Ankur Kumar, Ambika Srivastava and Subhas C. Misra
The purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within…
Abstract
Purpose
The purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within the logistics industry. In addition, the moderating effect that the risk factor has on the technological, environmental and organizational factors regarding the implementation of IoT in logistics.
Design/methodology/approach
For the purpose of testing the models and hypotheses, a survey was carried out in order to collect the responses from currently employed individuals at various companies working in the field of logistics or IoT. For the purpose of analysis, the authors made use of the partial least squares structure equation model (PLS-SEM) technique.
Findings
Findings of this study concluded that technology- and environmental-related factors significantly affect the adoption of IoT in logistics, while risk acts as a moderator for the technological-related factor only in the adoption of IoT in logistics.
Research limitations/implications
The relevance of the authors' study lies in the growing importance of IoT in logistics and the need for logistics companies to understand the factors that impact the adoption of IoT in their operations. By identifying and analyzing the factors that influence IoT adoption in logistics, the authors' study provides valuable insights that can help logistics companies make informed decisions about whether and how to adopt IoT.
Practical implications
The research will help organizations make strategies for the successful adoption of IoT and ease the lives of all the stakeholders.
Originality/value
In this research, the authors attempted to find the factors that influence the adoption of IoT in logistics management. The influence of the technological, environmental, organizational and risk-related factors on the adoption of IoT in logistics management was studied. The moderating effect of risk over these factors on the adoption of IoT in logistics was also analyzed. This is original work and has never been done earlier.
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Frank Teuteberg, Martin Kluth, Frederik Ahlemann and Stefan Smolnik
The purpose of this paper is to illustrate and evaluate the semantic process benchmarking concept.
Abstract
Purpose
The purpose of this paper is to illustrate and evaluate the semantic process benchmarking concept.
Design/methodology/approach
The authors' approach includes the use of metamodels and ontologies, which make the process models syntactically and semantically comparable. Furthermore, a software prototype is presented to analyze and compare individual process models and their performance information. Thereafter, the technical, conceptual, and economic perspectives of the approach's evaluation are aligned with their respective outcomes.
Findings
The evaluation proves that this approach is generally suitable to generate novel and useful information on different process models and their performance within the same problem domain. However, the initial set‐up costs are high and will only pay off once process models are used regularly.
Practical implications
The proposed approach depends strongly on the availability of appropriate metrics and ontologies, as well as on the annotation of these ontologies to process models, which is a time‐consuming task. If large benchmarking clearing centers are established, the approach will be more cost‐effective. The developed SEMAT prototype, that demonstrates and proves the proposed approach's general viability, supports cost‐effective ontology engineering and annotation in the context of semantic process benchmarking initiatives.
Originality/value
To date, process benchmarking has primarily been a manual process. In this article, the authors suggest an approach that allows time‐consuming and costly process analysis to be partially automated, which makes the performance indicators, as well as qualitative differences between processes, apparent.
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Johannes Zrenner, Frederik Oliver Möller, Christian Jung, Andreas Eitel and Boris Otto
Current business challenges force companies to exchange critical and sensitive data. The data provider pays great attention to the usage of their data and wants to control it by…
Abstract
Purpose
Current business challenges force companies to exchange critical and sensitive data. The data provider pays great attention to the usage of their data and wants to control it by policies. The purpose of this paper is to develop usage control architecture options to enable data sovereignty in business ecosystems.
Design/methodology/approach
The architecture options are developed following the design science research process. Based on requirements from an automotive use case, the authors develop architecture options. The different architecture options are demonstrated and evaluated based on the case study with practitioners from the automotive industry.
Findings
This paper introduces different architecture options for implementing usage control (UC). The proposed architecture options represent solutions for UC in business ecosystems. The comparison of the architecture options shows the respective advantages and disadvantages for data provider and data consumer.
Research limitations/implications
In this work, the authors address only one case stemming from the German automotive sector.
Practical implications
Technical enforcement of data providers policies instead of relying on trust to support collaborative data exchange between companies.
Originality/value
This research is among the first to introduce architecture options that provide a technical concept for the implementation of data sovereignty in business ecosystems using UC. Consequently, it supports the decision process for the technical implementation of data sovereignty.