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Case study research has been applied across numerous fields and provides an established methodology for exploring and understanding various research contexts. This paper aims to aid in developing methodological rigor by investigating the approaches of establishing validity and reliability.

Based on a systematic review of relevant literature, this paper catalogs the use of validity and reliability measures within academic publications between 2008 and 2018. The review analyzes case study research across 15 peer-reviewed journals (total of 1,372 articles) and highlights the application of validity and reliability measures.

The evidence of the systematic literature review suggests that validity measures appear well established and widely reported within case study–based research articles. However, measures and test procedures related to research reliability appear underrepresented within analyzed articles.

As shown by the presented results, there is a need for more significant reporting of the procedures used related to research reliability. Toward this, the features of a robust case study protocol are defined and discussed.

Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC projects.

A case study methodology was adopted, including individual case analyses and comparative multiple-case analyses.

The results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with “leveraging the diverse features of certain mature DT” being a shared recognition of all studied companies.

This research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service customization.

This research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.

In a highly competitive and globalised era, agile organisations proactively steer towards sustainability. This situation persuaded the organisations to align Quality Management (QM) initiatives to achieve sustainable outcomes. This study aims to explore quality–sustainability linkage, explicitly focusing on attaining the prestigious IAQ Quality Sustainability Award. Further it investigates, the impact of QM as a strategy for promoting sustainability to meet sustainable development goals (SDGs).

Due to the lack of substantial literature connecting QM to sustainability, the current research adopted an explanatory multiple-case study. Six cases were purposively chosen for the study. Three cases of those who have achieved the prestigious IAQ Quality Sustainability Award and remaining have been selected that have fallen short of receiving the award. A detailed within-case and cross-case examinations involving six cases that reported their QM achievements aligned with SDGs.

The findings demonstrate the significant role of QM adoption in achieving positive results from the perspective of SDGs, such as reduced environmental impacts, improved operational efficiency and enhanced quality of life. Effective stakeholder collaboration, proficiency in analytical tools and strategic alignment with SDGs emerged as critical success factors. Conversely, weak linkage with sustainability and unclear approaches were crucial challenges in attaining the IAQ Quality Sustainability Award.

This paper outlines essential commandments for organisations actively seeking to promote sustainability. It offers valuable insights for decision-makers, facilitating a profound understanding of the challenges and opportunities in pursuing sustainable performance.

The distinctive nature of this study lies in its dedicated exploration of the intricate relationship between QM deployment and its true impact on the achievement of the SDGs.

This study is exploratory in nature and designed to address poorly documented issues in the literature. The dimensions of regional distribution or spatial organisation of Industry 4.0 (I4.0), including the potential role of clusters, have only recently been addressed, with most available studies focusing on advanced, mainly Western European countries. Although developing fast, the literature on I4.0 in other countries, such as the Central and Eastern European or post-transition economies like Poland, needs to pay more attention to the spatial distribution or geographical and organisational aspects. In response to the identified knowledge gap, this paper aims to identify the role of clusters in the transformation towards I4.0. This explains why clusters may matter for advancing the fourth digital transformation, how advanced in implementing I4.0 solutions are the residents of Polish clusters and how they perceive the advantages of cluster membership for such implementation. Finally, it seeks to formulate policy recommendations based on the evidence gathered.

The methodology used in this study combines quantitative analysis of secondary data from a cluster benchmarking survey with a case study approach. The benchmarking survey, conducted by the polish agency for enterprise development in 2021, gathered responses from 435 cluster members and 41 cluster managers, representing an estimated 57% of the current clusters in Poland. In addition to quantitative analysis, a case study approach was used, incorporating primary sources such as interview with cluster managers and surveys of cluster members, as well as secondary sources like company documents and information from cluster organisation websites. Statistical analysis involved assessing the relationship between technology implementation and the adoption of management systems, as well as exploring potential correlations between technology use and company characteristics such as revenue, export revenue share and number of employees using Pearson correlation coefficient.

In Poland, implementing I4.0 technologies by cluster companies is still modest. The cluster has influenced the use of I4.0 technologies in 23% of surveyed companies. Every second surveyed company declared a positive impact of a cluster on technological advancement. The use of I4.0 technologies is not correlated with the revenue of clustered companies. A rather bleak picture emerges from the results, revealing a need for more interest among cluster members in advancing I4.0 technologies. This may be due to a comfortable situation in which firms still enjoy alternative competitive advantages that do not force them to seek new advanced advantages brought about by I4.0. It also reflects the sober approach and awareness of associated high costs and necessary investments, which are paramount and prevent successful I4.0 implementation.

