ICES III - Johan Erikson1 Effects of offering web questionnaires as an option in enterprise surveys – The Swedish experience Johan Erikson Statistics Sweden.

Slides:



Advertisements
Similar presentations
Professional Development Management System (PDMS) A tutorial for professional development cluster Vendors, Providers and Instructors Charlie Michels PSB.
Advertisements

Survey Methodology Nonresponse EPID 626 Lecture 6.
Online surveys for business tendency in Slovenia Brussels, November 2014 Laura Šuštar Kožuh.
COLLECTING DATA ON A SAMPLE OF RESPONDENTS Designing survey instruments.
Accounts Payable–1099 Processing 1Freedom Systems – Accounts Payable – 1099 Processing WELCOME TO THE ACCOUNTS PAYABLE – 1099 PROCESSING WEBINAR WE WILL.
The Many Ways of Improving the Industrial Coding for Statistics Canada’s Business Register Yanick Beaucage ICES III June 2007.
Information system for the Swedish Accommodation Statistics Sara Frankl, Statistics Sweden Marketing Manager at the unit “Travellers and Tourism” tfn:
Survey Research Questionnaire construction Types of surveys
Anabela Delgado Carlota Amorim Statistics Portugal - Census Unit « Simply2010 Ghent 2-3 December 2010 E-CENSUS: A new data collection system for the 2011.
 Journal entries are comments or notes that can be left on an employee ANYTIME throughout the year.  The purpose of the journal entries is to help reviewers.
Editing of mixed source data for turnover statistics Jeffrey Hoogland (SN) Work Session on Statistical Data Editing (Ljubljana, Slovenia, 9-11 May 2011)
Using Skype for Building Effective Group Collaboration
Towards a corporate-wide electronic data collection system at the National Statistical Institute of Spain Work Session on Statistical Data Editing Ljubljana,
Application Process USAJOBS – Application Manager USA STAFFING ® —OPM’S AUTOMATED HIRING TOOL FOR FEDERAL AGENCIES.
The converging pattern between Business statistics and Administrative data. Towards an “industrialized” statistical production process The Italian LCS2012.
Learning series creating agency users virtual classroom.
GFP in the IUID Registry – A Basic Look Walt Clark, CPPM Raytheon IIS.
October 18,  Benefit Year Earnings (BYE): Root Causes Identified:  Agency Causes  Insufficient resources  Claimant Causes  Unreported/Under.
IIPS Summer Conference Session VI Wednesday, July 23, 2008 ~ 8:30 – 10:00 AM Presenters: Carolyn S. Evert and Susan D. Pritchard, Caldwell Community College.
Making Sense of the Social World 4th Edition
Web-based Surveys: Changing the Survey Process, by Holly Gunn First Monday, volume 7, number 12 (December 2002), URL:
Introduction to AFRS Toolbox
1 CHAPTER 2 “ New Quotes ”. 2 1.New Quote – From the “Community Home Page”, click on the “Get a New PUP Quote” link. 1.
Microsoft Access Data Base Application. A Few Terms Database – A collection of related information. Database – A collection of related information. Field.
R&R Enhancements Brett Grumbine
Understanding the Decision to Participate in a Survey and the Choice of the Response Mode Anders Holmberg and Boris Lorenc European Conference on Quality.
Lesli Scott Ashley Bowers Sue Ellen Hansen Robin Tepper Jacob Survey Research Center, University of Michigan Third International Conference on Establishment.
Mixed mode in the data collection of SBS statistics within Statistics Sweden Cecilia Hertzman Seminar om Statistical Data Collection, Geneva
Georgia: business register data and gender-disaggregated indicators Tengiz Tsekvava Technical Meeting on Measuring Entrepreneurship from Gender Perspective.
Eurostat Data collection. Presented by Johan Erikson Statistics Sweden.
Development of Electronic Data Reporting (EDR) in Statistics Finland.
The Experiences of Web Based Data Collection from Enterprises in Finland August 9th 2006, JSM Seattle USA.
Primary Data Collection Primary Data Collection Strategies Survey Method Case Study Method Experiment Method.
IPortal Bringing your company and your business partners together through customized WEB-based portal software. SanSueB Software Presents iPortal.
NACEP Conference 2004 Capturing them in the Web: Using Web- Based Surveys to Increase Response Rates for College Freshman Debbie.
Use of Administrative Data Seminar on Developing a Programme on Integrated Statistics in support of the Implementation of the SNA for CARICOM countries.
Electronic data collection System in CSB of Latvia By Karlis Zeila, Vice President, CSB of Latvia IT DG meeting, October , Eurostat.
Comprehensive Unit-based Safety Program for CUSP4MVP – VAP HSOPS CONFIDENTIAL Leveraging the MedConcert Social Enterprise Platform to Scale and Spread.
Editing of linked micro files for statistics and research.
Increasing Efficiency in Data Collection Processes Arie Aharon, Israel Central Bureau of Statistics.
WebInq: electronic data collection service WebInq electronic data collection service INE Portugal Electronic Raw Data Reporting UNECE / Eurostat (Geneva,
Towards efficient data collection at Statistics Sweden Johan Erikson Data collection, process owner
Electronic Data Collection Systems in HCSO Luxembourg, 15 June, 2009
Welcome to the November Release Overview Meeting Please remember to place your phone on mute and do NOT place your phone on hold.
Chapter X Questionnaire and Form Design. Chapter Outline Chapter Outline 1) Overview 2) Questionnaire & Observation Forms i. Questionnaire Definition.
Pre-printing experiences at Statistics Sweden Anders Holmberg Department of Research & Development Statistics Sweden SE Örebro Sweden Tel:
Creating A Survey Using Office of Student Affairs Assessment The University of Georgia A-Team Training-Skills Session 1 October 30, 2007.
Trying to improve editing tasks through EDR methods Pedro Revilla, Ignacio Arbués, Margarita Gonzalez and Isabel Yun National Statistical Institute, Spain.
Managing Multi Mode Collection Instruments in the 2011 UK Census Frank Nolan, Heather Wagstaff, Ruth Wallis Office for National Statistics UK.
Producer Price Indices in Denmark - Producer price index for commodities (PPI) March 20 th 2015.
Data Collecting Techniques Telephone interviews Traditional telephone interviews involve phoning a sample of respondents and asking them a series.
Data Screening. What is it? Data screening is very important to make sure you’ve met all your assumptions, outliers, and error problems. Each type of.
DESKALERTS. INTERNAL COMMUNICATIONS | | DeskAlerts Enterprise Edition Features.
Measuring e-commerce - the Eurostat and OECD approach and the Statistics Finland experience Aarno Airaksinen Regional Workshop, Strengthening.
Confirmations, Bulk s, and System Text
Software Application Overview
USAJOBS – Application Manager
Microsoft Office 2003 Illustrated Introductory, Premium Edition
28 November - 1 December 2016, Amman, Jordan
Planning the change to a targeted survey design
28 November - 1 December 2016, Amman, Jordan
Electronic Data Collection at Statistics Canada
Global Assessment on Tendency Surveys
William Jones, Harry Bruce
Johan Erikson Statistics Sweden Luxemburg, March 2012
National needs for AES Purpose - describe participation in learning during a 12 months period. The main parameters are; Participation rates in different.
Improving Cost Efficiency of Chain Store Reporting in Norway
Mixed mode in Swedish SBS – importing SIE files
Multi-Mode Data Collection
Presentation transcript:

