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The purpose of this paper is to demonstrate that process verification has matured to a level where it can be used in practice. This paper reports on new verification techniques that can be used to assess the correctness of real‐life models.

The proposed approach relies on using formal methods to determine the correctness of business processes with cancellation and OR‐joins. The paper also demonstrates how reduction rules can be used to improve the efficiency. These techniques are presented in the context of the workflow language yet another workflow language (YAWL) that provides direct support for 20 most frequently used patterns found today (including cancellation and OR‐joins). But the results also apply to other languages with these features (e.g. BPMN, EPCs, UML activity diagrams, etc.). An editor has been developed that provides diagnostic information based on the techniques presented in this paper.

The paper proposes four properties for business processes with cancellation and OR‐joins, namely: soundness, weak soundness, irreducible cancellation regions and immutable OR‐joins and develop new techniques to verify these properties. Reduction rules have been used as a means of improving the efficiency of the algorithm. The paper demonstrates the feasibility of this verification approach using a realistic and complex business process, the visa application process for general skilled migration to Australia, modelled as a YAWL workflow with cancellation regions and OR‐joins.

Business processes sometimes require complex execution interdependencies to properly complete a process. For instance, it is possible that certain activities need to be cancelled mid‐way though the process. Some parallel activities may require complex “wait and see” style synchronisation depending on a given context. These types of business processes can be found in various domains, such as application integration, B2B commerce, web service composition and workflow systems. Even though cancellation and sophisticated join structures are present in many business processes, existing verification techniques are unable to deal with such processes. Hence, this paper plays an important role in making process verification a reality.

Process mining (PM) specialises in extracting insights from event logs to facilitate the improvement of an organisation's business processes. Industry trends show the proliferation and continued growth of PM techniques. To address the minimal attention given to developing empirically supported frameworks to assess the nature of impact in the PM domain, this study proposes a framework that identifies the key categories of PM impacts and their interrelationships.

The qualitatively derived framework is built, re-specified and validated from a diverse collection of 62 PM case reports. With multiple rounds of coding supported by coder corroborations, inductively extracted concepts relating to impact from a first set of 12 case reports were grouped into themes and sub-themes to derive an a-priori framework by adopting the balanced scorecard as a theoretical lens. Concepts from the remaining 50 case reports were deductively grouped to re-specify and validate the proposed PM impacts framework. Further analysis identified interrelationships between impacts, which extends our understanding of the identified PM impacts.

The proposed framework captures PM impacts in four main categories: (a) impact on the process, (b) customer impact, (c) financial impact, and (d) impact on innovation and learning. The authors extended this analysis to identify the interrelationships between these categories, which vividly demonstrates how impact on the process mediates the attainment of the other three impact types.

The need for a deeper understanding of PM impacts within the context of contemporary PM practice is addressed by this work. The PM impacts framework provides a classification of PM impacts into four categories with 19 subcategories. It also identifies direct, moderating and mediating relationships between categories and subcategories whilst highlighting the role of impact on the process as a precursor to the other types of PM impact.

When improving business processes, process analysts can use data-driven methods, such as process mining, to identify improvement opportunities. However, despite being supported by data, process analysts decide which changes to implement. Analysts often use process visualisations to assess and determine which changes to pursue. This paper helps explore how process mining visualisations can aid process analysts in their work to identify, prioritise and communicate business process improvement opportunities.

The study follows the design science methodology to create and evaluate an artefact for visualising identified improvement opportunities (IRVIN).

A set of principles to facilitate the visualisation of process mining outputs for analysts to work with improvement opportunities was suggested. Particularly, insights into identifying, prioritising and communicating process improvement opportunities from visual representation are outlined.

Prior work focuses on visualisation from the perspectives – among others – of process exploration, process comparison and performance analysis. This study, however, considers process mining visualisation that aids in analysing process improvement opportunities.

The need for assuring correctness of business processes in enterprises is widely recognised in terms of business process re-engineering and improvement. Formal methods are a promising approach to this issue. The challenge in business process verification is to create a formal model that is well-aligned to the reality. Process mining is a well-known technique to discover a model of a process based on facts. However, no studies exist that apply it to formal verification. This study aims to propose a methodology for formal business process verification by means of process mining, and attempts to clarify the challenges and necessary technologies in this approach using a case study.

