scholarly journals Creating customer value from data: foundations and archetypes of analytics-based services

2021 ◽  
Author(s):  
Fabian Hunke ◽  
Daniel Heinz ◽  
Gerhard Satzger
Keyword(s):  
Decision Making ◽  
Customer Value ◽  
Digital Transformation ◽  
Competitive Advantages ◽  
Detailed Characterization ◽  
Specific Service ◽  
Service Portfolio ◽  
Service Type

AbstractThe digital transformation offers new opportunities for organizations to expand their existing service portfolio in order to achieve competitive advantages. A popular way to create new customer value is the offer of analytics-based services (ABS)—services that apply analytical methods to data to empower customers to make better decisions and to solve complex problems. However, research still lacks to provide a profound conceptualization of this novel service type. Similarly, actionable insights on how to purposefully establish ABS in the market to enrich the service portfolio remain scarce. We perform a cluster analysis of 105 ABS and triangulate it with a revelatory case study to identify four generic ABS archetypes and to unveil their specific service objectives and characteristics. We also isolate essential factors that shape decision-making regarding the choice of adequate archetypes and subsequent transitions between them. The detailed characterization of different ABS types contributes to a more profound theorizing process on ABS as well as provides a systematization for strategic opportunities to enrich service portfolios in practice.

scholarly journals Using Pedotransfer Function (PTF) analysis in the assessment of the parameters of potential radionuclide transport through the vadose zone of PRAW “Novi Han” – an initial stage of a model case study

2019 ◽  
Vol 48 (2) ◽  
pp. 3-12
Author(s):  
Dimitar Antonov ◽  
Nikolay Stoyanov ◽  
Aleksey Benderev
Keyword(s):  
Vadose Zone ◽  
Hydraulic Parameters ◽  
Radionuclide Transport ◽  
Pedotransfer Function ◽  
Radionuclide Migration ◽  
Detailed Characterization ◽  
Model Case ◽  
Initial Stage

The Repository for Radioactive Waste in Novi Han, Lozen Mountain (Bulgaria), dates from the early 1960s. In the present study, the complex geoenvironmental setting of the repository site was analysed from the viewpoint of assessment of potential radionuclide migration from the repository to the geosphere. Thus, components of the mass transport field were elaborated as a part of a conceptual model. In connection with this, a detailed characterization of the subsurface, especially of the vadose zone around the repository, was performed. The fractions of sand, silt and clay based on the grain-size distribution curves of samples from the different hydrogeological units gathered on the site of RAW-Novi Han were implemented in the ROSETTA program, and the respective hydraulic parameters were determined. As a result, the entire vadose zone was hydraulically determined.

scholarly journals Consultants' Tools to Manage Digital Transformation

2021 ◽  
Vol 23 (4) ◽  
pp. 1-29
Author(s):  
Diana Claudia Cozmiuc ◽  
Richard Pettinger
Keyword(s):  
Value Creation ◽  
Digital Technology ◽  
Customer Value ◽  
Business Models ◽  
Digital Transformation ◽  
Maturity Stage ◽  
Instrumental Case Study ◽  
Service Business ◽  
Business Cases

Digital transformation since year 2010 has provided a huge worldwide market with digital consultants as top players. Digital transformation is a socio-economic phenomenon subject to lengthy surveys and actual cases on behalf of digital consultants between 2010-2020. By the end of the 2010s, digital transformation management has been reviewed in scientific journals. This is an instrumental case study about digital transformation at PWC, Siemens and Oracle as digital technology providers and consultants. Worldwide digital technology induces digital transformation with the purpose of value creation, motivating companies. Digital consultants are top players. Digital transformation frameworks and digital maturity studies show the dimensions, stages and scales of digital transformation. Roadmaps, programs, projects guide the specific steps from one maturity stage to the target. Business cases are used to compute customer value. Customer value is stipulated in customer contracts in as a service business models. Digital transformation solutions are marketed using these tools.

scholarly journals Consultants' tools to manage digital transformation - the case of PWC, Siemens and Oracle

2021 ◽  
Vol 23 (4) ◽  
pp. 0-0
Keyword(s):  
Value Creation ◽  
Digital Technology ◽  
Customer Value ◽  
Business Models ◽  
Digital Transformation ◽  
Maturity Stage ◽  
Instrumental Case Study ◽  
Service Business ◽  
Business Cases

Digital transformation since year 2010 has provided a huge worldwide market with digital consultants as top players. Digital transformation is a socio-economic phenomenon subject to lengthy surveys and actual cases on behalf of digital consultants between 2010-2020. By the end of the 2010s, digital transformation management has been reviewed in scientific journals. This is an instrumental case study about digital transformation at PWC, Siemens and Oracle as digital technology providers and consultants. Worldwide digital technology induces digital transformation with the purpose of value creation, motivating companies. Digital consultants are top players. Digital transformation frameworks and digital maturity studies show the dimensions, stages and scales of digital transformation. Roadmaps, programs, projects guide the specific steps from one maturity stage to the target. Business cases are used to compute customer value. Customer value is stipulated in customer contracts in as a service business models. Digital transformation solutions are marketed using these tools.

scholarly journals Physical Ergonomic Improvement and Safe Design of an Assembly Workstation through Collaborative Robotics