The limitations inherent in this study reflect the scarcity of the available data. This paper draws on the elementary survey administered centrally and is confined by the type of questions asked. The empirical section focuses on an important, though only one selected sector of the economy – the automotive industry. Nevertheless, the diagnosis of the Polish cluster’s role in advancing I4.0 should complement the existing literature.

The exploratory study concludes with policy recommendations and sets the stage for more detailed studies. Amidst the research’s limitations, this study pioneers a path for future comprehensive investigations, enabling a deeper understanding of Polish clusters’ maturity in I4.0 adoption. By comparing the authors’ analysis of the Polish Automotive Group (PGM) cluster with existing literature, the authors uncover a distinct disparity between the theoretical prominence of cluster catalysis and the current Polish reality. Future detailed dedicated enquiries will address these constraints and provide a more comprehensive map of Polish clusters’ I4.0 maturity.

This study identifies patterns of I4.0 implementation and diagnoses the role of clusters in the transformation towards I4.0. It investigates how advanced is the adoption of I4.0 solutions among the residents of Polish clusters and how they perceive the advantages of cluster membership for such transformation. Special attention was paid to the analysis of the automotive sector. Comparing the conclusions drawn from the analysis of the Polish PGM cluster in this case study to those from the literature on the subject, it becomes clear that the catalytic role of clusters in the implementation of I4.0 technologies by enterprises, as emphasised in the literature, is not yet fully reflected in the Polish reality.

Present study aimed to integrate Geographic Information Systems (GIS) and Building Information Modeling (BIM) in conjunction with multicriteria decision-making (MCDM) to enhance infrastructure investment planning.

This analysis combines GIS databases with BIM simulations for a novel highway project. Around 150 potential alternatives were simulated, narrowed to 25 more effective routes and 3 options underwent in-depth analysis using PROMETHEE method for decision-making, based on environmental, cost and safety criteria, allowing for comprehensive cross-perspective comparisons.

A comprehensive framework proposed was validated through a case study. Demonstrating its adaptability with customizable parameters. It aids decision-making, cost estimation, environmental impact analysis and outcome prediction. Considering these critical factors, this study holds the potential to advance new techniques for assessment and planning railways, power lines, gas and water.

The study acknowledges limitations in GIS data quality, particularly in underdeveloped areas or regions with limited technology access. It also overlooks other pertinent variables, like social, economic, political and cultural issues. Thus, conclusions from these simulations may not entirely represent reality or diverse potential scenarios.

The proposed method automates decision-making, reducing subjectivity, aids in selecting effective alternatives and considers environmental criteria to mitigate negative impacts. Additionally, it minimizes costs and risks while demonstrating adaptability for assessing diverse infrastructures.

By integrating GIS and BIM data to support a MCDM workflow, this study proposes to fill the existing research gap in decision-making prioritization and mitigate subjective biases.

India liberalized its economy in 1991, which resulted in intense global competition, quality-conscious and demanding customers. Additionally, significant technological advancements lead to enhancements in products and processes. These forced Indian organizations to adopt innovative business strategies in the past 30 years. Meanwhile, the Lean Six Sigma methodology has significantly grown with vast applicability during the past 30 years. Thus, the purpose of this study is to develop the learning on Lean Six Sigma methodology in the Indian context through investigation of literature.

A three-stage systematic literature review approach was adopted to investigate the literature during the present study. In total, 187 articles published in 62 journals/conference proceedings from 2005 to 2022 (18 years) were shortlisted. The first part of the article summarizes the significant milestones towards the quality journey in the Indian context, along with the evolution of the Lean Six Sigma methodology. The second part examines the shortlisted papers on Lean Six Sigma frameworks, their applicability in industrial sectors, performance metrics, outcomes realized, publication trends, authorship patterns and leading researchers from the Indian perspective.

