Acquiring logistics process intelligence: Methodology and an application for a Chinese bulk port

Wang, Ying; Caron, Filip; Vanthienen, Jan; Huang, Lei; Guo, Yi

doi:10.1016/j.eswa.2013.07.021

Cited by 51 publications

(26 citation statements)

References 45 publications

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“…This study further specifically inquired about data quality issues, since scholars indicated the considerable impact of human data collection errors (Wang, Caron, Vanthienen, Huang & Guo, 2014). This was confirmed by some interviewees but was evaluated as a minor component of the data quality issue, with its effect comparable to any other domain.…”

Section: Specifics In Intervening Conditionsmentioning

confidence: 52%

Mapping domain characteristics influencing Analytics initiatives: The example of Supply Chain Analytics

Herden

2020

JIEM

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Purpose: Analytics research is increasingly divided by the domains Analytics is applied to. Literature offers little understanding whether aspects such as success factors, barriers and management of Analytics must be investigated domain-specific, while the execution of Analytics initiatives is similar across domains and similar issues occur. This article investigates characteristics of the execution of Analytics initiatives that are distinct in domains and can guide future research collaboration and focus. The research was conducted on the example of Logistics and Supply Chain Management and the respective domain-specific Analytics subfield of Supply Chain Analytics. The field of Logistics and Supply Chain Management has been recognized as early adopter of Analytics but has retracted to a midfield position comparing different domains.Design/methodology/approach: This research uses Grounded Theory based on 12 semi-structured Interviews creating a map of domain characteristics based of the paradigm scheme of Strauss and Corbin.Findings: A total of 34 characteristics of Analytics initiatives that distinguish domains in the execution of initiatives were identified, which are mapped and explained. As a blueprint for further research, the domain-specifics of Logistics and Supply Chain Management are presented and discussed.Originality/value: The results of this research stimulates cross domain research on Analytics issues and prompt research on the identified characteristics with broader understanding of the impact on Analytics initiatives. The also describe the status-quo of Analytics. Further, results help managers control the environment of initiatives and design more successful initiatives.

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Section: Specifics In Intervening Conditionsmentioning

confidence: 52%

Mapping domain characteristics influencing Analytics initiatives: The example of Supply Chain Analytics

Herden

2020

JIEM

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“…The first cluster of academic papers focuses on the upstream stages of process mining, discovery and modeling. Wang et al (2013) and Wang et al (2014) construct a logistics process modeling methodology for highly and loosely structured processes, by using declarative and imperative approaches, but neither paper investigates process modeling as an integral phase of a BPM cycle. Elbert et al (2016) reveal how maritime transport chains work and model key processes with the objective to examine the inter-organizational information systems (IOS) share in the communication of individual organizations.…”

Section: Theoretical Application Of Business Process Management In Thmentioning

confidence: 99%

Business process management in the port sector: a literature review

Saragiotis

2019

MABR

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Purpose This paper aims to review the application of business process management (BPM) in the port sector. Its objective is to understand whether BPM principles are applied in the port sector, the role of the procedural factor in port performance evaluation and whether electronic data interchange systems have been used for process management purposes. Design/methodology/approach The objective of this research is to conduct a critical review of existing academic literature in the domain of BPM and its application in the ports sector. This paper assessed more than a hundred recent publications, from key journals in the domains of port economics, BPM and information technology. The two principle platforms used are the online databases of the World Bank Group and the University of Antwerp. Findings Academic literature reviewed reveals a partial application of BPM in the port and maritime sector. BPM related research is conducted via the utilization of modeling algorithms or optimization and simulation tools. There exists evidence that electronic data interchange (EDI) data extracted from EDI platforms can be used to model inter-organizational business processes in several industries. Yet, to the best of the author’s knowledge, no research investigates Port Community System (PCS) or single window (SW) data utilization for BPM purposes, although PCS and SW benefits are well documented. Port performance is largely assessed based on the production theory, and limited number of studies use elements of procedural efficiency as variables for their analysis. Originality/value The holistic application of BPM has been researched in numerous industries but in the port sector. This paper constitutes the first section of an original research study to define key components, assumptions and constraints for developing a comprehensive BPM framework in the port sector.

