In a supply chain, a warehouse is a crucial component for linking all chain parties. Automatic identification and data capture (auto-ID) technology, e.g. RFID and barcodes are among the essential ...technologies in the 21st century knowledge-based economy. Selecting an auto-ID technology is a long term investment and it contributes to improving operational efficiency, achieving cost savings and creating opportunities for higher revenues. The interest in auto-ID research for warehouse management is rather stagnant and relatively small in comparison to other research domains such as transport, logistics and supply chain. However, although there are some previous studies that explored factors for the auto-ID selection decision in a warehouse environment, those factors (e.g., operational factors) have been examined separately and researchers have paid no attention to all key factors that may potentially affect this decision. In fact, yet there is no comprehensive framework in the literature that comprehensively investigates the critical factors influencing the auto-ID selection decision and how the factors should be combined to produce a successful auto-ID selection process in warehouse management. Therefore, the main aim of this research is to investigate empirically the auto-ID technology-selection process and to determine the key factors that influence decision makers when selecting auto-ID technology in the warehouse environment. This research is preceded by a comprehensive and systematic review of the relevant literature to identify the set of factors that may affect the technology selection decision. The Technology-Organisation-Environment (TOE) framework has been used as lens to categorise the identified factors (Tornatzky & Fleischer, 1990). Data were collected by conducting first a modified (mixed-method) two-round Delphi study with a worldwide panel of experts (107) including academics, industry practitioners and consultants in auto-ID technologies. The results of the Delphi study were then verified via follow-up interviews, both face-to-face and telephone, carried out with 19 experts across the world. This research in nature is positivist, exploratory/descriptive, deductive/inductive and quantitative/qualitative. The quantitative data were analysed using the statistical package for social sciences, SPSS V.18, while the qualitative data of the Delphi study and the interviews were analysed manually using quantitative content analysis approach and thematic content analysis approach respectively. The findings of this research are reported on the motivations/reasons of warehouses in seeking to use auto-ID technologies, the challenges in making an auto-ID decision, the recommendations to address the challenges, the key steps that should be followed in making auto-ID selection decision, the key factors and their relative importance that influence auto-ID selection decision in a warehouse. The results of the Delphi study show that the six major factors affecting the auto-ID selection decision in warehouse management are: organisational, operational, structural, resources, external environmental and technological factors (in decreasing order of importance). In addition, 54 key sub-factors have been identified from the list of each of the major factors and ranked in decreasing order of the importance mean scores. However, the importance of these factors depends on the objectives and strategic motivations of warehouse; size of warehouse; type of business; nature of business environment; sectors; market types; products and countries. Based on the Delphi study and the interviews findings, a comprehensive multi-stage framework for auto-ID technology selection process has been developed. This research indicates that the selection process is complex and needs support and closer collaboration from all participants involved in the process such as the IT team, top management, warehouse manager, functional managers, experts, stockholders and vendors. Moreover, warehouse managers should have this process for collaboration before adopting the technology in order to reduce the high risks involved and achieve successful implementation. This research makes several contributions for both academic and practitioners with auto-ID selection in a warehouse environment. Academically, it provides a holistic multi-stage framework that explains the critical issues within the decision making process of auto-ID technology in warehouse management. Moreover, it contributes to the body of auto-ID and warehouse management literature by synthesising the literature on key dimensions of auto-ID (RFID/barcode) selection decision in the warehouse field. This research also provides a theoretical basis upon which future research on auto-ID selection and implementation can be built. Practically, the findings provide valuable insights for warehouse managers and executives associated with auto-ID selection and advance their understanding of the issues involved in the technology selection process that need to be considered.
Two-dimensional (2D) barcode technology is an electronic tagging technology based on combination of computer and optical technology. It is an important way of information collection and input. 2D ...barcode technology has been widely used in various fields of logistics, production automation, and e-commerce, but it also has brought about a series of safety problems. Based on evolutionary encryption technology, this paper improved algorithm of traditional 2D barcode generation, to improve forgery-proof performance of 2D barcode. This algorithm is applied to agricultural products quality and safety traceability system and the results show that it is effective.
