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In the last decade, the concept of Islamic attributes of destination (IAD) has emerged due to Muslim tourists’ need to visit a destination that complies with Sharia law. Since then, the IAD concept has been popular to increase the destination’s attractiveness and travel satisfaction for Muslim tourists. This concept evolved from evaluating the Muslim tourists’ perception of IAD to non-Muslim tourists and from assessing the Islamic attributes in Muslim-majority destinations to non-Muslim majority destinations. Furthermore, the literature showed several measurement scales to assess tourists’ satisfaction with IAD, and scholars were varied in the methods of analysis used to assess tourists’ satisfaction with IAD. The purpose of this study is to perform a systematic mapping study on satisfaction with IAD by answering five research questions.

This study used the preferred reporting items for systematic reviews and meta-analyses framework to guide the search process and search for relevant studies between 2012 and 2022 from two scientific databases, Scopus and Web of Science.

The search revealed 387 studies. In total, 31 articles met the eligibility criteria. This study indicates the journal considered research studies on tourists’ satisfaction with IAD the most, the method of analysis used in the previous studies, the Islamic destination attributes considered in the previous studies, the research distribution by counties, the research trend and the future direction.

To the best of the authors’ knowledge, this is the first systematic mapping study that delivers a summary of empirical research studies on tourists’ satisfaction with IAD.

European justice systems are facing a dramatic performance crisis due to the frequent inability to resolve cases without incurring unreasonable delays and backlogs. In this framework, the Italian Judicial system places itself well below the European countries average, in terms of speed of resolution of administrative, civil and criminal trials. The purpose of the paper was to (1) identify factors affecting Italian judicial system efficiency and (2) identify potential actions to manage them, improving judicial system efficiency.

In order to achieve the aims of this paper, a systematic review to map all critical factors discussed in previous studies was performed. Studies were extracted from Google Scholar, Web of Science and SSRN databases. In total, 22 studies were included.

The identified factors of inefficiency of the Italian judicial system have been divided into three macro-classes depending on whether they concern human resource management, the judicial process or whether they pertain to internal or external outside the judicial organization. For each of these, possible strategies have been developed in a new conceptual framework.

The framework seeks to assist policymakers in forming policy measures that can significantly increase court effectiveness. This is the first attempt to review and map all factors affecting judicial system efficiency systematically, providing a new conceptual framework to manage them.

This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.

The aim of this paper is to explore the possibility of using the Define-Measure-Analyze-Improve-Control (DMAIC) cycle, process mining (PM) and multi-criteria decision methods in an integrated way so that these three elements combined result in a methodology called the Agile DMAIC cycle, which brings more agility and reliability in the execution of the Six Sigma process.

The approach taken by the authors in this study was to analyze the studies arising from this union of concepts and to focus on using PM tools where appropriate to accelerate the DMAIC cycle by improving the first two steps, and to test using the AHP as a decision-making process, to bring more excellent reliability in the definition of indicators.

It was indicated that there was a gain with acquiring indicators and process maps generated by PM. And through the AHP, there was a greater accuracy in determining the importance of the indicators.

Through the results and findings of this study, more organizations can understand the potential of integrating Six Sigma and PM. It was just developed for the first two steps of the DMAIC cycle, and it is also a replicable method for any Six Sigma project where data acquisition through mining is possible.

The authors develop a fully applicable and understandable methodology which can be replicated in other settings and expanded in future research.

The application of integrated project delivery (IPD) in conjunction with building information modeling (BIM) and Lean Construction (LC) as the efficient method for improving collaboration and delivering construction projects has been acknowledged by construction academics and professionals. Once organizations have fully embraced BIM, IPD and LC integration, a measurement tool such as a maturity model (MM) for benchmarking their progress and setting realistic goals for continuous improvement will be required. In the context of MMs literature, however, no comprehensive analysis of these three construction management methods has been published to reveal the current trends and common themes in which the models have approached each other.

Therefore, this study integrates systematic literature review (SLR) and thematic analysis techniques to review and categorize the related MMs; the key themes in which the interrelationship between BIM, IPD and LC MMs has been discussed and conceptualized in the attributes; the shared characteristics of the existing BIM, IPD and LC MMs, as well as their strengths and limitations. The Preferred Reporting Items for Systematic Reviews (PRISMA) method has been used as the primary procedure for article screening and reviewing published papers between 2007 and 2022.

Despite the growth of BIM, IPD and LC integration publications and acknowledgment in the literature, no MM has been established that holistically measures BIM, IPD and LC integration in an organization. This study identifies five interrelated and overlapping themes indicative of the collaboration of BIM, IPD and LC in existing MMs' structure, including customer satisfaction, waste minimization, Lean practices and cultural and legal aspects. Furthermore, the MMs' common characteristics, strengths and limitations are evaluated to provide a foundation for developing future BIM, IPD and LC-related MMs.

This paper examines the current status of research and the knowledge gaps around BIM, IPD and LC MMs. In addition, the highlighted major themes serve as a foundation for academics who intend to develop integrated BIM, IPD, and LC MMs. This will enable researchers to build upon these themes and establish a comprehensive list of maturity attributes fulfilling the BIM, IPD and LC requirements and principles. In addition, the MMs' BIM, IPD and LC compatibility themes, which go beyond themes' intended characteristics in silos, increase industry practitioners' awareness of the underlying factors of BIM, IPD and LC integration.

