DialogEngines – Dialog Agents for Web-Based Self Service Consulting

Author(s):  
Oskar Bartenstein
Keyword(s):  
2010 ◽  
pp. 1668-1688
Author(s):  
R. Naidoo ◽  
A. Leonard

This chapter adopts an interpretive, case based research strategy to discuss the centrality of meaning in implementing an Internet-based self-service technology. Actor-Network theory (ANT) is used to describe the complex evolution of a Web-based service at a healthcare insurance firm. Using processes of inscribing, translating and framing, this chapter explores the emergence of the technology from 1999 – 2005 using three technological frames, ‘channel of choice’, ‘dazzle the customer’, and ‘complementary channel’ as episodes of translation. ANT demonstrates that the Internet-based self-service technology at this particular healthcare context emerged out of many unplanned negotiations and mediations with both human and non human actors. Finally, this chapter argues that ANT’s socio-technical lens provides a richer understanding of the meaning of Internet-based self-service technology within a multi-channel context.


2021 ◽  
Vol 4 (2) ◽  
pp. 92
Author(s):  
Syifa Irhammi Ramdhania ◽  
Ikrar Panji Satrio ◽  
M. Dicky Firyal ◽  
Afriyani Agustin ◽  
Aries Saifudin

Many companies engaged in fashion and self-service such as Independent Jeans, still use manual processes in storing incoming and outgoing product data, and in the process the system is still inefficient and there may still be errors in storing incoming and outgoing product data. Such as the process of storing incoming and outgoing product data that still uses paper, and the calculations still use a calculator and product entry and exit transactions. So in order to solve this problem, we need a web-based application for processing incoming and outgoing product data that has login features, user lists, added users, supplier pages, brand management, SPG transactions, print transactions, print transactions, transaction lists, report pages. The development process uses the waterfall method, for the language it uses the PHP (HyperText Processor) programming language and MySQL as a DBMS. Application using the waterfall method can facilitate the process of completing the application development process because there are already stages in the method used.


2019 ◽  
Vol 8 (3) ◽  
pp. 7034-7039

This study tried to understand the intention of technology adoption for web-based self-service technology (SST) pertaining to the airline sector in India. A survey-based approach was employed to acquire 458 responses. These responses were obtained from passengers who were using the airline’s service. The passengers were from three international airports that are located in Chennai, Hyderabad, and Bangalore. The partial least square structural equation modeling technique was employed to investigate the hypothesis. To recognize the influences on web-based SST(endogenous variables), along with the concept of adoption purpose as per the air passengers’ perceptions, the initial qualitative study joined the resultant literature examination in correspondence with the interview with focus groups. The following are the exogenous factors applied in the study; apparent usefulness: apparent ease of usage, trustworthiness, perceived risk, supposed behavioral regulator, subjective standard, word-of-mouth reports, apparent playfulness, and approach and adaptation purpose. Results specify factors that suggestively affect the intention to employ SSTs. Theoretical as well as managerial implications are deliberated on.


10.2196/19533 ◽  
2020 ◽  
Vol 4 (10) ◽  
pp. e19533
Author(s):  
Haipeng Zhang ◽  
Dimitar Dimitrov ◽  
Lynn Simpson ◽  
Nina Plaks ◽  
Balaji Singh ◽  
...  

Background As of July 17, 2020, the COVID-19 pandemic has affected over 14 million people worldwide, with over 3.68 million cases in the United States. As the number of COVID-19 cases increased in Massachusetts, the Massachusetts Department of Public Health mandated that all health care workers be screened for symptoms daily prior to entering any hospital or health care facility. We rapidly created a digital COVID-19 symptom screening tool to enable this screening for a large, academic, integrated health care delivery system, Partners HealthCare, in Boston, Massachusetts. Objective The aim of this study is to describe the design and development of the COVID Pass COVID-19 symptom screening application and report aggregate usage data from the first three months of its use across the organization. Methods Using agile principles, we designed, tested, and implemented a solution over the span of one week using progressively customized development approaches as the requirements and use case become more solidified. We developed the minimum viable product (MVP) of a mobile-responsive, web-based, self-service application using research electronic data capture (REDCap). For employees without access to a computer or mobile device to use the self-service application, we established a manual process where in-person, socially distanced screeners asked employees entering the site if they have symptoms and then manually recorded the responses in an Office 365 Form. A custom .NET Framework application solution was developed as COVID Pass was scaled. We collected log data from the .NET application, REDCap, and Microsoft Office 365 from the first three months of enterprise deployment (March 30 to June 30, 2020). Aggregate descriptive statistics, including overall employee attestations by day and site, employee attestations by application method (COVID Pass automatic screening vs manual screening), employee attestations by time of day, and percentage of employees reporting COVID-19 symptoms, were obtained. Results We rapidly created the MVP and gradually deployed it across the hospitals in our organization. By the end of the first week, the screening application was being used by over 25,000 employees each weekday. After three months, 2,169,406 attestations were recorded with COVID Pass. Over this period, 1865/160,159 employees (1.2%) reported positive symptoms. 1,976,379 of the 2,169,406 attestations (91.1%) were generated from the self-service screening application. The remainder were generated either from manual attestation processes (174,865/2,169,406, 8.1%) or COVID Pass kiosks (25,133/2,169,406, 1.2%). Hospital staff continued to work 24 hours per day, with staff attestations peaking around shift changes between 7 and 8 AM, 2 and 3 PM, 4 and 6 PM, and 11 PM and midnight. Conclusions Using rapid, agile development, we quickly created and deployed a dedicated employee attestation application that gained widespread adoption and use within our health system. Further, we identified 1865 symptomatic employees who otherwise may have come to work, potentially putting others at risk. We share the story of our implementation, lessons learned, and source code (via GitHub) for other institutions who may want to implement similar solutions.


