Publication:

How to deal with negative online employer reviews: An application of image repair theory

Date

Date

Date
2022
Journal Article
Published version

Citations

Citation copied

Kollitz, R., Ruhle, S., & Wilhelmy, A. (2022). How to deal with negative online employer reviews: An application of image repair theory. International Journal of Selection and Assessment, 30(4), 526–544. https://doi.org/10.1111/ijsa.12392

Abstract

Abstract

Abstract

Although negative employer reviews pose a threat to employers by reducing organizational attractiveness, employers can respond to reviews to avert these threats. However, we lack a clear understanding of the response strategies and factors that determine response strategies' impact. To address this issue, we introduce image repair theory (IRT) as a promising theoretical foundation in the study of employer response. Using an experimental design, we tested the effects of IRT's general image repair strategies (i.e., Denial, Evasion of Re

Additional indexing

Creators (Authors)

Journal/Series Title

Journal/Series Title

Journal/Series Title

Volume

Volume

Volume
30

Number

Number

Number
4

Page range/Item number

Page range/Item number

Page range/Item number
526

Page end

Page end

Page end
544

Item Type

Item Type

Item Type
Journal Article

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Keywords

Management of Technology and Innovation, Strategy and Management, General Psychology, Applied Psychology, General Business, Management and Accounting

Language

Language

Language
English

Publication date

Publication date

Publication date
2022-12-01

Date available

Date available

Date available
2023-05-09

Publisher

Publisher

Publisher

ISSN or e-ISSN

ISSN or e-ISSN

ISSN or e-ISSN
0965-075X

OA Status

OA Status

OA Status
Hybrid

Citations

Citation copied

Kollitz, R., Ruhle, S., & Wilhelmy, A. (2022). How to deal with negative online employer reviews: An application of image repair theory. International Journal of Selection and Assessment, 30(4), 526–544. https://doi.org/10.1111/ijsa.12392

Hybrid Open Access
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Files
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