Hospitals across the nation are struggling with implementing electronic medication administration and reporting (eMAR) systems as part of patient safety programs. St Luke's Hospital in Chesterfield, ...Mo, initiated their eMAR initiative in June 2003, initiating program start-up in September 2004. This case study documents how the project was approached, its overall success, and what was learned along the way. Also included is a recent update highlighting the expansion of St Luke's patient safety initiative, adapting eMAR to two specialty units: dialysis and laboratory processes.
With the swift increase of the number of mobile device users, more wireless information services and mobile commerce applications are needed. Since various barcodes have been used for decades as a ...very effective means in many traditional commerce systems, today people are looking for innovative solutions to use barcodes in the wireless world. Recently, the mobile industry began to pay more attention to barcode applications in m-commerce because 2D-barcodes not only provide a simple and inexpensive method to present diverse commerce data, but also improve mobile user experience by reducing their inputs. This paper first discusses 2D-barcode concepts, types and classifications, major technology players, and applications in mobile commerce. Then, it reports a research project to develop a 2D-barcode processing solution to support mobile applications. Moreover, the paper also presents the application examples, and case study using the solution.
Applying barcode technology to logistics and warehouse management becomes an inevitable trend for logistics modernization. In this paper, we introduce the bar code technology using in logistics and ...warehouse, then we pay more attention to how to apply barcode technology in the course of goods entering warehouse, storage and outing warehouse. At last we put forward that applying barcode technology to logistics and warehouse will bring logistics enterprises huge profit.
Circulating tumor DNA (ctDNA), which is the cell-free DNA released from dying cancer cells into the blood, is an emerging topic in cancer research. ctDNA is expected to gain importance in a large ...range of diagnostic applications, from early detection to disease progression monitoring. Unlike research involving other biomarkers such as microRNA, where the focus is on the exploration of new marker molecules, research involving ctDNA is mostly focused on the development of analytical technologies. These technologies are classified into those based on mutation-enriched PCR and those based on digital PCR (for example, BEAMing). Because it allows quantitative assessments, digital PCR is becoming the method of choice. Among devices that rely on digital PCR technology, massively parallel DNA sequencers are notable because of their ability to produce large amounts of data. For such sequencers, the current technical obstacle is the high read error rate. Barcode technology can eliminate read errors by using consensus reads generated from multiple sequence reads of a single molecule and enables the de novo detection of mutations, thus eliminating the requirement to screen mutations in primary tumors.
Healthcare organizations have increasingly adopted barcode technology to improve care quality and work efficiency. Barcode technology is simple to use, so it is frequently used in patient ...identification, medication administration, and specimen collection processes.
This study used a technology acceptance model and innovation diffusion theory to explore the innovation acceptance of barcode technology by nurses.
The data were collected using a structured questionnaire with open-ended questions that was based on the technology acceptance model and innovation diffusion theory. The questionnaire was distributed to and collected from 200 nurses from March to May 2014. Data on laboratory reporting times and specimen rejection rates were collected as well.
Variables that were found to have a significant relationship (p<.001) with innovation acceptance included (in order of importance): perceived usefulness (r=.722), perceived ease of use (r=.720), observability (r=.579), compatibility (r=.364), and trialability (r=.3
It is crucial for the studies of taxonomy and biodiversity by using DNA barcode technology to fast and accurately make species identification in the forests across tropics and temperate zones. In ...this study, the 183 plant species in a 20 hm2 subtropical forest plot in Dinghushan (DHS) National Nature Reserve of South China were sampled and sequenced, and the matK, rbcL, and psbA-trnH were employed to generate multi-locus barcodes. For the plot, the psbA-trnH possessed the highest integral success rate, i. e., the product of sequencing recovery and correct species identification (75%), followed by matK (70%), and rbcL (56%). A combination of three-locus barcode (matK, rbcL and psbA-trnH) could identify greater than 87% of the total species, followed by two-locus barcode (85% for matK+psbA-trnH, 83% for rbcL+psbA-trnH, and 81% for matK+rbcL). A comparison was made with the previously published results from one subtropical forest plot (LFDP in Puerto Rico, 143 species) and two tropical forest plots (BCI in Panam
