Field Research Designs Purpose of field research designs

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Field Research Designs • Purpose of field research designs • Types of field studies

Field Research Designs • Purpose of field research designs • Types of field studies • Planning a field study • Sampling plan • Questionnaire design – Online Questionnaires • Data analysis • Special concerns in field research

Some Definitions • Population • An entire group of people, events or things of

Some Definitions • Population • An entire group of people, events or things of interest • Element • Single member of population • Sample • Subgroup of the population • Subject • Single member of sample • Sampling • Selecting sufficient number of elements from population so that features of the sample (e. g. , mean) can be generalized to the population

Advantages of Sampling • Less cost • Compared to cost of studying population •

Advantages of Sampling • Less cost • Compared to cost of studying population • Less error • In collecting & analysing data • Less time • Because fewer elements considered • Less intrusive/destructive • E. g. , when measurement changes phenomenon

Sampling Plan • Random sampling • Each member of population has EQUAL chance of

Sampling Plan • Random sampling • Each member of population has EQUAL chance of being selected into sample • Ease of identifying population • Company vs. community vs. student populations • Determining sample • Random number tables, computerized routine, drawing from urn

Sampling Plan • Random sampling • Randomly select additional participants if initially selected ones

Sampling Plan • Random sampling • Randomly select additional participants if initially selected ones refuse/cannot • Order population, sample every xth person – ordering is not related to variable of interest • E. g. , Immigration checks • Use of convenience sample • Include variables that assess representativeness of obtained sample • If response rate is low • e. g. , ethnic harassment study

Sampling Plan • Modified random sampling • Stratified random sampling • Divide population into

Sampling Plan • Modified random sampling • Stratified random sampling • Divide population into subgroups & randomly select from subgroups • Sub-grouping expected to influence results (e. g. , motivational levels in R&D vs. secretarial staff) • Used when total sample size is small and number of subgroups is large • E. g. , visible minorities at Scar campus

Sampling Plan • Modified random sampling (cont’d) • Cluster sampling • Choose participants based

Sampling Plan • Modified random sampling (cont’d) • Cluster sampling • Choose participants based on membership of a group • Groups are then chosen to participate in study • Stats computed can have large sampling errors – E. g. , examine units in 4 vs. 30 boxes of a shipment • Over-sampling from a subgroup – E. g. , gays in the org’n • Need to weight descriptive stats appropriately

Field Research Designs • Sampling plan • Questionnaire design – Online Questionnaires • Data

Field Research Designs • Sampling plan • Questionnaire design – Online Questionnaires • Data analysis • Special concerns in field research

Questionnaire Design • Use existing measures of concepts • Comparability • Reliability (standardization) •

Questionnaire Design • Use existing measures of concepts • Comparability • Reliability (standardization) • Validity

Questionnaire Design • Writing Items • Comprehensiveness • E. g. , commitment scale •

Questionnaire Design • Writing Items • Comprehensiveness • E. g. , commitment scale • Accuracy • Maintain respondents’ cooperation & dignity

Questionnaire Design • Writing Items • Structured vs. Open-ended items • Respondent involvement in

Questionnaire Design • Writing Items • Structured vs. Open-ended items • Respondent involvement in research • Purpose of research • Exploratory vs. confirmatory • Type of question • E. g. , When all possibilities are not known/too many • Resource availability • Time & money for coding & analysing Saks 69 -73; Sekaran 238 -242

Questionnaire Design • Writing Items • • Use simple, direct, familiar language Be clear

Questionnaire Design • Writing Items • • Use simple, direct, familiar language Be clear & specific (avoid ambiguous items) Use positively and negatively worded items Avoid double-barreled items Avoid Leading questions Avoid loaded questions Ensure applicability to all respondents Avoid recall-dependent items Saks 69 -73; Sekaran 238 -242

Questionnaire Design • Writing Items • Minimize Response styles • Yea/Nay sayers (acquiescence) •

Questionnaire Design • Writing Items • Minimize Response styles • Yea/Nay sayers (acquiescence) • Positive vs. negatively worded items • Social Desirability » Forced choice format » Content-specific anchors (e. g. , BARS) » Items scattered across survey Saks 69 -73; Sekaran 238 -242

Questionnaire Design • Response options in structured scales • Types of Rating Scales •

