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Operational excellence (OpEx) is a proven philosophy focusing on continuous improvement in processes and systems for superior performance and efficiency. It plays a crucial role in the energy sector, acting as a catalyst for safety, customer satisfaction, sustainability and competitiveness. This research aims to assess OpEx methodologies in Oman’s energy sector, examining methods, approaches, motivations and sustainability.

This study applies qualitative analysis methodology, involving interviews with 18 industry experts, from the energy sector in a sizeable energy country.

The analysis revealed a growing demand, particularly, in the oil and gas industry, driven by emerging business needs. Qualitative data analysis has identified 10 themes such as implemented methodologies, motivation drivers, deployment approaches, sustainability factors, benefits and challenges. Additionally, new themes emerged, including influencers to start OpEx, resource requirements, enablers for successful OpEx and systems.

This research was limited to Oman and the findings drawn from Omani energy companies may have limited applicability to energy companies in other regions. Therefore, if these findings were to be used, the validation of the findings in relation to other countries should be conducted, to ensure the validity of the context and outcome.

These findings contribute to understanding OpEx dynamics in the Omani energy sector, offering valuable insights for effective utilisation and organisational goal achievement. Furthermore, the study offers valuable insights on how to effectively employ OpEx initiatives in the energy sector to achieve their goals and create value. It addresses the lack of knowledge, offers a framework for successful OpEx implementation, bridges the theory-practice gap and provides insights for optimal utilisation.

To the best of the authors’ knowledge, this is the first empirical study on assessing OpEx methodologies in the energy sector, and therefore it serves as a foundation for many future studies. The study provides a theoretical foundation for the OpEx methodologies in terms of organisational readiness for successful OpEx implementation.

The study aims to promote the use of qualitative methods in service research by investigating how these methods are reported in service journals, how the level of reporting has evolved and whether methodological reporting influences the downloads or citations received by qualitative articles.

Methodological reporting practices were identified through content analysis of 318 qualitative articles published in three major service research journals and comparison with prior methodological literature. Regression analysis was used to test how the level of methodological reporting influences article downloads and citations.

The study identifies 29 reporting practices related to 9 key methodological reporting areas. The overall level of methodological reporting in published qualitative articles has increased over time. While differences in the level of reporting between service journals persist, they are narrowing. The level of methodological reporting did not influence downloads or citations of qualitative articles.

Service scholars using qualitative methods should pay attention to methodological reporting as it can improve the chances of being published. Factors such as theoretical contributions are likely to have a greater influence on article impact than methodological reporting.

No prior study has explored methodological reporting practices across different qualitative methodologies or how reporting influences article impact. For authors, reviewers and editors, the study provides an inventory of reporting practices relevant for evaluating qualitative articles, which should lower barriers for qualitative methods in service research by providing practical guidelines on what to focus on when reporting and assessing qualitative research.

This study investigates Rokkan's research programme in the light of the differences between case- and variables-based methodologies. Three phases of the research process are distinguished. Studying the way Rokkan actually proceeded in the research within his Europe project, we find that he follows the protocols of case-methodologies such as grounded theory. In the second phase of the research process, however, he constructs variables-based models as tools for his macro-historical comparisons. To get to variables from the sensitizing concepts coded in the first phase, Rokkan defines his variables as close to cases as possible: variables as nominal level typologies, types as variable values. He thus faces two interrelated dilemmas. First, a philosophy of science dissonance: he legitimates his research only with reference to a variable-methodology, while his research is thoroughly case based. Second, a paradox of double coding: using variable-based models in the second phase, the status of the knowledge available in the first phase memos is degraded. Rokkan cannot decide between the two main solutions to these dilemmas: The first solution is to discard his heterogeneous data, instead working only with homogeneous data that opens up to more consistently variables-oriented research. The second solution is to replace the notion of variables/variable values with typology/types, thereby returning to cases, pursuing comparative case reconstructions in the third phase of research. The study concludes in favour of the second solution.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

This paper explores Lean Six Sigma principles and the DMAIC (define, measure, analyze, improve, control) methodology to propose a new Lean Six Sigma 4.0 (LSS 4.0) framework for employee occupational exams and address the real-world issue of high-variability exams that may arise.

This study uses mixed methods, combining qualitative and quantitative data collection. A detailed case study assesses the impact of LSS interventions on the exam management process and tests the applicability of the proposed LSS 4.0 framework for employee occupational exams.

The results reveal that changing the health service supplier in the explored organization caused a substantial raise in occupational exams, leading to increased costs. By using syntactic interoperability, lean, six sigma and DMAIC approaches, improvements were identified, addressing process deviations and information requirements. Implementing corrective actions improved the exam process, reducing the number of exams and associated expenses.

It is important to acknowledge certain limitations, such as the specific context of the case study and the exclusion of certain exam categories.

The practical implications of this research are substantial, providing organizations with valuable managerial insights into improving efficiency, reducing costs and ensuring regulatory compliance while managing occupational exams.

This study fills a research gap by applying LSS 4.0 to occupational exam management, offering a practical framework for organizations. It contributes to the existing knowledge base by addressing a relatively novel context and providing a detailed roadmap for process optimization.

This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

The various quality improvement (QI) frameworks and maturity models described in the health services literature consider some aspects of QI while excluding others. This paper aims to present a concerted attempt to create a quality improvement maturity model (QIMM) derived from holistic principles underlying the successful implementation of system-wide QI programmes.

