DATA MINING: A SEGMENTATION ANALYSIS OF U.S. GROCERY SHOPPERS

Consumers make choices about where to shop based on their preferences for a shopping environment and experience as well as the selection of products at a particular store. This study illustrates how retail firms and marketing analysts can utilize data mining techniques to better understand customer profiles and behavior. Among the key areas where data mining can produce new knowledge is the segmentation of customer data bases according to demographics, buying patterns, geographics, attitudes, and other variables. This paper builds profiles of grocery shoppers based on their preferences for 33 retail grocery store characteristics. The data are from a representative, nationwide sample of 900 supermarket shoppers collected in 1999. Six customer profiles are found to exist, including (1) "Time Pressed Meat Eaters", (2) "Back to Nature Shoppers", (3) "Discriminating Leisure Shoppers", (4) "No Nonsense Shoppers", (5) "The One Stop Socialites", and (6) "Middle of the Road Shoppers". Each of the customer profiles is described with respect to the underlying demographics and income. Consumer shopping segments cut across most demographic groups but are somewhat correlated with income. Hierarchical lists of preferences reveal that low price is not among the top five most important store characteristics. Experience and preferences for internet shopping shows that of the 44% who have access to the internet, only 3% had used it to order food.Consumer/Household Economics, Food Consumption/Nutrition/Food Safety,

DSS (Decision Support Systems) in Indian Organised Retail Sector

Indian organised retail industry is poised for growth. Rapid state of change due to speedy technological developments, changing competitive positions, varying consumer behaviour as well as their expectations and liberalized regulatory environment is being observed in organized retailing. Information is crucial to plan and control profitable retail businesses and it can be an important source of competitive advantage so long as it is affordable and readily available. DSS (Decision Support Systems) which provide timely and accurate information can be viewed as an integrated entity providing management with the tools and information to assist their decision making. The study, exploratory in nature plans to adopt a case study approach to understand practices of organized retailers in grocery sector regarding applications of various DSS tools. Conceptual overview of DSS is undertaken by reviewing the literature. The study attempts to describe practices and usage of DSS in operational decisions in grocery sector and managerial issues in design and implementation of DSS. Comparision across national chain and local organized retailer in grocery sector reveals that national chain having implemented ERP partially are mostly using the same for majority of operational decisions like inventory management, CRM, campaign management. Two local players use spread sheets and in house software to make the above operational decisions. The benefits realized remain the same across the retailers. Prioritization as well as quantification of benefits was not communicated. The issues of coordination, integration with other systems in case of ERP usage, training were highlighted. Future outlook of DSS by the respondents portrayed a promising picture.

An Exploratory Study of RFID Implementation in the Supply Chain

The purpose of this paper is to investigate the barriers and motivations for adopting radio frequency identification (RFID), the level of RFID implementation, the processes RFID is utilized in, and issues in the deployment of RFID. A survey instrument was developed based on a literature review. The survey was then distributed to the members of the Association for Operations Management Rhode Island and Boston chapters. The results were then analyzed. It was found that the majority of the surveyed firms are not considering RFID implementation. Lack of a business case and lack of understanding were cited as their main concerns. For firms considering RFID implementation and firms that had implemented RFID, better inventory management, obtaining competitive advantage, and cost reduction were the three most important motivations for adopting RFID. Financial concerns and the lack of a business case were the most prevalent issues. In addition, product tracking (pallets, cases, and items) in shipping was the most cited RFID application. It was also found that considering firms are facing less pressure from customers to adopt RFID and reported a much higher degree of apprehension regarding potential issues than implementing firms reported for actual difficulties faced. One of the limitations is the small sample size (n = 49) which may limit the generalizability of the results. By identifying barriers, motivations, and issues in the implementation of RFID, this study further educates practitioners on the challenges and opportunities of RFID, as well as providing direction to academicians for further research on this area

Indian Organised Apparel Retail Sector and DSS (Decision Support Systems)