A trading company simulation model is used as a case study. A workflow model is discovered from an event log produced by a simulation tool and manually complemented to a formal model. Correctness requirements of both domain-dependent and domain-independent types of the model are checked by means of model-checking.

For business process verification with both domain-dependent and domain-independent correctness requirements, more advanced process mining techniques that discover data-related aspects of processes are desirable. The choice of a formal modelling language is also crucial. It depends on the correctness requirements and the characteristics of the business process.

Formal verification of business processes starting with creating its formal model is quite new. Furthermore, domain-dependent and domain-independent correctness properties are considered in the same framework, which is also new. This study revealed necessary technologies for this approach with process mining.

In line with the noticeable trend toward automation in internal audit functions, and considering Saudi Arabia’s Vision 2030, which prioritizes technological innovation, the purpose of this study is to explore the adoption of robotic process automation (RPA) within the KSA’s various sectors of internal auditing domain, with a particular emphasis on understanding the challenges and evaluating the impact on audit efficiency.

Using a quantitative research design, this study uses a bootstrapping approach and partial least squares structural equation modeling (PLS-SEM) to meticulously analyze data collected from 138 certified internal auditors around KSA.

This study reveals associations between the regulatory environment, data security, vendor reputation, intention to adopt RPA and internal audit efficiency.

The study findings offer valuable insights for auditors, policymakers and industry practitioners involved in RPA adoption initiatives. The organizations can use these results to develop informed strategies for navigating the challenges and maximizing the benefits of RPA implementation in internal audit functions.

This study contributes significantly to the existing literature by delving into the adoption of RPA, with a particular emphasis on understanding the challenges and evaluating the impact on audit efficiency, specifically in the context of KSA – an area that has not been extensively studied.

The purpose of this paper is to present a new heuristic approach for finding errors and possible improvements in business process models.

First, the paper translates the information that is included in a model into a set of Prolog facts. It then searches for patterns which are related to a violation of the soundness property or bad modeling style or otherwise gives rise to the assumption that the model should be improved. To validate this approach, the paper analyzes a repository of almost 1,000 business process models. For this purpose, three different model‐checkers that explore the state space of all possible executions of a model are used. The result of these tools are compared with the results given by this heuristic approach.

The paper finds that the heuristic approach identifies violations of the soundness property almost as accurate as model‐checkers. However, other than these tools, the approach never ran into state space explosion problems. Furthermore, this heuristic approach can also detect patterns for bad modeling style which can help to improve the quality of models.

Heuristic checks can run in the background while the modeler works on the model. In this way, feedback about possible modeling errors can be provided instantly. This feedback can be used to correct possible problems immediately.

Current Prolog‐based validation tools check mainly for syntactical correctness and consistency requirements. This approach adds one more perspective by also detecting control‐flow errors (like deadlocks) and even pragmatic issues.

The significance of business processes has fostered a close collaboration between academia and industry. Moreover, the business landscape has witnessed continuous transformation, closely intertwined with technological advancements. Our main goal is to offer researchers and process analysts insights into the latest developments concerning artificial intelligence (AI) and machine learning (ML) to optimize their processes in an organization and identify research gaps and future directions in the field.

In this study, we perform a systematic review of academic literature to investigate the integration of AI/ML in business process management (BPM). We categorize the literature according to the BPM life-cycle and employ bibliometric and objective-oriented methodology to analyze related papers.

In business process management and process map, AI/ML has made significant improvements using operational data on process metrics. These developments involve two distinct stages: (1) process enhancement, which emphasizes analyzing process information and adding descriptions to process models and (2) process improvement, which focuses on redesigning processes based on insights derived from analysis.

While this review paper serves to provide an overview of different approaches for addressing process-related challenges, it does not delve deeply into the intricacies of fine-grained technical details of each method. This work focuses on recent papers conducted between 2010 and 2024.