Questionnaire Design • Response options in structured scales • Types of Rating Scales • Likert, Semantic Differential, Itemized Rating etc. (p. 197 -199 Sekaran) • Bimodal responding • Using only a portion of the response options • Ensure anchors have same meaning to all respondents • Use numbers w/verbal descriptors

Questionnaire Design • Response options in structured scales • Identify time frame of phenomenon

Questionnaire Design • Response options in structured scales • Identify time frame of phenomenon of interest • Optimal number of scale points • 5 points is best, fewer results in less variability • Instructions • Provide examples • Participants’ education level • Previous exposure to method of data collection • e. g. , web/email surveys

Questionnaire Design • Response options in structured scales • Sequencing • General to specific,

Questionnaire Design • Response options in structured scales • Sequencing • General to specific, easy to difficult • Avoid placing positively and negatively worded items tapping into the same dimension near each other • Beware of ordering effects • Issues with dispersal of items • Numbering • Attend to data analyses issues Sekaran 242

Questionnaire Design • Response options in structured scales • Layout (appearance) • Introduction •

Questionnaire Design • Response options in structured scales • Layout (appearance) • Introduction • e. g. , Study Information Sheet • Organization • By sections • Personal Data • Request sensitive personal data at the end • Open-ended questions in the end • Conclusion Sekaran 245 -249

Questionnaire Design • Pre-testing Survey • Readability, item content, ambiguities • Ways to Optimize

Questionnaire Design • Pre-testing Survey • Readability, item content, ambiguities • Ways to Optimize Return Rate • Upper management or union support • Work time allocated for survey completion • Coercion, confidentiality concerns • Participants’ belief in value of research • Previous experience with HR research • 30% rate is common

Questionnaire Design • Optimizing Return Rate • Professional appearance • For mailed survey: use

Questionnaire Design • Optimizing Return Rate • Professional appearance • For mailed survey: use first class mail & include return postage • • Send reminders Provide Incentives for responding Keep survey at optimal length Identify characteristics of non-responders to establish representativeness of sample • Identify mechanism for clarifying questions

Online Questionnaires • Advantages • Speed • Delivery to participants • Completed surveys to

Online Questionnaires • Advantages • Speed • Delivery to participants • Completed surveys to researcher • Cost efficiency • Environmental costs (e. g. , paper, ink) • Personnel costs (e. g. , typing, data entry)

Online Questionnaires • Concerns • Respondents’ access to computers • Establish invariance b/w paper-pencil

Online Questionnaires • Concerns • Respondents’ access to computers • Establish invariance b/w paper-pencil and computer versions (e. g. , achievement, attitude measures) • Ballot stuffing • Unique access control numbers • Start up costs • E. g. survey monkey $20/month • Technical difficulties during survey administration • Researcher’s control over design interface • E. g. survey monkey • Employee reactions to online surveys

Data Analysis • Preliminary Data Cleaning • Use descriptive data to catch errors •

Data Analysis • Preliminary Data Cleaning • Use descriptive data to catch errors • E. g. , means, ranges, standard deviations • Coding open-ended responses • Analysis & Interpretation • Descriptive data • Frequencies, means • Group comparisons • T-tests, ANOVAs • Establish relations between variables • Correlations, regressions

Special Issues in Field Research • Scale reduction • Alternatives to shortening existing scales

Special Issues in Field Research • Scale reduction • Alternatives to shortening existing scales • Reduce number of variables • Use alternative methods of measurement • E. g. , peer ratings, archival data etc.

Special Issues in Field Research • Percept-percept problem • Response bias due to cross-sectional,

Special Issues in Field Research • Percept-percept problem • Response bias due to cross-sectional, monomethod measurement of all variables • Alternatives to self-report questionnaires • E. g. , archival, objective data • Multiple data collection times • E. g. , Longitudinal study • Dispositional influences • E. g. , neuroticism

Special Issues in Field Research • Survey matching • Ensure confidentiality & anonymity •

Special Issues in Field Research • Survey matching • Ensure confidentiality & anonymity • Controlling extraneous variables • Conceptual understanding • Sample characteristics • Measurement or control of variables

Special Issues in Field Research • Response Variability • Dichotomous scales (e. g. ,

Special Issues in Field Research • Response Variability • Dichotomous scales (e. g. , y/n responses) • Ethics • Info re: research objectives • Precautions re: anonymity • Limit demographic info requested • Web/email based surveys • Mechanisms for research feedback • Implications, planned action, follow up