obtained much attention,as the online channel calls the viability of traditional stationary retailing into question.Today,since innovation is a key factor in the Digital Age,the presence in the digital marketplace is essential for retailers,also in the food retailing.The paper aims to analyze the online commerce for food groceries and compare the evolution from 2017 to 2019.The sample represents the 99%of Italian brands of brick and mortar supermarkets and hypermarket.The first study was conducted in 2017,after two years the paper has analyzed the same sample and reported how many groceries retailers have adopted the online selling.Through the visit of every Internet site and some interviews to managers,this paper proposes the reasons why only a limited number of grocery brands sell food over Internet.Moreover,this paper calculates the cost(in Italy)to prepare the expense and satisfy the order of a customer.Characteristics of goods(freshness,perishability,cold chain warranty,etc.),expensive operations needed to prepare the delivery,the cost of delivery,and difficult reverse logistics are the main causes of low adoption of e-commerce.Online groceries retailers are concentrated around big cities in particular in the north Italy(Milan,Turin,Genoa,etc.).Expense is prepared inside the retail by the employees.Some shops use the drive-in model and only a limited number of cases deliver to home.The few cases of food e-commerce offer the delivery only in a limited area of big cities.At the end,this paper demonstrates the logistics cost(picking,packing and transport)in Italy is higher than the price of the service and this strategy isn’t profitable for companies.

Retailers Enliven Catalog Offerings Through Apps

New York Times reported on November 20 that when you browsed Anthropologie’s stores, you would feel as if you’re wandering through an artsy home, where there are sure to be closets full of eclectic outfits, bedrooms with bohemian quilts and kitchen tables with

Retailers,You Can Get Omni-Shopper’s Satisfaction!

This paper evaluates the influence that information processing routes have on omni-shopping behavior,as well as analyzing the consequences of this behavior for retailers through a cognitive-affective approach.A sample of 705 mobile phone users was used for this purpose.The results obtained using the binomial logit model in a first phase and later with an application of structural equations,reflect that omni-shoppers have a more planned purchasing behavior than those who develop a one-stop shopping behavior.They search for information in a rational and deep way,spending time and effort.As for the consequences that the omni-channel behavior has for retailers,it has been found that those omni-shoppers who experience negative emotions with the retailer,have a low perceived value of the company and their satisfaction will also be negative.

Robust dual-channel correlation algorithm for complex weak target detection with wideband radar

In the scene of wideband radar,due to the spread of target scattering points,the attitude and angle of view of the target constantly change in the process of moving.It is difficult to predict,and the actual echo of multiple scattered points is not fully matched with the transmitted signal.Therefore,it is challenging for the traditional matching filter method to achieve a complete matching effect in wideband echo detection.In addition,the energy dispersion of complex target echoes is still a problem in radar target detection under broadband conditions.Therefore,this paper proposes a wideband target detection method based on dualchannel correlation processing of range-extended targets.This method fully uses the spatial distribution characteristics of target scattering points of echo signal and the matching characteristics of the dual-channel point extension function itself.The radial accumulation of wideband target echo signal in the complex domain is realized through the adaptive correlation processing of a dual-channel echo signal.The accu-mulation effect of high matching degree is achieved to improve the detection probability and the performance of wideband detection.Finally,electromagnetic simulation experiments and measured data verify that the proposed method has the advan-tages of high signal to noise ratio(SNR)gain and high detection probability under low SNR conditions.

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.

Fake Makes Chinese Retailers Lose Millions

On April 13,the judiciary of Brazil St.Paul under the help of the local police suddenly confiscated the wholesales market of Chinese clothing,located at Street 25 of the shopping center. In all,48 Chinese dealers were seized under allegation

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.

COTTON USA Buyers Tour Brings Global Brands and Retailers to China

MEMPHIS-The COTTON USA Buyers Tour to China delivered representatives from 18 global companies-with a combined

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.