Lean Six Sigma has emerged as a highly acclaimed and structured business improvement strategy worldwide. The Indian economy has seen remarkable growth in the past decade and is one of the fastest-growing economies in the 21st century. Lean Six Sigma implementation in India has significantly increased from 2014 onward. The study revealed that researchers have proposed several different frameworks for Lean Six Sigma implementation, the majority of which are conceptual. Furthermore, the balanced applicability of Lean Six Sigma in manufacturing and service sectors was observed with the highest implementation in the health-care sector. Additionally, the widely adopted tools, techniques along with performance metrics exploring case studies were reported along with a summary of eminent and leading researchers in the Indian context.

This study is confined to reviewed papers as per the research criteria with a significant focus on the Indian context and might have missed some papers due to the adopted papers selection strategy.

The present study is one of the initial attempts to investigate the literature published on Lean Six Sigma in the Indian context, including perspective on the Indian quality movement. Therefore, the present study will provide an understanding of Lean Six Sigma methodology in the Indian context to graduating students in engineering and management and entry-level executives. The analysis and findings on Lean Six Sigma frameworks, research approach, publications details, etc., will be helpful to potential research scholars and academia. Additionally, analysis of case studies on Lean Six Sigma implementation by Indian industries will assist the managers and professionals in decision making.

Focusing on critical discourse analysis, this paper aims to propose a framework for analysing the way activist anti-tourism groups construct their social action of protest. The authors argue that activist groups use different narrative strategies to construct and legitimise their discourse of protest to convey social meanings for social action practices. This study represents an attempt to explain how anti-tourism activist groups have the agency to build different paradigms of protest rooted in particular views of tourism.

As a result of the lack of research in this area, this study used a comparative case study methodology drawn on four case studies in the field of anti-tourism protest. Case study is deemed adequate to explore a complex social phenomenon, how activist groups differ from each other, in a specific socio-economic context. A critical discourse analysis method is used to study primary (interviews) and secondary sources (reports, websites and online campaigns documents) of information, which express the activist group motivations and objectives to protest against tourism.

This study’s findings provide evidence in how discourse differs among the protest groups. Three narrative paradigms of protest are identified, which guide their agency: scepticism, based on a global and ecological approach; non-interventionist transformation, rooted in local community issues; and direct transformation, based on a sectoral problem-solving approach. These differences are interpreted as the consequences of the emergence and the development of different paths of protest according to specific social contexts and power relations in which anti-tourism groups are embedded.

This paper provides a contemporary approach to anti-tourism activism within the context of social movements. This case study may be of interest to practitioners and international destination managers interested in gaining a better understanding of anti-tourism protest strategies, new anti-tourism narratives following COVID-19 and the opportunities and challenges for opening a dialogue with those involved in activism and social urban movements as part of sustainable tourism governance. Our results can also help activists to rethink how they integrate differences and particular strategic positions to avoid hindering collective action. This knowledge is especially useful for managers and authorities seeking to develop more accurate collaborative governance practices with local activists, and especially those interested in fostering participative action without marginalising the diverse range of local community perspectives.

The purpose of this paper is to identify and analyze the interdependence of project complexity factors (PCFs) in metro rail projects using the Decision-Making Trial and Evaluation Laboratory (DEMATEL). The study provides qualitative and quantitative analysis of project complexities factors and their relationships. The results of the study facilitate effective project planning, proactive risk management and informed decision-making by stakeholders.

This study employs a case-based method for identifying PCFs and a DEMATEL method for analyzing the interdependence of complexity factors in metro rail projects. Initially, PCFs were identified through an extensive literature review. To validate and refine these factors, semi-structured interviews were conducted with thirty experienced professionals, each having 5–20 years of experience in roles such as project management, engineering, and planning. Further, elevated and underground metro rail projects were purposefully selected as cases, for identifying the similarities and differences in PCFs. A questionnaire survey was conducted with various technical experts in metro rail projects. These experts rated the impact of PCFs on a five-point Likert scale, for the evaluation of the interdependence of PCFs. The DEMATEL technique was used to analyze the interdependencies of the PCFs.

Metro rail projects are influenced by project complexity, which significantly impacts their performance. The analysis reveals that “design problems with existing structures,” “change in design or construction” and “land acquisition” are the key factors contributing to project complexity.

The study of project complexity in metro rail projects is limited because most of the studies have studies on examining complexity in mega projects. The existing literature lacks adequate attention in identifying project complexity and its effects on metro rail project performance. This research aims to bridge this gap by examining project complexity and interdependencies in metro rail projects.

Lean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.

A literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.

The implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.

Reviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.

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.