Safety ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 14
Author(s):  
Ana Colim ◽  
Carlos Faria ◽  
João Cunha ◽  
João Oliveira ◽  
Nuno Sousa ◽  
...  
Keyword(s):  
Working Conditions ◽  
Digital Transformation ◽  
Initial Condition ◽  
Manual Assembly ◽  
Collaborative Robotics ◽  
Furniture Manufacturing ◽  
Definition Of ◽  
Robotic Applications

One of the key interesting features of collaborative robotic applications is the potential to lighten the worker workload and potentiate better working conditions. Moreover, developing robotics applications that meets ergonomic criteria is not always a straightforward endeavor. We propose a framework to guide the safe design and conceptualization of ergonomic-driven collaborative robotics workstations. A multi-disciplinary approach involving robotics and ergonomics and human factors shaped this methodology that leads future engineers through the digital transformation of a manual assembly (with repetitive and hazardous operations) to a hybrid workstation, focusing on the physical ergonomic improvement. The framework follows four main steps, (i) the characterization of the initial condition, (ii) the risk assessment, (iii) the definition of requirements for a safe design, and (iv) the conceptualization of the hybrid workstation with all the normative implications it entails. We applied this methodology to a case study in an assembly workstation of a furniture manufacturing company. Results show that the methodology adopted sets an adequate foundation to accelerate the design and development of new human-centered collaborative robotic workstations.

A Combined Approach to Characterization of Dent With Metal Loss

2012 ◽  
Author(s):  
Rick Yahua Wang ◽  
Richard Kania ◽  
Udayasankar Arumugam ◽  
Ming Gao
Keyword(s):  
Mechanical Damage ◽  
Practical Experience ◽  
Metal Loss ◽  
Combined Approach ◽  
Detailed Characterization ◽  
Strain Limit ◽  
Study Results ◽  
Damage Criteria

Current in-line inspection technologies (e.g., Caliper/MFL or Combo) for mechanical damage characterization can detect dent with metal loss but with limited ability to discriminate metal loss between corrosion, gouge and crack with certainty. There are also some cases that metal loss signals were detected but not reported by ILI vendors because of either signals below threshold for reporting or other reasons. Practical experience showed that, with assistance of strain based dent analysis and strain limit damage criteria; detailed characterization of MFL tri-axial signals could effectively facilitate to discriminate metal loss features and identify potential risk of cracks or gouges in the dent. In this paper, the newly developed approach is utilized to identify the critical dents in the pipelines and discriminate those dents associated with metal loss reported by combined ILI technologies. A case study was performed with four real dent features, as an example to demonstrate the effectiveness of this approach. The details of the case study, results and findings are summarized in this paper.

scholarly journals Division of labour promotes the spread of information in colony emigrations by the ant Temnothorax rugatulus

2019 ◽  
Author(s):  
Gabriele Valentini ◽  
Naoki Masuda ◽  
Zachary Shaffer ◽  
Jake R. Hanson ◽  
Takao Sasaki ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Living ◽  
Division Of Labour ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Detailed Characterization ◽  
Group Members ◽  
Share Information ◽  
Colony Level

AbstractThe fitness of group-living animals often depends on how well members share information needed for collective decision-making. Theoretical studies have shown that collective choices can emerge in a homogeneous group of individuals following identical rules, but real animals show much evidence for heterogeneity in the degree and nature of their contribution to group decisions. In social insects, for example, the transmission and processing of information is influenced by a well-organized division of labour. Studies that accurately quantify how this behavioural heterogeneity affects the spread of information among group members are still lacking. In this paper, we look at nest choices during colony emigrations of the ant Temnothorax rugatulus and quantify the degree of behavioural heterogeneity of workers. Using methods from both machine learning and network analysis, we identify and characterize four behavioural castes of workers – primary, secondary, passive, and wandering – covering distinct roles in the spread of information during each emigration. This detailed characterization of the contribution of each worker can improve models of collective decision-making in this species and promises a deeper understanding of behavioural variation at the colony level.

scholarly journals Data Mining Approach Improving Decision-Making Competency along the Business Digital Transformation Journey: A Case Study – Home Appliances after Sales Service

SEEU Review ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. 45-65
Author(s):  
Hyrmet Mydyti
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Nearest Neighbor ◽  
Practical Implication ◽  
Absolute Error ◽  
Digital Transformation ◽  
Classification Algorithms ◽  
K Nearest Neighbor ◽  
Home Appliances

Abstract Data mining, as an essential part of artificial intelligence, is a powerful digital technology, which makes businesses predict future trends and alleviate the process of decision-making and enhancing customer experience along their digital transformation journey. This research provides a practical implication – a case study - to provide guidance on analyzing information and predicting repairs in home appliances after sales services business. The main benefit of this practical comparative study of various classification algorithms, by using the Weka tool, is the analysis of information and the prediction of repairs in the home appliances after sales services business. The comparison of algorithms is performed considering different parameters, such as the mean absolute error, root mean square error, relative absolute error and root relative squared error, receiver operating characteristic area, accuracy, Matthews’s correlation coefficient, precision-recall curve, precision, F-measure, recall and statistical criteria. Five classification algorithms such as the Naive Bayes, J48, random forest, K-Nearest Neighbor, and logistic regression were implemented in the dataset. J48 has proved to provide the best accuracy and the lowest error among the other examined algorithms applied to a home appliances after sales services dataset to predict repairs based on product guarantee period. The extracted information and results of an after sales services business by using data mining techniques prove to alleviate the process of streamlining decision-making and provide reliable predictions, especially for the customers, as well as increase businesses’ efficiency along their digital transformation journey.

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