Premium
Conceptualizations of Trust: Can We Trust Them?
Author(s) -
Whipple Judith M.,
Griffis Stanley E.,
Daugherty Patricia J.
Publication year - 2013
Publication title -
journal of business logistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.611
H-Index - 79
eISSN - 2158-1592
pISSN - 0735-3766
DOI - 10.1111/jbl.12014
Subject(s) - construct (python library) , replication (statistics) , scale (ratio) , supply chain , strengths and weaknesses , business , sort , development theory , supply chain management , marketing , knowledge management , process management , computer science , psychology , social psychology , economics , medicine , market economy , physics , quantum mechanics , information retrieval , programming language , virology
Although logistics and supply chain management research efforts have continued to become more sophisticated, opportunities still exist for further advancement. One critical area needing improvement is enhanced scale development and validation. This study provides insights into the strengths and weaknesses of one specific construct, trust, by examining how trust has been measured in our literature. A methodology for improving scale development, the Q‐sort procedure, is used to demonstrate a need for better measurement scales. Our findings suggest that numerous measures of trust have been used for logistics and supply chain research—most of which have been borrowed from other disciplines—without significant replication. More importantly, the results illustrate that all too often content validity is less than adequate. It appears as though we are not always measuring what we want to. Greater focus is recommended for future research that examines theory‐based scale development, purification of measures, and replication of scales to further refine and improve construct measurement for enhanced survey research.