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Port performance and port choice have been treated as separate streams of research. This hampers the efforts of ports to anticipate on and respond to possible future changes in port choice by shippers, freight forwarders and carriers. The purpose of this paper is to develop and demonstrate a port performance measurement methodology, extended from the perspective of port choice, which includes hinterland performance and a weighting of attributes from a port choice perspective.

A review of literature is used to extend the scope of port performance indicators. Multi-criteria decision analysis is used to operationalize the context of port choice, presenting a weighted approach using the Best-Worst Method (BWM). An empirical model is built based on an extensive port stakeholder survey.

Transport costs and times along the transport chain are the dominant factors for port competitiveness. Satisfaction, reputation and flexibility criteria are the other important decision criteria. The results also show how the availability of different modal alternatives impact on the position of a port. A ranking of routes for hinterland regions is done.

The paper focuses on two extensions of port performance measurement. So far, not all factors that determine port choice have been included in port performance studies. Here, first, factors related to hinterland services are included. Second, a weighting of port performance measures is proposed. The importance of factors is assessed using BWM. The approach is demonstrated empirically for a case of the European contestable hinterland regions, which so far have lacked quantitative analysis.

This study aims to deepen the understanding of how top managers reason about handling the relationships between quality of patient care, economy and professionals’ engagement.

Qualitative design. Individual in-depth interviews with all members of the executive management team at an emergency hospital in Norway were analysed using reflexive thematic method.

The top managers had the intention to balance between quality of patient care, economy and professionals’ engagement. This became increasingly difficult in times of high internal or external pressures. Then top management acted as if economy was the most important focus.

For health-care top managers to lead the pursuit towards increased sustainability in health care, there is a need to balance between quality of patient care, economy and professionals’ engagement. This study shows that this balancing act is not an anomaly top-managers can eradicate. Instead, they need to recognize, accept and deliberately act with that in mind, which can create virtuous development spirals where managers and health-professional communicate and collaborate, benefitting quality of patient care, economy and professionals’ engagement. However, this study builds on a limited number of participants. More research is needed.

Sustainable health care needs to balance quality of patient care and economy while at the same time ensure professionals’ engagement. Even though this is a central leadership task for managers at all levels, there is limited knowledge about how top managers reason about this.

In the context of the journey toward digital transformation and the realization of a fully connected factory, concepts such as data science, artificial intelligence (AI), machine learning (ML) and even predictive models emerge as indispensable pillars. Given the relevance of these topics, the present study focused on the analysis of customer complaint data, employing ML techniques to anticipate complaint accountability. The primary objective was to enhance data accessibility, harnessing the potential of ML models to optimize the complaint handling process and thereby positively contribute to data-driven decision-making. This approach aimed not only to reduce the number of units to be analyzed and customer response time but also to underscore the pressing need for a paradigm shift in quality management. The application of AI techniques sought to enhance not only the efficiency of the complaint handling process and data accessibility but also to demonstrate how the integration of these innovative approaches could profoundly transform the way quality is conceived and managed within organizations.

To conduct this study, real customer complaint data from an automotive company was utilized. Our main objective was to highlight the importance of artificial intelligence (AI) techniques in the context of quality. To achieve this, we adopted a methodology consisting of 10 distinct phases: business analysis and understanding; project plan definition; sample definition; data exploration; data processing and pre-processing; feature selection; acquisition of predictive models; evaluation of the models; presentation of the results; and implementation. This methodology was adapted from data mining methodologies referenced in the literature, taking into account the specific reality of the company under study. This ensured that the obtained results were applicable and replicable across different fields, thereby strengthening the relevance and generalizability of our research findings.

The achieved results not only demonstrated the ability of ML models to predict complaint accountability with an accuracy of 64%, but also underscored the significance of the adopted approach within the context of Quality 4.0 (Q4.0). This study served as a proof of concept in complaint analysis, enabling process automation and the development of a guide applicable across various areas of the company. The successful integration of AI techniques and Q4.0 principles highlighted the pressing need to apply concepts of digitization and artificial intelligence in quality management. Furthermore, it emphasized the critical importance of data, its organization, analysis and availability in driving digital transformation and enhancing operational efficiency across all company domains. In summary, this work not only showcased the advancements achieved through ML application but also emphasized the pivotal role of data and digitization in the ongoing evolution of Quality 4.0.