ICES III - Johan Erikson1 Effects of offering web questionnaires as an option in enterprise surveys – The Swedish experience Johan Erikson Statistics Sweden

ICES III - Johan Erikson2 Disposition Background (The SIV tool and general strategies) Experience (take-up and efforts to raise it, re- design, data quality – a few case studies) Conclusions

ICES III - Johan Erikson3 The SIV tool Generalised tool Form construction, Administration, Security, Presentation on web Data base solution, pages generated ”on the fly” one at a time Dynamic in all aspects (pages, questions, rows and columns) Developed (ongoing) Used for both enterprise surveys, household surveys, surveys to agencies and municipalities Will be integrated to have three presentation tools: web, windows form (for telephone interviews), hand-held computers Up to now: used in 40+ enterprise surveys, 100+ surveys in total

ICES III - Johan Erikson4 General strategy Defensive strategy Paper form + opportunity to reply on the web Log-in information normally placed on the paper form and not on the cover letter Web questionnaires slightly re-designed to fit screen size rather than paper size Dynamic when possible (skip patterns, add rows and columns when necessary) Some (but mostly simple) edit checks Reminders – some have new paper form, some do not

ICES III - Johan Erikson5 Take-up With general strategy – take-up varies from less than 2% to more than 40% Normal take-up: 5-20% Surveys with high take-up: register updates, surveys that have had TDE as an option Take-up in monthly surveys: stable or rising Possible effort to raise take-up: No paper questionnaire (ordinary sending or reminder)

ICES III - Johan Erikson6 Take-up over time

ICES III - Johan Erikson7 Efforts to raise take-up ”LINDA” survey – wages (november) for specific individuals (longitudinal survey) – not all employees Normally, 1-10 individuals per enterprise Almost enterprises (27500 have 1-3 individuals) Experiment: 20 per cent of enterprises 1-4 indivisuals and 100% of enterprises 5-10 individuals were sent no paper questionnaire (will be sent at reminder, when the others will not be sent a new paper questionnaire)

ICES III - Johan Erikson8 Efforts to raise take-up

ICES III - Johan Erikson9 Efforts to raise take-up Development of new enterprises Experiment: No new paper form at reminder, extra push for web

ICES III - Johan Erikson10 Efforts to raise take-up The big step – eliminating paper forms 3-4 surveys Most enterprises use web when it´s the option given Paper form when active effort (phone call) Some extra efforts have been made on reminders Response rates have varied, from no change to small dips

ICES III - Johan Erikson11 Re-design Web as a third alternative – turnover statistics Before: paper/TDE Now: paper/TDE/Web Only one indicator (turnover) Monthly/quarterly statistic

ICES III - Johan Erikson12 Re-design

ICES III - Johan Erikson13 Data quality Data is scarce Based on editing after collection Ratio of objects showing at least one error signal Remember: not many edit checks in web questionnaire But: elementary edits (format, radio buttons allowing only one mark, automatic skip patterns) eliminate some errors Tendency is similar regardless of type of survey – ratio of objects with error signals is lower for web Slight but slow tendency of error rates to decrease over time

ICES III - Johan Erikson14 Data quality

ICES III - Johan Erikson15 Data quality

ICES III - Johan Erikson16 Conclusions Take-up with defensive strategy is rather low Take-up-rates may be influenced significantly Not sending paper questionnaires may reduce response rates Offering web as an alternative can raise electronic share of responses even when TDE is used as well Data quality tends to be somewhat higher on web than on paper – mostly because simple errors can be eliminated