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Managers are increasingly looking to adopt the Internet of Things (IoT) to include the vast amount of big data generated in their decision-making processes. The use of IoT might yield many benefits for organizations engaged in civil infrastructure management, but these benefits might be difficult to realize as organizations are not equipped to handle and interpret this data. The purpose of this paper is to understand how IoT adoption affects decision-making processes.

In this paper the changes in the business processes for managing civil infrastructure assets brought about by IoT adoption are analyzed by investigating two case studies within the water management domain. Propositions for effective IoT adoption in decision-making processes are derived.

The results show that decision processes in civil infrastructure asset management have been transformed to deal with the real-time nature of the data. The authors found the need to make organizational and business process changes, development of new capabilities, data provenance and governance and the need for standardization. IoT can have a transformative effect on business processes.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the propositions further.

The paper shows that data provenance is necessary to be able to understand the value and the quality of the data often generated by various organizations. Managers need to adapt new capabilities to be able to interpret the data.

This paper fulfills an identified need to understand how IoT adoption affects decision-making processes in asset management in order to be able to achieve expected benefits and mitigate risk.

This work is part of a research project that seeks to gain insight into the applicability of different actor analysis methods. This paper aims to describe the analysis of the predictive value of two different actor analysis methods applied to the redesign of the water management of a Dutch polder.

The paper's approach is a parallel application and comparison of the results of two separate actor analysis methods: conflict analysis and transactional analysis.

Transactional analysis was more accurate regarding the prediction of the real world outcomes than conflict analysis.

The choice of analysis method may be of significant influence on the quality of understanding of the risks involved with different stakeholders. There may not be a single silver bullet.

An asset manager needs to apply multiple actor analysis techniques to fully grasp the impact of the threats posed by the stakeholders on the asset and its risk register.

The parallel application of the two methods and comparison of their predictive value is new.

The adoption of the Internet of Things (IoT) as a new technology is gaining traction in many business organizations in developing countries. The purpose of this study is to assess the effect of IoT on the organizational performance of Tanzanian banks.

For data collection, this study used a quantitative approach with a questionnaire. A total of 342 respondents were considered, with an 82.16% response rate. AMOS software was used to analyze data using structural equation modeling (SEM) as the primary technique.

The results revealed that the majority of the hypotheses tested in this study have a significant effect on organizational performance, as indicated by their p-value of 0.05. However, there is no statistically significant effect of performance expectancy on organizational performance by lowering IoT operation costs. Furthermore, the availability of IoT has no discernible effect on organizational performance by improving service quality.

The findings of this study inform policymakers to reformulate information and communication technologies policy to clearly spell out the adoption and implementation of the IoT as a new technological innovation for providing services not only in the banking sector but also in other service delivery organizations. In particular, the policy should have a clear vision of implementing an appealing, conducive and positive, meaningful service delivery environment, as well as achieving appropriate, successful, effective and sustainable organizational performance

As a result, this paper contributes to a better understanding of the factors (including performance expectancy, effort expectancy and accessibility) of IoT on organizational performance by influencing operational costs, service delivery speed and service quality. These factors were not adequately addressed in previous related studies, and they have a significant influence on organizational performance levels in Tanzanian banks.