Proactive decision making in supply chain procurement

Vlahakis, George N.; Kopanaki, Evangelia; Apostolou, Dimitris

doi:10.1080/10919392.2019.1671739

Cited by 6 publications

(4 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, it argues that the analysis of the impact of complex IT infrastructures on business resilience can be conducted through the identification and evaluation of its different systems and IT characteristics. Based on the literature the paper identifies important IT characteristics, such as information sharing [72], interconnection [9], similar messaging standards, event management [77], proactive decision-making capabilities [76,79], software scalability and resource on demand [22].…”

Section: Discussionmentioning

confidence: 99%

“…"SCEM is reactive by its nature as event processing deals with the detection and notification upon undesired events that are already identified in the supply chain, taking action upon already known situations." [76] (p. 29). Therefore, event handling presupposes situation awareness.…”

Section: Messaging Standardsmentioning

confidence: 99%

“…Proactive decision making is related to the ability to predict future and undesired events as well as to make decisions needed to mitigate the effects of the predicted events before their occurrence [76,79]. Consequently, proactive event processing must identify future events, predict event patterns and specify possible courses of action to take [80].…”

mentioning

confidence: 99%

See 2 more Smart Citations

Conceptualizing Supply Chain Resilience: The Role of Complex IT Infrastructures

Kopanaki

2022

Systems

Self Cite

View full text Add to dashboard Cite

To deal with environmental uncertainty, organizations need resilience to respond to disruptions, such as changing market conditions or variations in demand or supply, while avoiding large scale adjustments. The concept of resilience is ambiguous, often explained as the capability of an organization or a supply chain to recover its original state, within an appropriate time frame, after being disrupted. Resilient supply chains have event handling capabilities, can provide efficient responses, and can return to their normal operating performance, after the disruptive event. To increase their resilience, companies often make changes or adjustments to their internal IT infrastructure, which may temporarily disrupt their smooth operation. As a result, contemporary IT infrastructures are mixed and include varied systems or technologies. Although new technologies, including blockchain, IoT and cloud-based solutions, may facilitate the handling of changes by providing secure, low cost and scalable solutions, more traditional systems may hinder such changes. Therefore, the relationship between IT and supply chain resilience is still unclear. The paper intends to examine the above issues by adopting a socio-technical approach to explain the concept of supply chain resilience and investigate the role of IT. More specifically, based on previous literature and on the appreciative systems thinking theoretical perspective, the paper develops a theoretical framework to analyse the organisational and/or supply chain resilience. It then uses this framework to examine and explain the impact of IT, by identifying important characteristics of an IT infrastructure and examining whether they may support or hinder business resilience.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Messaging Standardsmentioning

confidence: 99%

See 1 more Smart Citation

Conceptualizing Supply Chain Resilience: The Role of Complex IT Infrastructures

Kopanaki

2022

Systems

Self Cite

View full text Add to dashboard Cite

show abstract

“…Predictive analytics is also often used in the decision tree (DT) as it is deemed a userfriendly predictive tool where users can easily interpret the data. DT is a supervised easy learning algorithm focused on deducing the class or value of target variables according to the machine learning (ML) order trained by the training data (Vlahakis et al, 2020;Sarker, 2021). The approach is easy to use and interpret with simple mathematics without statistical knowledge or complex formulas.…”

Section: Introductionmentioning

confidence: 99%

Predictive Analytics in Business Analytics: Decision Tree

2022

ADS

View full text Add to dashboard Cite

Purpose: Business Analytics was defined as one of the most important aspects of combinations of skills, technologies and practices which scrutinize a corporation's data and performance to transpire data-driven decision-making analytics for a corporation's future direction and investment plans. In this paper, much of the focus will be given to predictive analytics, which is a branch of business analytics that scrutinize the application of input data, statistical combinations and intelligence machine learning statistics on predicting the plausibility of a particular event happening, forecast future trends or outcomes utilizing on-hand data with the final objective of improving the performance of the corporation. While it has been around for decades, predictive analytics has gained much attention in the late 20th century. This technique includes data mining and big data analytics. Last but not least, the decision tree methodology, a supervised simple classification tool for predictive analytics, is fully scrutinized below for applying predictive business analytics and decision tree in business applications.Design/ Methodology/Approach: A systematic literature review was conducted in predictive analytics and decision tree. The literature review explains various fields' latest predictive analytics and decision trees. All the research papers are obtained from two databases: Web of Science and Scopus, which are widely acknowledged by the scientific and research communities that contain top-quality peer-reviewed journals.Findings: This study reviews the application of predictive analytics and decision tree in business decision-making across various fields.Practical implications: This paper will strongly contribute to providing significant inputs to analysts or researchers in business analytics, predictive analytics and decision tree as it presents recent evidence of the applications of various fields. This review will be in the interest of academics and practitioners in business analytics, especially predictive analytics.

show abstract

A probabilistic approach to information management of order fulfilment reliability with the help of perfect-order analytics

Lukinskiy

Ivanov

et al. 2023

International Journal of Information Management

View full text Add to dashboard Cite

Proactive decision making in supply chain procurement

Cited by 6 publications

References 58 publications

Conceptualizing Supply Chain Resilience: The Role of Complex IT Infrastructures

Conceptualizing Supply Chain Resilience: The Role of Complex IT Infrastructures

Predictive Analytics in Business Analytics: Decision Tree

A probabilistic approach to information management of order fulfilment reliability with the help of perfect-order analytics

Contact Info

Product

Resources

About