Supplement to the Article: How Product Representation Influences the Understanding of Supply Chain Process Models

2019 ◽  
Author(s):  
Joerg Leukel ◽  
Vijayan Sugumaran
Keyword(s):  
Supply Chain ◽  
Process Models ◽  
Chain Process ◽  
Product Representation ◽  
Supply Chain Process

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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joerg Leukel ◽  
Vijayan Sugumaran
Keyword(s):  
Supply Chain ◽  
Information Acquisition ◽  
Empirical Evaluation ◽  
Process Models ◽  
Chain Process ◽  
Content Type ◽  
Textual Representations ◽  
Scor Model ◽  
Supply Chain Process ◽  
Diagram Group

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.

scholarly journals The mediating effect of big data analysis on the process orientation and information system software to improve supply chain process in Saudi Arabian industrial organizations

2021 ◽  
pp. 135-142 ◽  
Author(s):  
Ahmed Faek Elgendy
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Information Systems ◽  
Data Analysis ◽  
Saudi Arabian ◽  
Big Data Analysis ◽  
Chain Process ◽  
Process Orientation ◽  
Industrial Organizations ◽  
Supply Chain Process

This study aims to investigate the nature of the relationship between Big Data Analysis as a mediator in Process Orientation (PO) and Information Systems Programming (ISP) to supply chains processes in Saudi Arabian industrial organizations. A stratified random sample of 357 managers and employees working in 37 industrial companies in Saudi Arabia was tested. The study relied on the descriptive and analytical research methodology. The results indicated that there is a significant indirect effect of Big Data Analysis (Planning, Procuring, Manufacturing, Delivering) as the mediator on Process Orientation and Information Systems Programming (ISP) and (PO) to improve supply chain process as well as organizational effectiveness. The researcher made a number of recommendations for the Saudi Arabian manufacturing firms to develop analytical capabilities in managers in order to utilize big data analysis as a tool to increase efficiency and effectiveness in the organizational system. A wide spread awareness program about the benefits to adopt big data analysis and management information systems may be adopted to ensure an efficient supply chain system.

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