Assessing the demand for value‐based organic meats in Canada: a combined retail and household scanner‐data approach

We apply sets of weekly retail and household scanner data to estimate consumer demand of selected organic and conventional fresh beef products in the Canadian retail market. The main contribution of our study stems from the application of a two‐stage procedure that provides new and deeper insight into consumers' responses to changing retail environment and pricing for organic and conventional meat products. Combined knowledge of point‐of‐sale consumer behaviour for value‐based products, such as organic products, and distinct socio‐demographic profiles of buyers vs. non‐buyers of meat is especially interesting for retail managers and meat industry stakeholders. First, household meat consumption patterns are investigated based on household scanner data that track household's meat purchases in the period 2006–2007. The second step of analysis then involves the estimation of an almost ideal demand system for selected organic and conventional fresh beef products using retail scanner data for the period 2000–2007. The introduction of greater selections in organic product lines across mainstream supermarkets in Canada in response to consumer health concerns is expected to spur retail competition in an otherwise saturated Canadian retail market. The analysis of socio‐demographic profiles in beef consumption using individual household's purchase data reveals that besides regional differences in preferences, household size and resource characteristics are major determinants of point‐of‐sale beef purchase decisions. Our demand system results indicate that organic beef is highly dependent on price and expenditures, whereas demand for conventional beef is mostly driven by income, habits and ‘typical’ Canadian seasonal beef consumption patterns. Altogether, our conclusions on organic beef vs. conventional beef buyers may have further implications for institutional regulations.     

A New Application of RFM Clustering for Guild Segmentation to Mine the Pattern of Using Banks’ e-Payment Services

ABSTRACT

With increasing use of point of sale terminals at stores, banks are seeking to achieve a bigger portion in such financial exchanges. An important problem for banks is to identify the most profitable professions. For this purpose, a new application using recency, frequency, and monetary (RFM)-based clustering and customer lifetime value analysis containing two extensions of RFM is proposed for guild segmentation. The methodology is applied on a real data from an Iranian state bank. The findings reveal that this methodology is applicable in practice and could be very effective for bank managers of any other banks.     

Analysis of the promotion of cigarettes at the point of sale and its attractiveness to children

Smoking habit seriously affects public health in a number of direct and indirect ways. The study reported here took place in Brazil and examined the promotional activities of the tobacco industry at the point of sale, with particular reference to their impact on children. Tobacco control policies are generally in place in developed countries, and smokers typically develop the habit while still young. Trained researchers visited a stratified sample of 429 retail outlets in the city of São Paulo, comprising the local equivalents of bars, snack bars, luncheonettes and pubs. Data for analysis were collected by direct observation at the point of sale and interviews with the person deemed to be in charge of the outlet visited. The results indicate that the tobacco industry is displaying its products within full view of children and making use of the sales' incentives offered to the retailer. The findings contribute significantly to the study of the effect of promotion at the point of sale on young smokers and can inform the policy debate on the increasing regulation of tobacco marketing promotional methods.     

“No sale” items in auctions: do they really matter?

Research interest in auctions has grown steadily in nearly every business discipline because of the distinctive constructs and processes that the data analyses yield. Auction data present researchers with a particular challenge because of the presence of no sale items. Researchers have varied in their accommodation of no sale items and the analysis technique, which may lead to biases in the analyses. The first question is how should no sale items be treated? To address this, the type of data generated by auctions must be examined, since various methods handle no sale items differently. Additional questions are: What analysis technique is preferred for this type of data? What is the effect of using other analysis techniques? The results suggest that including no sale items improves estimation accuracy. Also, we found that using ordinary least squares with censored data provides results that are much better than using truncated data.     

An empirical investigation and comparison of neural networks and regression for scanner data analysis

The objective of this study is to examine neural networks as an alternative to traditional statistical methods for the analysis of scanner data. The results of the study showed that neural networks can be an effective alternative to regression for modeling and predicting the effects of retailer activity on brand sales. The neural network models exhibited better performance in terms of both mean squared error and R² than the regression model.     

Integrating Web-based e-commerce applications with business application systems

The World Wide Web has become an environment for distributed applications of all kinds. The originally intended use of the Web as distributed system for knowledge-interchange seems to disappear, compared to the increasing number of electronic commerce Web applications. Organizations offer products and services in the Web, and use the Web as a means to integrate their (heterogeneous) business application systems. Offering Web-based products requires combining services of different application systems, which were built on the coarse-grained Web implementation model. Reusing the respective fine-grained services and application systems respectively integrating these cross-platform application systems increases quality and reduces costs of the new product. However, communication between (legacy) business application systems has to be ensured on an abstract level to realize this scenario. The Web as a global point of sale seems to be very promising but obviously suffers from its heritage – the coarse-grained implementation model. We introduce a generic integration layer that uses an object-oriented approach as well as the WebComposition Markup Language to facilitate the reuse of code and design, and show how inter-application communication can be provided by means of an additional basic integration layer. This revised version was published online in August 2006 with corrections to the Cover Date.     