This review article is the first of a kind to analyze the interaction of IPD, BIM and LC in the context of MMs in current AEC literature. This study concludes that BIM, IPD and LC share several joint cornerstones according to the existing MMs.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic data sets on air quality (AQ) predictions has not been fully investigated. This paper aims to investigate the effects traffic data set have on the performance of machine learning (ML) predictive models in AQ prediction.

To achieve this, the authors have set up an experiment with the control data set having only the AQ data set and meteorological (Met) data set, while the experimental data set is made up of the AQ data set, Met data set and traffic data set. Several ML models (such as extra trees regressor, eXtreme gradient boosting regressor, random forest regressor, K-neighbors regressor and two others) were trained, tested and compared on these individual combinations of data sets to predict the volume of PM_2.5, PM₁₀, NO₂ and O₃ in the atmosphere at various times of the day.

The result obtained showed that various ML algorithms react differently to the traffic data set despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%.

This research is limited in terms of the study area, and the result cannot be generalized outside of the UK as some of the inherent conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research, therefore, leaving out a few other ML algorithms.

This study reinforces the belief that the traffic data set has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form of traffic data set in the development of an AQ prediction model. This implies that developers and researchers in AQ prediction need to identify the ML algorithms that behave in their best interest before implementation.

The result of this study will enable researchers to focus more on algorithms of benefit when using traffic data sets in AQ prediction.

Insufficient productivity development in the global and Finnish infrastructure sectors indicates that there are challenges in genuinely achieving the goals of resource efficiency and digitalization. This study adapts the approach of capability maturity model integration (CMMI) for examining the capabilities for productivity development that reveal the enablers of improving productivity in the infrastructure sector.

Civil engineering in Finland was selected as the study area, and a qualitative research approach was adopted. A novel maturity model was constructed deductively through a three-step analytical process. Previous research literature was adapted to form a framework with maturity levels and key process areas (KPAs). KPA attributes and their maturity criteria were formed through a thematic analysis of interview data from 12 semi-structured group interviews. Finally, validation and refinement of the model were performed with an expert panel.

This paper provides a novel maturity model for examining and enhancing the infrastructure sector’s maturity in productivity development. The model brings into discussion the current business logics, relevance of lifecycle-thinking, binding targets and outcomes of limited activities in the surrounding infrastructure system.

This paper provides a new approach for pursuing productivity development in the infrastructure sector by constructing a maturity model that adapts the concepts of CMMI and change management. The model and findings benefit all actors in the sector and provide an understanding of the required elements and means to achieve a more sustainable built environment and effective operations.

Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.

This study aims to emphasize the integration of lean start-up and design thinking approaches and investigate how they may be used together.

The report uses a systematic literature review methodology to analyze and summarize previous research on combining lean start-up and design thinking. Inferences were discovered and analyzed after relevant publications were chosen based on predetermined inclusion criteria.

The research shows that combining lean start-up and design thinking significantly impacts entrepreneurship. Start-ups can efficiently uncover consumer needs, reduce risks and improve their product or service offerings by combining the client-centricity of design thinking with the iterative and data-driven concepts of lean start-up. This integration promotes an innovative culture, gives teams the freedom to try new things and learn from mistakes and raises the possibility of start-up success.

The dependence on pre-existing literature, which might cover only some potential uses and circumstances, is a weakness of this research. It is advised that more empirical research be conducted to determine the precise circumstances in which the integrated strategy performs best. Future studies should also explore the difficulties and drawbacks of using these approaches to offer suggestions for overcoming them and maximizing their advantages.

The findings have significant ramifications for business owners and other professionals working in the start-up environment. The combination of lean start-up and design thinking emphasizes the relevance of early customer interaction and empathy-driven design. To foster creativity and hasten the expansion of start-ups, practitioners are urged to create a comprehensive strategy that integrates the advantages of both techniques. Through this integration, business owners may develop solutions that appeal to their target market, increasing adoption rates and market competitiveness.

This study is interesting in comparing lean start-up and design thinking, emphasizing the overlaps and benefits of their application to entrepreneurship. This study discusses successful start-up methods by offering suggestions for future research and practice. It also provides a basis for further developing and adopting the integrated approach.

In recent years, the robotic process automation (RPA) technology has increasingly been used to automate business processes. While a lot of research has been published on the potential and benefits of the technology, only a few studies have conducted research on challenges related to RPA adoption. Hence, this study aims to identify and discuss challenges related to RPA implementation projects.

Following an inductive methodology, interviews have been conducted with consultants who were involved in multiple RPA implementation projects. Hence, their extensive experience and views contribute to a detailed and in-depth understanding of the phenomena under research.

The results suggest that there are various process-related, technical, resource-related, psychological and coordinative challenges that must be considered when conducting an RPA implementation project.

This paper contributes to knowledge by presenting a new typology of challenges, as well as providing an in-depth discussion of the individual challenges that organizations face.