Conference Paper

IP-Mapping a RFID-Integrated Shelf Replenishment Information System for the Retail Industry to Assess Information Quality

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Abstract

Motivated by the problem of out-of-shelf (OOS) in retail industry and the emergence of RFID (Radio Frequency Identification) technology, this paper investigates the impact that the adoption of RFID has on the quality of information utilized during the shelf replenishment process. A RFID-integrated information system (IS) with three alternative implementation scenarios is proposed to enhance the shelf replenishment process. The impact of the three alternative solutions on the quality of the IS information input and output is examined in terms of accuracy, timeliness and completeness. The quality of the IS information input and output will be assessed by developing the Information Product Maps (Ballou et al. 1998, Shankaranarayan et al. 2003) of the alternative implementations of the RFID-integrated shelf replenishment IS and utilizing the methodology introduced by the fundamental study of Ballou, Wang, Pazer and Tayi (1998). The contribution of this study is reflected on the research approach of using this methodology, not applied until now, based on the available literature.

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Increasing supply chain complexity poses new challenges to managers. On the other hand, evolving information and communication technology offers ample opportunity for more reliable supply chain management practices. Event processing has established itself in many applications in logistics. Although the topic has enjoyed increasing popularity, there is no study taking stock of prior developments and guiding future research. Therefore, a systematic literature review on the topic of event processing in supply chain management from 2005 until the present is undertaken. Extant literature is synthesized and analyzed from technological and supply chain management perspectives to inform scholars and practitioners of existing field developments. Additionally, to guide future scholarly endeavors, a research agenda is derived from promising topics raised in papers and unfulfilled practical requirements. We find that current solutions primarily focus on a limited number of supply chain core processes and a restricted number of supply chain actors. The majority of publications focused on time-temperature sensitive products. Additionally, the domination of road transportation can be observed, while other modes of transport are often ignored in solution implementations. Decision support in terms of object traceability within the supply chain is found in most articles. RFID, typically accompanied by the Electronic Product Code Information Services standard, is the dominant enabling technology. Future research should focus on the topics of standardization, granularity, data sources, and cooperation. Moreover, holistic event processing supported by big data and machine learning techniques could create interfaces with other legacy business intelligence applications. Another promising area includes the exploration of new technologies, i.e. IoT, to enable new smart solutions.
Chapter
“Technology has made our lives more full, yet at the same time we’ve become uncomfortably “full”. (Maeda, 2006, p.I). After considering these words within marketing context we can see that each day we are dealing with an information flow. Although there is a lot of information about almost everything (sold products, barcodes, invoices, information from the supplier, prices, customer data, competitors etc.) today’s managers are more unsecure to take certain decisions. They also don’t have enough time to pay attention for these controllable or uncontrollable forces. During a business process the way from production to wholesalers and than to retailers is very complicated. After products finally meet the customers, feedbacks are coming back to the companies and the cycle begins from the start. This product and information flow makes business processes very complex because different people (engineers, sales staff, consumers, managers) interfere this cycle. In this study our aim is - based on the simplicity theory of John Maeda – with the help of RFID technology to create a simple process model for retailers. By using RFID tags in their warehouses and stores they might be able to serve better and more efficiently to their customers and have a better overview in a short period of time. The information supplied via RFID allows corporations to plan their internal processes more efficiently. We also would like to analyze the pitfalls of RFID with a case from Turkish retail industry especially for In-Store usage of RFID.
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Information quality occurs along ten dimensions, is defined by the information's customer, and is constantly changing over time. IS managers must understand the dimensions and the dynamic nature of information quality to effectively use information as a product, as a component of their production processes, and as a vehicle for managerial planning and control.
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In this paper, several “disruptive” technologies are considered and the paths they have taken from the early innovation phase to full implementation are traced. The technologies include: refrigeration; the automobile and highway system; incandescent lighting; the television; and, the personal computer. Each technology is traced through several steps leading from the early innovation to wide adoption. Then the same steps are applied to RFID, placing it in this historical context and speculating on the possible future adoption and impact of this technology.
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Radio-frequency identification (RFID) as an emerging technology has generated enormous amount of interest in the supply chain arena. With RFID technology, inventory can be tracked more accurately in real time resulting in reduced processing time and labor. More significantly, the complete visibility of accurate inventory data throughout the entire supply chain, from manufacturer's shop floor to warehouses to retail stores, brings opportunities for improvement and transformation in various processes of the supply chain. We developed a simulation model to study how RFID can improve supply chain performance by modeling the impact of RFID technology in a manufacturer-retailer supply chain environment. Our study provides a quantitative analysis to demonstrate the potential benefits of RFID in inventory reduction and service level improvement.
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Poor data quality (DQ) can have substantial social and economic impacts. Although firms are improving data quality with practical approaches and tools, their improvement efforts tend to focus narrowly on accuracy. We believe that data consumers have a much broader data quality conceptualization than IS professionals realize. The purpose of this paper is to develop a framework that captures the aspects of data quality that are important to data consumers.A two-stage survey and a two-phase sorting study were conducted to develop a hierarchical framework for organizing data quality dimensions. This framework captures dimensions of data quality that are important to data consumers. Intrinsic DQ denotes that data have quality in their own right. Contextual DQ highlights the requirement that data quality must be considered within the context of the task at hand. Representational DQ and accessibility DQ emphasize the importance of the role of systems. These findings are consistent with our understanding that high-quality data should be intrinsically good, contextually appropriate for the task, clearly represented, and accessible to the data consumer.Our framework has been used effectively in industry and government. Using this framework, IS managers were able to better understand and meet their data consumers' data quality needs. The salient feature of this research study is that quality attributes of data are collected from data consumers instead of being defined theoretically or based on researchers' experience. Although exploratory, this research provides a basis for future studies that measure data quality along the dimensions of this framework.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000. Includes bibliographical references (p. 61-64). by Yogesh V. Joshi. S.M.
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Inventory inaccuracy is a main issue in businesses dealing with physical assets. The aim of this paper is to examine the relationship between inventory inaccuracy and performance in a retail supply chain. We simulate a three echelon supply chain with one product in which end-customer demand is exchanged between the echelons. In the base model, without alignment of physical inventory and information system inventory, inventory information becomes inaccurate due to low process quality, theft, and items becoming unsaleable. In a modified model, these factors that cause inventory inaccuracy are still present, but physical inventory and information system inventory are aligned at the end of each period. The results indicate that an elimination of inventory inaccuracy can reduce supply chain costs as well as the out-of-stock level. Auto-ID technologies can be one means to achieve inventory accuracy.
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To increase productivity, organizations must manage information as they manage products. The field of information quality (IQ) has experienced significant advances during its relatively brief history. Today, researchers and practitioners alike have moved beyond establishing information quality as an important field to resolving IQ problems ranging from IQ definition, measurement, analysis, and improvement to tools, methods, and processes. However, theoretically-grounded methodologies for Total Data Quality Management (TDQM) are still lacking. Based on cumulated research efforts, this article presents such a methodology for addressing these problems. The purpose of this TDQM methodology is to deliver high quality information products to information consumers. It aims to facilitate the implementation of an organization's overall data quality policy formally expressed by top management. Organizations of the 21st century must harness the full potential of their data in order to gain competitive advantage and attain strategic goals.
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This publication contains reprint articles for which IEEE does not hold copyright. Full text is not available on IEEE Xplore for these articles.
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