Search results

The continuous redesign of processes is crucial for companies in times of tough competition and fast‐changing surrounding conditions. Since the manual redesign of processes is a time‐ and resource‐consuming task, automated redesign will increasingly become a useful alternative. Hence, future redesign projects need to be valuated based on both a manual and an automated redesign approach. The purpose of this paper is to compare the manual and automated process redesign on the basis of the Business Process Management (BPM) lifecycle.

In this paper, the authors compare the manual and automated process redesign on the basis of the Business Process Management (BPM) lifecycle. The results form the basis for a mathematical model that outlines the general economic characteristics of process redesign as well as for the manual and automated approaches. Subsequently, the authors exemplarily apply their model to a set of empirical data with respective assumptions on particular aspects of the automated approach.

In the problem setting described in the paper, the valuation model shows that automated process redesign induces an equal or higher number of optimized processes in a company. Therefore, the authors present a decision support that outlines how much to invest in automated process redesign.

The model considers the cost side of automated process redesign; therefore, further research should be conducted to analyze the possibility of higher returns induced by automated redesign (e.g., through a quicker adaption to real‐world changes). Moreover, for automated redesign, there is no requirement for broad empirical data that should be collected and analyzed as soon as this approach leaves the basic research and prototyping stages.

This paper presents an approach that can be used by companies to estimate the upper limit for investments in manual and automated process redesign. Working under certain general assumptions and independently from actual cost and return values, the paper demonstrates that automated process redesign induces an equal or higher ratio of optimized processes. Thus, companies introducing automated redesign cannot only apply the model to evaluate their investments but can also expect a higher ratio of optimized processes for this approach.

As existing literature primarily focuses on the technical aspects of automated process redesign, these findings contribute to the current body of literature. This paper discusses a first decision‐support for the economic aspects of automated process redesign, particularly with regard to the investments that are required for it. This information is relevant as soon as the approach leaves the stage of a prototype.

Automated valuation models have been in use at least for the last 50 years in both academia and practice, while automated valuation recently re-emerged as very important with the rise of digital infrastructure. The current state of the art, therefore, justifies the dual contributions of this paper: organising existing knowledge and providing a new framework.

This paper provides much-needed analysis and synthesis of the accumulated body of knowledge by proposing an updated classification of automated valuation approaches based on two criteria, and a taxonomy adapted to new trends. The latter requires a paradigm shift from models to automated valuation systems. Both classification and taxonomy arose after literature review.

This paper provides a framework for an explicit context under which automated valuation is carried out. To do so, authors propose a definition of automation valuation systems; contextualise the differences among theories, approaches, methods, models and systems present in automated valuation and introduce a classification of automated valuation approaches and a non-hierarchical taxonomy of automated valuation systems.

Perhaps, a systematic literature review process instead of a selective list of 100 references could additionally validate the proposed classification and taxonomy.

The new framework, underlying various dimensions of the automated valuation process, can help practitioners surpass judging models based purely on their predictive accuracy. Also, the automated valuation system is a more generic term that can better accommodate future research coming from a multitude of disciplines, more diverse business areas and enlarged variety of practical users.

This is the first paper that develops a taxonomy of automated valuation systems.

This research aims to argue that manual geometric modeling is blocking the building information modeling (BIM) promotion to small-size companies. Therefore, it is necessary to study a manner of automated modeling to reduce the dependence of BIM implementation on manpower. This paper aims to make a study into such a system to propose both its theory and prototype.

This research took a prototyping as the methodology, which consists of three steps: (1) proposing a theoretical framework supporting automated geometric modeling process; (2) developing a prototype system based on the framework; (3) conducting a testing for the prototype system on its performance.

Previous researches into automated geometric modeling only respectively focused on a specific procedure for a particular engineering domain. No general model was abstracted to support generic geometric modeling. This paper, taking higher level of abstraction, proposed such a model that can describe general geometric modeling process to serve generic automated geometric modeling systems.

This paper focused on only geometric modeling, skipping non-geometric information of BIM. A complete BIM model consists of geometric and non-geometric data. Therefore, the method of combination of them is on the research agenda.

The model proposed by this paper provide a mechanism to translate engineering geometric objects into textual representations, being able to act as the kernel of generic automated geometric modeling systems, which are expected to boost BIM promotion in industry.

The main purpose of this paper is to highlight the significance of service quality factors on customer retention within the Australian traditional and automated banking contexts.

The relative importance of traditional and automated service quality factors on customer retention was examined with the intention of determining which indicator factors are likely to have a significant impact on customer retention. The paper then proposes a conceptual model of the relationship between service quality factors within the two contexts and customer retention. AMOS 5 was used to test for the hypothesized relationships.

All of the traditional service quality factors have positively influenced customer retention. Conversely, this paper finds that automated service quality in general has no positive significant influence on customer retention.

This research was applied to the financial institutions in Queensland, Australia. Further testing of the proposed conceptual model across different industries and countries is needed to determine the generalisability and consistency of this study's findings.

