Big Data Driven Supply Chain Design and Applications for Blockchain: An Action Research using Case Study approach

PurposeThis research aims at investigating the common practical problem of how procurement can be transformed from tactical and administrative to becoming an organizational strategic partner and indeed a competitive weapon, using modern technologies in particular. We investigated how procurement can be reinvented, from being digitized to digitalized to digitally integrated, ultimately contributing in business terms beyond supply chain effectiveness but also to profit generation.Design/methodology/approachA case study approach was designed to investigate three firms, each at very different stages of digital maturity in procurement. Interviews with managers, investigation of processes and documentary materials and in-depth follow-up discussions were conducted.FindingsThe iterative digitalization transformation discovered encompasses complexities rooted in organizational structure, supply chain design and the management of the technology for employees' uptake. There are both operations and strategy implications as a result. This initial research phase led to mapping a model of digital maturity as well as identifying its underlying constructs.Originality/valueThis research discovered that the implementation of digital technologies can lead the procurement function of the supply chain to completely grow out of its administrative and clerical shell into a strategic, consultative, value-adding and potentially revenue-generating function, thereby contributing to the well-being of not only the supply chain but also the entire organization.

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The Re-Conceptualization of the Port Supply Chain as a Smart Port Service System: The Case of the Port of Salerno

10.20944/preprints201704.0002.v1 ◽

2017 ◽

Cited By ~ 1

Author(s):

Antonio Botti ◽

Antonella Monda ◽

Marco Pellicano ◽

Carlo Torre

Keyword(s):

Supply Chain ◽

Service System ◽

Service Science ◽

Case Study Approach ◽

Study Approach ◽

Smart Service ◽

Comprehensive Framework ◽

Practical Implications ◽

Smart Port

This paper proposes a re-conceptualization of the port supply chain as a smart service system, according to the theory of the Service science. Starting from a short literature review about the port supply chain approach and the Service science, a new comprehensive framework is provided to better understand the seaport dynamics and the creation of competitive port supply chains. The methodology used is the case study approach. The authors examined the port of Salerno (Italy), and re-conceptualized it as a smart port service systems. Both theoretical and practical implications are provided to enrich the literature about the port supply chain and to support the port operators.

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Mitigating traceability risks amongst SMEs along the beef supply chain: A multiple case study approach to investigating the role and potential impact of information technology

10.5130/acis2018.bk ◽

2018 ◽

Author(s):

Mazino Amuno ◽

◽

Mohammad Sadegh Taskhiri ◽

Paul Turner ◽

◽

...

Keyword(s):

Information Technology ◽

Supply Chain ◽

Multiple Case Study ◽

Case Study Approach ◽

Study Approach ◽

Multiple Case ◽

Potential Impact ◽

Beef Supply Chain

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Data-Driven Inventory Management in the Healthcare Supply Chain

Supply Chain and Logistics Management ◽

10.4018/978-1-7998-0945-6.ch067 ◽

2020 ◽

pp. 1390-1403

Author(s):

Shuojiang Xu ◽

Kim Hua Tan

Keyword(s):

Big Data ◽

Supply Chain ◽

Inventory Management ◽

Data Driven ◽

Forecasting Model ◽

Market Demand ◽

Improved Model ◽

Future Work ◽

Statistic Approach

From 21st century, enterprises combine supply chain management with big data to improve their products and services level. In China healthcare industry, supply chain decisions are made based on experience, due to the environment complexities, such as changing policies and license delay. A flexible and dynamic big data driven analysis approach for supply chain decisions is urgently required. This report demonstrates a case study on CRT forecasting model of inventory data to predict the market demand based on pervious transaction data. First a basic statistic approach has been applied to represent the superficial patterns and suggest some decisions. After that a CRT model has been built based on the several independent variables. And there is also a comparison between CRT and CHAID models to choose a better one to further build an improved model. Finally some limitations and future work have been proposed.

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