This work addresses a significant gap by employing a pioneering approach to introduce challenges in BPM alongside AI/ML techniques and integrated tools. Hence, it offers comprehensive guidelines that elucidate the alignment between ML methods and solutions to current challenges across the BPM life-cycle, including process enhancement and process improvement. Additionally, by detailing various aspects of the life-cycle phases and highlighting ML technique characteristics, this research demonstrates potential approaches for future exploration, thereby enhancing applicability for both process analysts and researchers in this context.

New methods have been introduced as revolutionary approaches in the construction industry, such as off-site manufacturing (OSM) and building information modelling (BIM). Although these approaches can provide many benefits, there are still barriers to meeting the expectations of improved construction productivity via their implementation. Hence, the purpose of this paper is to critically review the capabilities of OSM and BIM techniques, as well as their potential interactions, in productivity improvement.

A scoping review approach was adopted, where 100 peer-reviewed journal articles were collected to analyse the capabilities of OSM and BIM, as well as their potential interactions, in productivity improvement as assessed by key productivity indicators (KPrIs).

The results reveal seven BIM-based capabilities and six OSM-based capabilities, as well as 12 potential OSM–BIM interactions that have significant potential for satisfying KPrIs.

An integrated framework has also been developed to clarify and conceptualise the roles of OSM–BIM interactions in their designated KPrIs. The research has developed insightful and practical references for strategic planning and management in OSM–BIM-based projects.

The purpose of this paper is to integrate business process management (BPM) and accounting on a conceptual level in order to account for the economic implications of process-state changes in process design-time and process run-time.

The paper adopts a design science research paradigm. The research, grounded in an “events” approach to accounting theory, builds on the REA accounting model that has been adapted for the design of a process accounting model (PAM).

The paper presents a PAM that can be used to structure event records in process-aware information systems (PAIS) to enable process-oriented accounting. The PAM is specified as a light weight data structure that is intended for the integration of PAIS and accounting information systems.

As this paper is technical in nature, more research is needed to evaluate more thoroughly its approach in naturalistic settings.

The PAM can support traditional accounting approaches, and because of the adopted events approach, it readily supports use cases related to real-time analytics in BPM and accounting.

The PAM presents a novel approach to integrating BPM and accounting. The novelty of this approach lies in its use of event records to document flows of economic resources.

The purpose of this study is to systematically analyse and synthesise the existing research published on offsite manufacturing/construction. The study aims to highlight and associate the core elements for adopting the offsite concept in different construction contexts. This ultimately facilitates the enhancement of the offsite uptake.

The research study was carried out through a systematic literature review (SLR). The SLR was conducted to identify and understand the existing themes in the offsite research landscape, evaluate contributions and compile knowledge, thereby identifying potential directions of future research. The grand electronic databases were explored to gather literature on the offsite concept, lean and agile principles and simulation. A total of 62 related articles published between 1992 and 2015 have been included in this study. The relevant literature was systematically analysed and synthesised to present the emerging offsite themes.

The descriptive and thematic analyses presented in this paper have identified related offsite research studies that have contributed to setting a firm foundation of the offsite concept in different construction contexts. Each of the 62 articles was examined for achieving the aim and objectives of this study, the method of data collection and coverage of offsite themes. The results of the analyses revealed that the articles mostly provide information on the offsite concept and its definitions (53 per cent) and offsite barriers and/or drivers (27 per cent). However, limited attention has been paid to the integration of lean and agile principles (13 per cent) and simulation (7 per cent) within the offsite concept, which are therefore more open to research within the offsite concept.

The literature review highlights the main themes and components of the offsite construction concept. This forms a solid basis and motivation for researchers and practitioners to build on to enhance the uptake of the offsite concept in different contexts. This study also presents a research roadmap within the offsite concept, along with a recommendation for further research to be conducted using the research framework proposed in this study. The framework could lead to validation of using simulation to integrate lean and agile principles within the offsite concept.

This paper presents a systematic review of the literature related to offsite construction in different contexts. The emerging components, that is, offsite definitions, drivers and/or barriers, lean and agile principles and simulation have been highlighted and discussed thematically. A research framework that enables pursuit of the integration of lean and agile principles offsite through the lens of simulation has been proposed. The framework is expected to open up new opportunities on the effectiveness of offsite development in different contexts.