The proposed model of retention prediction has the potential to help Australian bank managers to strengthen the customer‐bank relationship and, ultimately, to enhance customer retention ratios.

The key contribution of this paper is a conceptualisation of customer retention predictors that takes into account both traditional and automated service customer interactions with banks.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.

Several studies have addressed the use of four-dimensional (4D) building information modeling (BIM) for construction management. However, the automation of the processes for generating 4D models and their integrated use with Location-Based Planning and the Last Planner® System is not well discussed. Therefore, this paper aims to develop a method for automating the generation and use of 4D BIM models integrated with Location-Based Planning and Last Planner® System supporting project control cycles.

The research strategy adopted was Design Science Research. The automated method for using the 4D models was developed and refined in two residential building projects in Brazil, along with 31 meetings and involving 11 direct users. The assessment of the proposed method focuses on four constructs: the impact of process automation, the impact on the identification and assessment of site progress and the planning process, ease of adoption and utility of the proposed method.

The results of this paper indicated increased adherence between planned and executed through an automated method for using the 4D models. The established routines enabled automating the link between the planning levels and the three-dimensional (3D) model, providing a more agile and updated data source and achieving 92.8% of user satisfaction regarding the deadline and frequency of delivery of the 4D model reports. Moreover, this study identified the relationships between the processes of the method proposed and Digital Models.

The primary scientific value achieved in this study is creating a method for automating processes and simplifying steps for the generation and use of 4D BIM models in the production planning and control cycles during the construction phase.

The paper's purpose is to review the growth of computer supported valuation models and the increased access via information technology to property data in the world of property taxation. The paper aims to stimulate debate on what the short/medium term future may hold. Is there room for both traditional valuation surveying skills and computer mass appraisal models in the enlightened property taxation world, where transparency and access to property data is expected?

The paper compares and contrasts developments and trends in the use of automated valuation models (AVMs) across the world to assess property for local taxation purposes. It focuses in detail on three automated property taxation valuation systems of which the author has working knowledge and experience: Valuation Office Agency – Council Tax (Dwellings) and Non Domestic Rating (Commercial); Northern Ireland Valuation and Lands Agency – Domestic (Dwellings); Hong Kong Rating and Valuation Department (Dwellings and Commercial) property. The paper also considers the progress made in access to property data and data storage/retrieval.

Automated valuation programmes assist in the production of a valuation but its quality and accuracy are data and valuer led. One size does not fit all and there is no automated replacement for the subjective professional judgement of the valuer.

This paper considers the challenges, opportunities and possible problems when using computer driven valuation models for property taxation purposes.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

Assembly variations, which will propagate along the assembly process, are inevitable and difficult to analyze in Aeronautical Thin‐Walled Structures (ATWS) assembly. The purpose of this paper is to present a new method for analyzing the variation propagation of ATWS with automated riveting.

The paper addresses the variation propagation model and method by first, forming a novel Stage‐State model to represent the process of automated riveting. Second, the effect of positioning error on assembly variation is defined as propagation variation (PV), and propagation matrix of key characteristic points (KCP) is discussed. Third, the effect between the variations in each stage is defined as expansion variation (EV). According to the analysis of mismatch error and the reference transformation, the expansion matrix is formed.

The model can solve the variation propagation problem of ATWS with automated riveting efficiently, which is shown as an example of this paper.

The variation obtained by the model and method presented in this paper is in conformity with the variation measured in experiments.

The propagation variation and expansion variation is proposed for the first time, and variations are studied according to novel propagation matrix and expansion matrix.

Nowadays, building information modeling (BIM) represents an evolution in the architecture, engineering and construction (AEC) industries with its various applications. BIM is capable to store huge amounts of information related to buildings which can be leveraged in several areas such as quantity takeoff, scheduling, sustainability and facility management. The main objective of this research is to establish a model for automated schedule generation using BIM and to solve the time–cost trade-off problem (TCTP) resulting from the various scenarios offered to the user.

A model is developed to use the quantities exported from a BIM platform, then generate construction activities, calculate the duration of each activity and finally the logic/sequence is applied in order to link the activities together. Then, multiobjective optimization is performed using nondominated sorting genetic algorithm (NSGA-II) in order to provide the most feasible solutions considering project duration and cost. The researchers opted NSGA-II because it is one of the well-known and credible algorithms that have been used in many applications, and its performances were tested in several comparative studies.

The proposed model is capable to select the near-optimum scenario for the project and export it to Primavera software. A case study is worked to demonstrate the use of the proposed model and illustrate its main features.

The proposed model can provide a simple and user-friendly model for automated schedule generation of construction projects. In addition, opportunities related to the interface between an automated schedule generation model and Primavera software are enabled as Primavera is one of the most popular and common schedule software solutions in the construction industry. Furthermore, it allows importing data from MS Excel, which is used to store activities data in the different scenarios. In addition, there are numerous solutions, each one corresponds to a certain duration and cost according to the performance factor which often reflects the number of crews assigned to the activity and/or construction method.