Entertainment in retailing: The influences of advanced technologies

In recent years, the importance of an enjoyable experience during the shopping activity increased. As a consequence, many researchers are focusing on the best application of enjoyable elements in the points of sale in order to maintain existing consumers and attract new ones.The aim of this paper is to analyze how the introduction of advanced technologies modifies the retailing context and affects consumers shopping experience. In particular, three aspects of our results emerge from a theoretical standpoint: new advantages for retailers (the possibility to achieve fast information on consumer behavior and preferences); the improvement of the point of sale; and the positive influences on consumers shopping experience.     

复杂轨迹合成孔径雷达后向投影算法图像流GPU成像

相对于基于傅里叶变换的频域成像算法,后向投影(BP)算法因采用时域逐点相干积累,更适合于复杂轨迹合成孔径雷达(SAR)高精度成像。但BP算法计算量巨大,限制了其应用于SAR大场景大数据量快速成像。图形处理器(GPU)具有强大浮点运算和并行处理能力,为大场景BP算法快速成像实现提供了途径。结合GPU并行处理,提出了一种基于图像流的复杂运动SAR大场景BP快速成像处理方法。该方法借助BP算法中图像像素点相互独立处理的特性,采用图像像素点并行及图像流程处理,设计了孔径与图像缓存调度方案,提高SAR大场景大数据BP算法成像效率。仿真和机载实测数据结果验证了方法的有效性,在有限GPU显存条件下实现了8 192×8 192大场景快速成像,并且成像加速比相对于传统CPU单线程处理可达300倍以上。     

基于自相似网络通信量非参数预测的多媒体实时传输

首先讨论了自相似网络通信量预测对于网络性能分析和网络资源利用率提高的重要意义，然后利用改进的Wiener-Kolmogorov方法来进行自相似网络通信量的非参数预测，最后研究了该预测方法在多媒体实时传输中的应用。     

网络零售的商品特性适合度浅析

电子商务和传统商务在本质属性上并没有什么不同,但加入了网络这种新型的生产工具后,电子商务与传统商务又在某些方面产生了差异。对在传统商务条件下盈利的产品,如果是简单的、不加选择的移植到网络中进行销售,是有一定风险的,所以,对什么商品可以在网上成功销售,选择出适合于网络零售的产品,就很有必要。本文将从网络零售的商品特性进行分析。     

长城汽车出口俄罗斯整体战略研究

文章对俄罗斯汽车市场和汽车工业做了调查分析,对长城汽车公司在俄罗斯的发展轨迹进行了剖析,并对如何提高长城汽车在俄罗斯市场的品牌竞争力,更好适应俄罗斯市场的消费需求,完善营销网络建设和售后服务体系,促进中俄两国汽车市场共建共赢提出了可操作性对策。     

Technology acceptance modeling of augmented reality at the point of sale: Can surveys be replaced by an analysis of online reviews?

Online reviews by users have become an increasingly important source of information. This is true not only for new users of goods or services, but also for their producers. They extend the insight into the acceptance of new goods and services, e.g. at the point of sale, from a mere sales and usage quantity oriented point of view to a cause and effect oriented one. Since online reviews by consumers of many goods and services are nowadays widespread and easily available on the internet, the question arises whether their analysis can replace the more traditional approaches to measure technology acceptance, e.g., using questionnaires with TAM (Technology Acceptance Model) items. This paper tries to answer this question using IKEA׳s mobile catalogue app as an example. For comparisons reasons, data on the acceptance of the current version of this catalogue is collected in four different ways, (1) as answers to batteries of TAM items, (2) as assignments to pre-defined adjective pairs, (3) as textual likes and dislikes of users (simulating online reviews), and (4) as publicly available (real) reviews by users. The source for (1)–(3) is a survey with a sample of respondents, the source for (4) an online forum. The data is analyzed using partial least squares (PLS) for TAM modeling and text mining for pre-processing the textual data. The results are promising: it seems that data collection via surveys can be replaced – with some reservations – by the analysis of publicly available (real) online reviews.     

