Using Key Alignment Indicators for Performance Evaluation in Collaborative Networks

Francisco, Roberto da Piedade; Azevedo, Américo; Bastos, João; Almeida, António

doi:10.1007/978-3-642-23330-2_18

Cited by 4 publications

(3 citation statements)

References 15 publications

(13 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To build a single model that is capable of measuring the performance of all partners and the network, it is essential to use multi-criteria methods to support decisions that assist in the implementation of different elements that make up a performance measurement model for collaborative networks (Verdecho et al, 2010;2011;Ferreira et al, 2011aFerreira et al, , 2011bFrancisco et al, 2011;.…”

Section: Performance Management In Horizontal Business Networkmentioning

confidence: 99%

A measurement model for managing performance of horizontal business networks and a research case

Bonatto

Resende

Pontes

et al. 2017

Prod.

View full text Add to dashboard Cite

A significant challenge facing companies that are members of collaborative networks are measuring their market performance, even as they evaluate their contribution to the development of the network. This paper develops a model for analyzing the performance measurement of horizontal business networks. We do this by reviewing literature related to performance management in horizontal networks and systematically selecting eight functional perspectives, and 25 operational factors associated with them, to measure the performance of both companies and the network. We employ the Analytic Hierarchy Process (AHP) for deciding perspective weights and use its quantitative results to create a diagram for representing the effectiveness of performance management at the company and network level. The model is tested by applying it to companies in an Information Technology business network. We analyze the results of the individual and network performance of the companies surveyed, along with the evaluative perspectives relevant to the network.

show abstract

Section: Performance Management In Horizontal Business Networkmentioning

confidence: 99%

A measurement model for managing performance of horizontal business networks and a research case

Bonatto

Resende

Pontes

et al. 2017

Prod.

View full text Add to dashboard Cite

show abstract

“…Industrial machines and sensors from different vendors have different standardized protocols which can be challenging for data exchange and to align them in the CN. For that reason, this paper proposes a framework of connecting different robots and sensors with different protocols to increase the overall performance of the CN and to monitor performance of the robots [15].…”

Section: Introductionmentioning

confidence: 99%

Key Performance Indicators Integrating Collaborative and Mobile Robots in the Factory Networks

Aliev

Antonelli

Awouda

et al. 2019

Collaborative Networks and Digital Transformation

View full text Add to dashboard Cite

Measuring performances of collaborative robots in Industry 4.0 applications is an open research area since the emergence of collaborative and mobile robots as a support for semi-automatic manufacturing processes. A compelling management problem is the definition of convenient performance measures on which to assess the new generation of robots, to improve process performances both at the robotic cell design stage and at the production stage. A consequent problem is to gather the required data to measure performances. Data must be obtained automatically and in real time. Different levels of communication protocols have to be harmonized in order to transfer data from robots and other factory machines to the cloud on the internet and eventually to the production control system. A case study allows to demonstrate the operation of data acquisition system for collaborative and mobile robots and the real-time monitoring dashboard. The outcome of the study is the gathering of data at field level, the evaluation of robot performances at machine level in order to execute the real time production control at factory level.

show abstract

“…B [25] This paper proposes an approach that leads to the exploration of the performance prediction paradigm. Also, it develops tools to estimate and evaluate the performance and the degree of alignment by creating instances of future performance in collaborative networks.…”

mentioning

confidence: 99%

The Periodic Table of Industries: Detection of Collaboration Opportunities Based on an Imitation of the Mendeleev Periodic Table of Elements

Koura

Bénaben

Gou

et al. 2020

CSIMQ

View full text Add to dashboard Cite

The concept of collaborative networks has been encountered very often lately as the answer when trying to adapt and improve enterprises in these highly competitive business environments, therefore the urge for constantly addressing this topic. A lot of work-related to collaborative networks has been done so far, from defining network types to leveling partnerships and proposing models for partnership developments. But the lack of tackling a very important obstacle, which is the difficulty of detecting and anticipating collaboration opportunities between enterprises, inspired this research. In this article, a new theoretical opportunity detection approach is proposed based on enterprise characterization concept, KPI classification as well as collaboration types. This detection approach is a table of industrial classifications that imitates the Mendeleev periodic table from the concept point of view. A fictional example from an industrial context is shown to explain the usage of this approach accompanied by discussion about future work and limitations.

show abstract

Using Key Alignment Indicators for Performance Evaluation in Collaborative Networks

Cited by 4 publications

References 15 publications

A measurement model for managing performance of horizontal business networks and a research case

A measurement model for managing performance of horizontal business networks and a research case

Key Performance Indicators Integrating Collaborative and Mobile Robots in the Factory Networks

The Periodic Table of Industries: Detection of Collaboration Opportunities Based on an Imitation of the Mendeleev Periodic Table of Elements

Contact Info

Product

Resources

About