Indian apparel retail sector poses interesting challenges to a manager as it is evolving and closely linked to fashions. Appealing mainly to youth, the sector has typical information requirements to manage its operations. DSS (Decision Support Systems) provide timely and accurate information & it can be viewed as an integrated entity providing management with the tools and information to assist their decision making. The study exploratory in nature, adopts a case study approach to understand practices of organized retailers in apparel sector regarding applications of various DSS tools. Conceptual overview of DSS is undertaken by reviewing the literature. The study describes practices and usage of DSS in operational decisions in apparel sector and managerial issues in design and implementation of DSS. A multi brand local chain and multi brand national chain of apparel was chosen for the study. Varied tools were found to be used by them. It was also found that for sales forecasting and visual merchandising decisions, prior experience rather than any DSS tool was used. The benefits realized were; “help as diagnostic tool”, “accuracy of records and in billing”, “smooth operations”. The implementation issues highlighted by the store managers were; more initial teething problems rather than resistance on the part of employees of the store, need for investment of time & money in training, due to rapid technological advancements, time to time updation in DSS tools is required . Majority of operational decisions like inventory management, CRM, campaign management were handled by ERP (Enterprise Resource Planning) or POS (Point of Sale). Prioritization as well as quantification of benefits was not attempted. The issues of coordination, integration with other systems in case of ERP usage, training were highlighted. Future outlook of DSS seems bright as apparel retailers are keen to invest in technology.

Social media analytics: a survey of techniques, tools and platforms

This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing

Association Rules in Data Mining: An Application on a Clothing and Accessory Specialty Store

Retailers provide important functions that increase the value of the products and services they sell to consumers. Retailers value creating functions are providing assortment of products and services: breaking bulk, holding inventory, and providing services. For a long time, retail store managers have been interested in learning about within and cross-category purchase behavior of their customers, since valuable insights for designing marketing and/or targeted cross-selling programs can be derived. Especially, parallel to the development of information processing and communication technologies, it has become possible to transfer customers shopping information into databases with the help of barcode technology. Data mining is the technique presenting significant and useful information using of lots of data. Association rule mining is realized by using market basket analysis to discover relationships among items purchased by customers in transaction databases. In this study, association rules were estimated by using market basket analysis and taking support, confidence and lift measures into consideration. In the process of analysis, by using of data belonging to the year of 2012 from a clothing and accessory specialty store operating in the province of Osmaniye, a set of data related to 42.390 sales transactions including 9.000 different product kinds in 35 different product categories (SKU) were used. Analyses were carried out with the help of SPSS Clementine packet program and hence 25.470 rules were determined

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Analytical customer relationship management in retailing supported by data mining techniques

Tese de doutoramento. Engenharia Industrial e Gestão. Faculdade de Engenharia. Universidade do Porto. 201

Integrating Kano’s Model and SERVQUAL to Improve Healthcare Service Quality

The purpose of this research is focus on customer relationship management (CRM) strategies and relationship between service attributes and customer satisfaction through Kano’s model especially on healthcare service at the private hospital. The paper specifically investigates the applicability of the model and the key factors in the hospital service business. The hospital service quality much depends on the performance of the attributes that define a service. The aim of this paper is first to investigate the attribute of service quality using Servqual perspective, thus the management is able to adjust the relationship between performance of service attributes and customer satisfaction, and second, through a case study in the private hospital to prove that the importance of a service attribute is a function of the performance of that attribute. An empirical study using questionnaires with a focus on service enquiring about the performance of service key attributes and overall customer satisfaction was conducted using Servqual perspective including 5 parameters i.e. Tangibles, Reliability, Responsiveness, Assurance, Empathy. The data were fed into the Kano customer satisfaction model which used Five-level Kano questionnaire for analysis and comparison between one attribute to the others. This research found that there are three of the total 26 service quality attributes have been categorized as “attractive”. Four service quality attributes have been categorized as “must be”, and sixteen of them as “one-dimensional”. However, there is no service quality attribute can be categorized as “reverse” and “questionable”. It can be predicted that offering customers “must be” or expected quality attributes will not be enough for customer satisfaction in few next days cause of the contemporary world and the environment changing. Hence, companies should focus on “attractive” quality attributes instead of “must be” or “one-dimensional” attributes in order to satisfy customers and to achieve competitive advantage. The research limitations is the Kano model of customer satisfaction needs to be extended to other customer behavior variables and also management strategic response to increase customer loyalty; which not include in this paper. The implication is the methodology employed here can be easily applied by hospital management to evaluate customer behaviors and service quality performance