A hybrid methodology involving a systematic review (Phase 1) of over 270 empirical research articles and books developed the basis for the proposed QIMM. It was followed by expert interviews to refine the core constructs and ground the proposed QIMM in contemporary QI practice (Phase 2). The experts included academics in two academic conferences and 59 QI managers from the New Zealand health-care system. In-depth interviews were conducted with QI managers to ascertain their views on the QIMM and its applicability in their respective health organisations (HOs).

The QIMM consists of four dimensions of organisational maturity, namely, strategic, process, supply chain and philosophical maturity. These dimensions progress through six stages, namely, identification, ad-hoc, formal, process-driven, optimised enterprise and finally a way of life. The application of the QIMM by the QI managers revealed that the scope of QI and the breadth of the principles adopted by the QI managers and their HOs in New Zealand is limited.

The importance of QI in health systems cannot be overstated. The proposed QIMM can help HOs diagnose their current state and provide a guide to action achieving a desirable state of quality improvement maturity. This QIMM avoids reliance on any single QI methodology. HOs – using the QIMM – should retain full control over the process of selecting any QI methodology or may even cherry-pick principles to suit their needs as long as they understand and appreciate the true nature and scope of quality overstated. The proposed QIMM can help HOs diagnose their current state and provide a guide to action achieving a desirable state of quality improvement maturity. This QIMM avoids reliance on any single QI methodology. HOs – using the QIMM – should retain full control over the process of selecting any QI methodology or may even cherry-pick principles to suit their needs as long as they understand and appreciate the true nature and scope of quality.

This paper contributes new knowledge by presenting a maturity model with an integrated set of quality principles for HOs and their extended supply networks.

This paper introduces a methodology to identify, analyse and represent heritage site attributes, emphasizing their impact on value, authenticity, integrity and management, with a case study on Ghadames, Libya. Inscribed in 1986 and moved to the In-Danger List in 2016 due to conflict, this work seeks to update the site's attributes and values for improved management.

This methodology, focusing on Ghadames, leverages recent heritage management advancements to monitor conflict-induced changes, aiming to enhance decision-making through a detailed analysis of the site's natural and cultural attributes.

Our findings highlight the need for systematic and holistic assessments of heritage site attributes and values, crucial for managing sites of both local and global significance. This approach is a key to understanding their identity, guiding interpretation, management and preserving cultural significance.

Developed for Ghadames, the methodology requires adaptation for other sites, underscoring the importance of identifying core tangible and intangible attributes that define a site's uniqueness.

Our developed methodology offers a replicable framework that can be modified by local heritage professionals to map attributes and assess the direct and indirect impact of conflict on heritage sites.

The detailed assessment provides a foundation for crafting informed policies and effective management strategies. It specifically targets minimizing the adverse effects of conflict on heritage sites' attributes. This effort is instrumental in preparing the necessary documentation to support the delisting of these sites from the UNESCO World Heritage Site In-Danger List, promoting their preservation and recovery.

This study aims to introduce and define the concept of phygital brand community (PBC). It discusses the potential conflicts that can arise from engaging in multiple PBCs and propose an enriched netnographic methodological approach to explore the role of PBC engagement overlap and its influence on the phygital experience.

Following a critical analysis of the inherent limitations of netnographic methodological approaches in the context of PBCs, this study develops an enriched netnographic research protocol that accounts for the challenges of engagement overlap among PBCs.

This study proposes two methods of analysis, namely, “participatory netnography” and “witness netnography,” which are derived from a mixed-methodology approach that integrates elements of netnography.

The findings of this study underscore the requisite methodological refinements imperative for enhancing netnographic analysis, particularly in its application for a better comprehension of individual behaviors within the realm of PBCs. In pursuit of this objective, the identified adjustments encompass ethical considerations, evaluation methods and their application in a digital milieu, where intricate mechanics and technologies frequently elude conventional methodologies.

In this study, the authors present a novel conceptualization of PBCs, highlighting their role and development, as well as the challenges they pose. To adequately capture the impact of PBC engagement overlap, the authors propose the need for an enriched mixed-methodological approach.

The purpose of this study is to examine the critical failure factors (CFFs) linked to various types of process improvement (PI) projects such as Kaizen, Lean, Six Sigma, Lean Six Sigma and Agile. Proposing a mitigation framework accordingly is also an aim of this study.

This research undertakes a systematic literature review of 49 papers that were relevant to the scope of the study and that were published in four prominent databases, including Google Scholar, Scopus, Web of Science and EBSCO.

Further analysis identifies 39 factors that contribute to the failure of PI projects. Among these factors, significant emphasis is placed on issues such as “resistance to cultural change,” “insufficient support from top management,” “inadequate training and education,” “poor communication” and “lack of resources,” as primary causes of PI project failures. To address and overcome the PI project failures, the authors propose a framework for failure mitigation based on change management models. The authors present future research directions that aim to enhance both the theoretical understanding and practical aspects of PI project failures.

Through this study, researchers and project managers can benefit from well-structured guidelines and invaluable insights that will help them identify and address potential failures, leading to successful implementation and sustainable improvements within organizations.

To the best of the author’s knowledge, this paper is the first study of its kind to examine the CFFs of five PI methodologies and introduces a novel approach derived from change management theory as a solution to minimize the risk associated with PI failure.