This study presents a significant contribution by exploring complaint data within the organization, an area lacking investigation in real-world contexts, particularly focusing on practical applications. The development of standardized processes for data handling and the application of predictions for classification models not only demonstrated the viability of this approach but also provided a valuable proof of concept for the company. Most importantly, this work was designed to be replicable in other areas of the factory, serving as a fundamental basis for the company’s data scientists. Until then, limited data access and lack of automation in its treatment and analysis represented significant challenges. In the context of Quality 4.0, this study highlights not only the immediate advantages for decision-making and predicting complaint outcomes but also the long-term benefits, including clearer and standardized processes, data-driven decision-making and improved analysis time. Thus, this study not only underscores the importance of data and the application of AI techniques in the era of quality but also fills a knowledge gap by providing an innovative and replicable approach to complaint analysis within the organization. In terms of originality, this article stands out for addressing an underexplored area and providing a tangible and applicable solution for the company, highlighting the intrinsic value of aligning quality with AI and digitization.

Many organizations currently transition towards digitalized process design, execution, control, assurance and improvement, and the purpose of this research is to empirically demonstrate how data-based operational excellence techniques are useful in digitalized environments by means of the optimization of a robotic process automation deployment.

An interpretive mixed-method case study approach comprising both secondary Lean Six Sigma (LSS) project data together with participant-as-observer archival observations is applied. A case report, comprising per DMAIC phase (1) the objectives, (2) the main deliverables, (3) the results and (4) the key actions leading to achieving the presented results is presented.

Key findings comprise (1) the importance of understanding how to acquire and prepare large system generated data and (2) the need for better large system-generated database validation mechanisms. Finally (3) the importance of process contextual understanding of the LSS project lead is emphasized, together with (4) the need for LSS foundational curriculum developments in order to be effective in digitalized environments.

This study provides a rich prescriptive demonstration of LSS methodology implementation for RPA deployment improvement, and is one of the few empirical demonstrations of LSS based problem solving methodology in industry 4.0 contexts.

The role of logistics service provider (LSP) is essential for efficient logistics service quality (LSQ) and supply chain management, especially in multimodal transport. Multimodal transport routes that use the Trans-Siberian Railway (TSR) play an important role in the supply chains of Northeast Asia. This paper aims to identify current conditions of TSR LSQ and propose improvements to enhance the competitiveness of traditional routes. Therefore, this study sheds light on and provides recommendations for various managerial strategies to LSPs in the context of the TSR. This study utilizes Importance-Performance Analysis (IPA) to measure levels of importance and performance of the logistics service of LSPs that provide multimodal transport services via the TSR from South Korea to Europe. This study identifies capabilities on the basis of five criteria (price, timeliness, reliability, equipment systems, and customer service) from a customers’ perspective. The results of the research indicate that operational improvements should be considered to activate TSR multimodal transport for northern logistics routes from the perspective of Korean shippers. Specific findings show that balanced development strategies are needed for logistics routes that have not yet been significantly activated, while implying that logistics costs could be reduced initially to satisfy shippers. This study presents an operational strategy for LSPs using the TSR in northern logistics through IPA methods. Furthermore, this research can help policymakers propose specific policies to revitalize the northern logistics of Korean logistics companies and to provide incentive supports for shippers.

There is a large amount of published literature on project management. However, there exists a gap between the existing literature and current practices in the industry for the development and execution of megaprojects. Existing literature generally focuses on individual elements applicable to project management in general. This article aims to provide an overview of the project management system components used in industrial megaprojects and identify the gaps between theory and practice, which can be used as input for further research on the topic.

The topic of megaproject management is reviewed based on available literature sources on megaproject management systems to identify the main gaps in the literature between theory and practice. Based on the findings, an analysis is provided to discuss the improvements required in distinct project management areas and phases.

There are multiple gaps associated with issues, failures, successes and challenges in industrial megaprojects. Improvements are needed in distinct management areas and over the entire project lifetime. Further guidelines are required for achieving improved megaproject management systems. Such concepts could benefit researchers and practitioners in streamlining their research toward the most relevant and critical areas of improvement of megaproject management systems.

This study addresses the literature gaps between theory and practices on megaproject management systems with an overview that provides helpful guidance for industrial applications and future research. A holistic analysis identifies gaps and critical drives in the body of knowledge, revealing avenues for future research focused on quality as the central pillar that affects the entire megaproject management system.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

The article presents the phenomenon of hazards related to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the food supply chain (FSC) by identifying possible stakeholders of a seafood company who might be influenced by the hazards.

