Supplement to the Article: The Role of Application Domain Knowledge in Understanding Supply Chain Process Models

Leukel, Joerg; Hubl, Marvin

doi:10.2139/ssrn.3228419

Cited by 1 publication

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“…We summed up the scores for the two domains (maximum scores of six and eight, respectively and total score of fourteen). This type of task and the measurement of task performance have been introduced and validated in previous research (Leukel and Hubl, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…Grammar test score was defined as the number of correct answers to six multiple-choice (MC) questions about the SCOR grammar. Participants had to validate statements adapted from previous research (Leukel and Hubl, 2018). We included this variable to measure participants' actual modeling knowledge.…”

Section: Methodsmentioning

confidence: 99%

“…Diagram test score also measured participants' actual modeling knowledge by providing an exemplar diagram for which participants had to answer five MC questions (four answer options each). We adapted the diagram and questions from a previous experiment (Leukel and Sugumaran, 2018).…”

Section: Methodsmentioning

confidence: 99%

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How novice analysts understand supply chain process models: an experimental study of using diagrams and texts

Leukel

Sugumaran

2021

JEIM

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PurposeProcess models specific to the supply chain domain are an important tool for the analysis of interorganizational interfaces and requirements of information technology (IT) systems supporting supply chain decision-making. The purpose of this study is to examine the effectiveness of supply chain process models for novice analysts in conveying domain semantics compared to alternative textual representations.Design/methodology/approachA laboratory experiment with graduate students as proxies for novice analysts was conducted. Participants were randomly assigned to either the diagram group, which worked with “thread diagrams” created from the modeling grammar “Supply Chain Operation Reference (SCOR) model”, or the text group, which worked with semantically equivalent textual representations. Domain understanding was measured using cognitively demanding information acquisition for two different domains.FindingsDiagram users were more accurate in identifying product-related information and organizing this information in a graph compared to those using the textual representation. The authors found considerable improvements in domain understanding, and using the diagrams was perceived as easy as using the texts.Originality/valueThe study's findings are unique in providing empirical evidence for supply chain process models being an effective representation for novice analysts. Such evidence is lacking in prior research because of the evaluation methods used, which are limited to scenario, case study and informed argument. This study adds the diagram user's perspective to that literature and provides a rigorous empirical evaluation by contrasting diagrammatic and textual representations.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%