制造类企业实施ERP与Ecommerce的优先性分析

文中主要对目前国内制造业在实施ERP和Ecommerce的优先性这一问题进行了分析。提出在企业的实施过程中应该先进行ERP的实施,而后进行Ecommerce的实施,并对做出这个提议的原因进行了分析,以及就这种实施过程中存在的问题以及可以采取的措施进行了论述。

Impact of the COVID-19 pandemic and generational heterogeneity on ecommerce shopping styles-A case study of Sacramento,California

The COVID pandemic has accelerated the growth of ecommerce and reshaped shopping patterns,which in turn impacts trip-making and vehicle miles traveled.The objectives of this study are to define shopping styles and quantify their prevalence in the population,investigate the impact of the pandemic on shopping style transition,understand the generational heterogeneity and other factors that influence shopping styles,and comment on the potential impact of the pandemic on long-term shopping behavior.Two months after the initial shutdown(May/June 2021),we collected ecommerce behavioral data from 313 Sacramento Region households using an online survey.A K-means clustering analysis of shopping behavior across eight commodity types identified five shopping styles,including ecommerce independent,ecommerce dependent,and three mixed modes in-between.We found that the share of ecommerce independent style shifted from 55%pre-pandemic to 27%during the pandemic.Overall,30%kept the same style as pre-pandemic,54%became more ecommerce dependent,and 16%became less ecommerce dependent,with the latter group more likely to view shopping an excuse to get out.Heterogeneity was found across generations.Pre-pandemic,Millennials and Gen Z were the most ecommerce dependent,but during the pandemic they made relatively small shifts toward increased ecommerce dependency.Baby Boomers and the Silent Generation were bimodal,either sticking to in-person shopping or shifting to ecommercedependency during the pandemic.Post-pandemic intentions varied across styles,with households who primarily adopt non-food ecommerce intending to reverse back to in-person shopping,while the highly ecommerce dependent intend to limit future in-store activities.

Behavior Analysis of Bank into E-Commerce under Network Externalities

With the advent of Internet financial innovation,many commercial banks quietly have started to enter into the Ecommercial in order to prevent oligarchs from eroding financial market.From the perspective of industrial division,this paper reveals the nature of a phenomenon that E-commercial enterprises and banks have stepped into each other's field,which E-commerce of banks can give full play to network effects.Then it uses game theory to analyze the motions of banks to involve into E-commerce and the short-term competitive equilibrium of large incumbent Ecommercial enterprises as well.For individual rationality,the dominant strategy of banks and E-commercial enterprises is(enter,counterattack).Considering network externalities,it constructs a competing model on banks and incumbent E-commercial enterprises and simulates competitive trends and balanced results of their behaviors,which illustrates that banks can obtain network effect after choosing E-commerce strategy.

机电一体化培训和教育中的电子移动学习课件开发(英文)

Knowledge is essential for the competitiveness of individuals as well as organizations.Thus the application of the latest methodologies and technologies are utilized to support knowledge acquisition,warehousing,distribution,and transfer.Means and methods of web 2.0 are useful to support this procedure.Especially,highly complex and very dynamic knowledge domains have to be accessible and applicable in the framework of learning network communities,including the stakeholders of training and education.Mechatronics for example is such an interdisciplinary,dynamic field of research and application.Based on intelligence,software,and hardware it is requiring special approaches for developing a courseware based learning and knowledge transfer environment.After defining the specifics of mechatronics education and postgraduate training in the context of e-education,the concepts of the development and utilization of mechatronic courseware can be deduced from e-learning 2.0 and mobile learning facilities,possibilities,and abilities.Mechatronic courseware will be developed by using authoring software and embedding the material into learning management systems with respect to general methods and rules of modern system and software development.As an example,the courseware is used for vocational training and further education especially in cooperation networks of educational institutions and SME.

A Data Mining Based Approach to Customer Behaviour in an Electronic Settings

The understanding of customer incidents and behaviour is crucial to the success of any organization. Evidence from literature shows a prediction pattern of products to customer. These studies predicted product characteristics leaving out the customers characteristics. To address this gap, this study aims to design datamining system and implement it on an electronic commerce organization website. The customer information and history (clickstreams) from the electronic commerce website was used to predict the customers’ behaviour. This will give meaningful and usable data patterns to organizations. Python programming language was used to design the datamining system, while PHP, HTML, and JavaScript were used for the e-commerce website. A brief description of the background of e-commerce and data mining, previous work of researchers who have worked on data mining in e-commerce settings, was reviewed and the relationship between their findings and this work was established. The data mining system utilizes consensus clustering technique and the clustering algorithm with a graphical-based approach. Furthermore, the interaction between the data mining system and the customer’s dataset on an ecommerce website was defined. Quantitative evidence for determining the number and membership of possible customer behavioural clusters within the dataset was generated.

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.

Architecture of a Commercialized Search Engine Using Mobile Agents

Shopping Search Engine(SSE)implies a unique challenge for validating distinct items available online in market place.For sellers,having a user finding relevant search results on top is very difficult.Buyers tend to click on and buy from the listings which appear first.Search engine optimization devotes that goal to influence such challenges.In current shopping search platforms,lots of irrelevant items retrieved from their indices;e.g.retrieving accessories of exact items rather than retrieving the items itself,regardless the price of item were considered or not.Also,users tend to move from shoppers to another searching for appropriate items where the time is crucial for consumers.In our proposal,we exploit the drawbacks of current shopping search engines,and the main goal of this research is to combine and merge multiple search results retrieved from some highly professional shopping sellers in the commercial market.Experimental results showed that our approach is more efficient and robust for retrieving a complete list of desired and relevant items with respect to all query space.

An Intelligent Voice-Based eMarketplace for Visually Impaired People

Today eMarketplaces play a significant role in contemporary life by providing a lot of income and business opportunities to people and organizations throughout the world. Despite innovations in the field of IT, many of eMarketplaces lack the ability to provide appropriate services for people with special needs, especially the blind.? Therefore, this paper is focused on incorporating an interface for blind people to participate in the business of eMarketplaces. A proposed model of a voice-based eMarketplace has been introduced using voice recognition technology. Specific blind users of the system are uniquely identified using voice recognition technology to enable them to access the eMarketplace in a secure manner. Further work of this project involves building such as module on an existing eMarketplace.

Helping consumers to overcome information overload with a diversified online review subset

Redundant online reviews often have a negative impact on the efficiency of consumers' decisi on-making in their on line shopping.A feasible solution for business analytics is to select a review subset from the original review corpus for consumers,which is called review selection.This study aims to address the diversified review selection problem,and proposes an effective review selection approach called Simulated Annealing-Diversified Review Selection(SA-DRS)that considers the semantic relationship of review features and the con tent diversity of selected reviews simultaneously.SA-DRS first constructs a feature taxonomy by utilizing the Latent Dirichlet Allocation(LDA)topic model and the Word2vec model to measure the topic relation and word context relation.Based on the established feature taxonomy,the similarity between each pair of reviews is defined and the review quality is estimated as well.Fin ally,diversified,high-quality reviews are selected heuristically by SA-DRS in the spirit of the simulated annealing method,forming the selected review subset.Extensive experiments are conducted on real-world e-commerce platforms to demonstrate the effectiveness of SA-DRS compared to other extant review selection approaches.