A case study analysis was conducted with a review of the organization's documentation alongside a semi-structured interview and an impact effort matrix.

Seven out of 18 stakeholders had to strongly engage in minimizing the effects of hazards related to SARS-CoV-2. The most important areas of cooperation regarded safety were identified. Both external and internal documents and reports regarding the minimizing of negative effects of hazards related to SARS-CoV-2 were required by institutional clients, official authorities and the studied organization itself. The proper identification of stakeholders and up-to-date knowledge about them allowed the organization to react faster and protect the FSC.

The authors’ research was based on qualitative methods, so it lacked a diagnostic survey, along with similar studies for comparison of results and approaches.

The surveyed company may be a good benchmark for others to follow when choosing the appropriate approach in the field of stakeholder analysis for addressing new emerging risks.

The findings are important, timely and original, and they focus on a subject rarely studied in the literature. The information from the paper applies to numerous groups of food companies.

Despite many efforts within organizations toward business process orientation (BPO), research on real-world experiences remains in its infancy. The purpose of this paper is to redress the existing knowledge gap by analyzing a Swedish public housing company that has made notable effects regarding BPO and to explore lessons learned from the BPO journey (from 1998 to 2013).

The point of departure is principles in the BPO foundation, principles of successful BPM and effects in empirically based literature. The reconstruction of the narrative case study describes milestones and critical junctions, as well as effects based on quantitative and qualitative data.

Effects in BPO are demonstrated in terms of higher customer satisfaction, increased innovative ability, improved operational performance, higher employee satisfaction and, as a result of these, increased profitability. Theoretical constructs with implications for the theory building on BPO are suggested in a three-layer management framework – with capabilities and abilities emerging from the case study used as an illustrative example.

Lessons are learned regarding critical practices related to advancement in BPO. A strategy-building process based on eight design propositions is suggested to define the pre-conditions for BPO in an organization.

This is the first longitudinal case study to provide a comprehensive view and detailed insights of a BPO journey and top management performance toward a business process-oriented organization. Practitioners and BPM community get valuable insights into how the temporality and the context shape the BPO maturity process in terms of new organizational structure and roles during the journey.

This study aims to dispense a concrete and coherent picture on the role of digitalization of accounting information (DOAI) among the small and medium-sized enterprises (SMEs) through a statistically reliable and parsimonious paradigm for procuring the impact of DOAI on sustainable innovation ecosystem (SIE) and public value (PV) generation. With this cue, the geographical scope of this tentative manuscript was framed in SMEs of developing countries.

A three-pronged methodology was disposed in this research, namely, literature review, expert interviews and self-administered survey. Qualitative data was procured from a series of semi-structured in-depth interviews. The quantitative data was drawn on a self-administered survey in which the closed-ended questionnaires were conveniently circulated to a cross-sectional sample of 583 respondents. The data captured from quantitative approach was processed and analyzed via covariance-based structural equation modeling with AMOS 26.0.

The outcomes analysis highlighted that there were significant positive associations between the hypothesized constructs regarding significance and effect size. These interlinks were also partially mediated through the mediation of quality of information on financial reports and SIE.

This research was bounded by geographical provenance emphasis on one country and relative smallness of the data set procured through anonymous survey-based approach drawn from a convenient sample of digitally savvy respondents working in one sub-sector resulted in the reduction in the robustness and generalizability of the observations. Nevertheless, these above-mentioned limitations could thus offer the starting points for novel avenues creation for the future research.

The practitioners would definitely have valuable benefits from in-depth insights on the obtained findings. Concretely, as lifting the degree of understandings on the magnitude of long-term cooperation and superior coordination within the SIE would enable practitioners to enlarge their business viewpoints to better cope with the challenges of complicated business settings, facilitating them to co-create PV for all their key stakeholders through giving priority to implementing DOAI.

Society could benefit from this study if policymakers and the influencers of government focus on innovative features and assure the possible environment for innovation deployment through embarking on introducing policies that would facilitate the digitalization as well as stimulate and incentivize establishing the SIE for PV generation. It would be good for both the SMEs and society when SMEs could thrive in community settings as well as this togetherness.

Unpacking the potential of DOAI has been considered as the promising research avenues that are outlined not only to redress the shortfall in the research stream in relation to the digitalization among SMEs but also provide the right directions for sustainable development among SMEs.