基于决策树的数据挖掘方法在CRM中的应用研究

基于ID3算法的CRM数据分类实例证明:决策树的核心问题是选择最佳的划分标准,采取数据挖掘中的决策树分类算法,将其应用于CRM系统中,以从中发现企业产品的销售规律和客户群特征,从而提高CRM对市场活动和销售活动的分析能力,以期为企业更科学、更有效地制定产品开发、生产、销售和服务策略提供有力的技术支持。     

太阳能无线传感器网络节点传输功率策略优化

针对配备太阳能采集设备的无线传感器网络节点，以如何合理使用采集到的能量使得时间期限内点对点传输的数据量最大为优化目的，结合必要的约束条件（能量获取电池只有有限的能量存储能力以及能量因果关系），建立了数据传输的能量通道优化模型，通过能量通道策略优化算法得到了最优传输功率策略。与当前普遍使用的能量即到即用方法进行了性能对比，仿真发现系统累积传输了更多的数据量，性能提升明显。在此基础上，考虑了实际太阳能获取量与预测值的偏差，提出了改进的能量通道算法，使得其更加适应于实际场景中。     

Application of hedonic price modeling to consumer packaged goods using store scanner data

This paper contributes to the marketing research literature by proposing an application of hedonic modeling to consumer packaged goods using store scanner data. While other studies have applied hedonic price modeling to CPG, the interpretation of their results might have been flawed. This paper, by proposing an extension of the traditional approach to account for sales quantity, makes the hedonic modeling results based on CPG scanner data acquire their intended interpretation. Hedonic modeling provides an additional alternative in the toolkit of the applied marketing researcher to assist revealing markets' relative preferences. To illustrate the use of hedonic modeling in CPG, the paper focuses on Premium Carbonated Soft Drinks. It uses a full year of weekly store scanner data from grocery stores sampled across the U.S.     

How Retailers Determine Which Products Should Go on Sale: Evidence From Store-Level Data

Recent theoretical research on retail pricing dynamics provides an explanation of why retailers periodically put items on sale, even when their costs are unchanged. The authors extend this research to show that more popular items (i.e., those that appeal to a wide range of consumers) are more likely to go on sale. One implication of the proposed model is that a good is more likely to be on sale when demand for the good is at its season peak (e.g., eggs at Easter). This implication is tested using store-level retail price data, and the prediction is borne out for the categories of goods that are examined. Additional tests also support the premise that popularity and frequency of sales are positively related.     

Measuring the shopper's attitude toward the point of sale display: Scale development and validation

In Europe alone, marketers invest several hundred million of Euros in marketing activities at the point of sale every year. A prominent role is assigned to display promotions. However, despite their large practical importance, surprisingly, there is no measure to pre-evaluate different displays and their design facets so that the display which reached the best pre-evaluation results may be identified and, if poor rated facets were found, those may be altered before production and rollout of the display in question. Therefore, this paper develops and validates a scale to measure the shopper's attitude toward a point of sale display reflecting all relevant facets of a display from the shopper's point of view. Examination of the scale led to satisfactory results in terms of reliability, validity, and its predictive power for purchase intention. Summarizing, the scale can help to improve display designs prior to rollout, thus, enhancing the efficiency of display promotions.     

An exploratory study of determinants for restaurant servers’ actual tip earnings: Individual characteristics and work conditions

This exploratory study investigates two different types of determinants for servers’ actual tip earnings (individual characteristics versus work conditions) using readily available organizational data. Unlike previous studies that measured servers’ tips by asking subjects (servers or customers) to report tip amounts, we measure the actual tip earnings of each server extracted from the point of sale system. The results show that work conditions (daily work hours, weekend work hours, and immediate supervisors’ characteristics) have stronger relationships with servers’ tip earnings than servers’ individual characteristics (gender, tenure, and job satisfaction). This study represents an initial attempt to use objective data to measure servers’ tip earnings and explore its potential relationship with work conditions compared to its relationships with individual characteristics which have been frequently examined in previous studies.     

Why do customers use self-service information technologies in retail? The mediating effect of perceived service quality

To ensure a high level of service quality (SQ), retailers think about offering self-service information technologies (SSIT) at the point of sale. However, the explanatory value of the SQ for SSIT adoption is barely researched. Thus, the present study examines the mediation effect of SQ within the technology acceptance model. Building on data from a laboratory experiment using a fully functional application for Tablet PCs, the partial least squares approach is applied. The findings reveal that the perceived SQ partially mediates the effect of the attitude towards using on the intention to reuse. Therefore, retailers have to emphasize the service-related value of SSITs.     

基于J2ME和PHP技术的移动计算应用解决方案

对以蜂窝网作为承栽网络的移动计算应用平台进行了分析，针对现有J2ME开发平台的复杂性，提出了一种以PHP／PHP JSP作为中间件的完整、高效及便于开发的应用解决方案，同时对相关的技术难点尤其是缓存技术进行了探讨，给出了典型算法。最后给出了一个应用实例——个人健康顾问系统。