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“…Fragment duration considers the time required to complete a fragment (a set of activities) of a process. Wang et al [41] propose a framework for applying process mining in logistics and analyze process fragments of a Chinese bulk port process. They identify the most time-consuming fragments of the process and, using the fragment durations, they categorize cases containing those fragment to give insights on their performance.…”

Section: Aspects Of Process Performance (Rq1)mentioning

confidence: 99%

“…A business seeking to conduct data-driven performance analysis, should first select the type of technique. Descriptive analysis will show the current state and [34], [23], [5], [6], [32], [3] Process Duration -- [41] Fragment Duration Activity Start and End Time [7], [24], [23], [17], [5] Activity Duration -- [19], [31], [29], [34], [7], [24] Waiting Duration [30], [38], [36], [ [21], [22] Framework to extract process characteristics from event logs discriminating between positive and negative cases [5], [6] Comparing waiting duration of similar process in different installations [11], [15] Collaborative Processes [26] Evolution of performance over time [40] Framework for performance-related analysis with information-poor event logs Type Domain…”

Section: Frameworkmentioning

confidence: 99%

A Comparative Evaluation of Log-Based Process Performance Analysis Techniques

Milani

Maggi

2018

Business Information Systems

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Process mining has gained traction over the past decade and an impressive body of research has resulted in the introduction of a variety of process mining approaches measuring process performance. Having this set of techniques available, organizations might find it difficult to identify which approach is best suited considering context, performance indicator, and data availability. In light of this challenge, this paper aims at introducing a framework for categorizing and selecting performance analysis approaches based on existing research. We start from a systematic literature review for identifying the existing works discussing how to measure process performance based on information retrieved from event logs. Then, the proposed framework is built starting from the information retrieved from these studies taking into consideration different aspects of performance analysis. accessibility to open source tools has never been easier, in particular for data driven analysis of business processes. Therefore, in a digital era, businesses cannot hope to survive with manually driven methods. The process analysis must also be digitally transformed by tapping into data-driven analysis methods.One group of techniques for data driven performance analysis uses event logs of processes to assess performance. Indeed, nowadays, business processes are often supported by IT systems that log their execution. For instance, an order-to-invoice process might include activities such as register, validate, approve, fill order and send invoice. Each order has a unique id and every activity is recorded in the event log with information about the time when it was executed (timestamp) and other additional data such as the resource (person or device) that executed the activity. As such, the process is inherently captured in the log. With process mining techniques [2], the performance of such processes can be assessed and analyzed in great detail based on event logs.The body of research and tools within the field of process mining has grown significantly during this decade. However, the availability of tools and approaches developed for specific aspects of process performance does not make it easier for businesses to employ them. In fact, it poses a challenge. There is no way for businesses to easily get an overview of what performance indicators can be measured, what input data is required for such analysis, or what industry specific implementations are available. In light of this context, we propose a framework for the selection of log-based performance analysis techniques. We do so by conducting a systematic literature review to identify the body of existing work. We analyze the results and focus on identifying existing process performance indicators, required input data, and approaches available. Based on the results, we build a framework for the selection of suitable performance analysis approaches.The structure of this paper is as follows. Section 2 summarizes the research protocol for the systematic survey. In Section 3, the research que...

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Acquiring logistics process intelligence: Methodology and an application for a Chinese bulk port

Cited by 51 publications

References 45 publications

Mapping domain characteristics influencing Analytics initiatives: The example of Supply Chain Analytics

Mapping domain characteristics influencing Analytics initiatives: The example of Supply Chain Analytics

Business process management in the port sector: a literature review

A Comparative Evaluation of Log-Based Process Performance Analysis Techniques

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