2010 ◽  
Vol 29 (1) ◽  
pp. 41-49
Author(s):  
Ming-Hsien Yang ◽  
Jason C.H. Chen ◽  
Cheng-Hang Wu ◽  
Hung-Yi Chao

2020 ◽  
Vol 40 (04) ◽  
pp. 197-203
Author(s):  
Athithya E ◽  
Kavitha AC ◽  
Dr. Muralidhar S

Every organisation irrespective of its size primarily cares about its most valuable and indispensable asset the Human Resource (HR). At present, In many organisations the processes of Human Resource Development (HRD) have undergone a great transformation from a conventional mode (Human intensive manual system) to a computerised one. The objective of this paper is to discuss about design, implementation and analyzing about the impact of computerised HR process in Workforce Training Management using web based self service portal for the entire training process. Experimental analysis revealed that the automated system improves transparency, traceability, ease of access, flexibility and also enhances the overall system efficiency.


Author(s):  
Haipeng (Mark) Zhang ◽  
Dimitar Dimitrov ◽  
Lynn Simpson ◽  
Balaji Singh ◽  
Nina Plaks ◽  
...  

AbstractBackgroundThe COVID-19 pandemic has impacted over 1 million people across the globe, with over 330,000 cases in the United States. To help limit the spread in Massachusetts, the Department of Public Health required that all healthcare workers must be screened for symptoms daily – individuals with symptoms may not work. We rapidly created a digital COVID-19 symptom screening tool for a large, academic, integrated healthcare delivery system, Partners HealthCare, in Boston, Massachusetts.ObjectiveWe describe the design and development of the COVID-19 symptom screening application and report on aggregate usage data from the first week of use across the organization.MethodsUsing agile principles, we designed, tested and implemented a solution over the span of a week using progressively custom development approaches as the requirements and use case become more solidified. We developed the minimum viable product (MVP) of a mobile responsive, web-based self-service application using REDCap (Research Electronic Data Capture). For employees without access to a computer or mobile device to use the self-service application, we established a manual process where in-person, socially distanced screeners asked employees entering the site if they have symptoms and then manually recorded the responses in an Office 365 Form. A custom .NET Framework application was developed solution as COVID Pass was scaled. We collected log data from the .NET application, REDCap and Office 365 from the first week of full enterprise deployment (March 30, 2020 – April 5, 2020). Aggregate descriptive statistics including overall employee attestations by day and site, employee attestations by application method (COVID Pass automatic screening vs. manual screening), employee attestations by time of day, and percentage of employees reporting COVID-19 symptomsResultsWe rapidly created the MVP and gradually deployed it across the hospitals in our organization. By the end of the first week of enterprise deployment, the screening application was being used by over 25,000 employees each weekday. Over the first full week of deployment, 154,730 employee attestation logs were processed across the system. Over this 7-day period, 558 (0.36%) employees reported positive symptoms. In most clinical locations, the majority of employees (∼80-90%) used the self-service application, with a smaller percentage (∼10-20%) using manual attestation. Hospital staff continued to work around the clock, but as expected, staff attestations peaked during shift changes between 7-8am, 2-3pm, 4-6pm, and 11pm-midnight.ConclusionsUsing rapid, agile development, we quickly created and deployed a dedicated employee attestation application that gained widespread adoption and use within our health system. Further, we have identified over 500 symptomatic employees that otherwise would have possibly come to work, potentially putting others at risk. We share the story of our implementation, lessons learned, and source code (via GitHub) for other institutions who may want to implement similar solutions.


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