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As a problem-solving tool, the kaizen event (KE) is underutilised in practice. Assuming this is due to a lack of group process quality during those events, the authors aimed to grasp what is needed during high-quality KE meetings. Guided by the phased approach for structured problem-solving, the authors built and explored a measure for enriching future KE research.

Six phases were used to code all verbal contributions (N = 5,442) in 21 diverse, videotaped KE meetings. Resembling state space grids, the authors visualised the course of each meeting with line graphs which were shown to ten individual kaizen experts as well as to the filmed kaizen groups.

From their reactions to the graphs the authors extracted high-quality KE process characteristics. At the end of each phase, that should be enacted sequentially, explicit group consensus appeared to be crucial. Some of the groups spent too little time on a group-shared understanding of the problem and its root causes. Surprisingly, the mixed-methods data suggested that small and infrequent deviations (“jumps”) to another phase might be necessary for a high-quality process. According to the newly developed quantitative process measure, when groups often jump from one phase to a distant, previous or next phase, this relates to low KE process quality.

A refined conceptual model and research agenda are offered for generating better solutions during KEs, and the authors urge examinations of the effects of well-crafted KE training.

Organic food processing must include organic principles to be authentic. This qualitative study aims to understand the processors' understanding of organic food processing quality.

This study is based on semi-structured expert interviews with eight employees of six purely or partly organic dairies from Germany and Switzerland. Interview themes are (1) quality of organic milk processing in general, (2) assessment of specific processing techniques, (3) product quality of organic milk and (4) flow of information between producer and consumer. The interviews have been audio-recorded, transcribed verbatim and thematically analysed.

(1) Experts prefer minimal processing; some prefer artisanal processing, whilst others stress the advantages of mechanisation. (2) High temperature short time (HTST) pasteurisation and mechanical processing techniques are accepted; ultra-high-temperature (UHT) milk processing is partly rejected. (3) Traditional taste and valuable ingredients should be present in the final product. Natural variances are judged positively. (4) Consumers' low level of food technology literacy is challenging for communication.

The results cannot be generalised due to the qualitative study design. Further studies, e.g. qualitative case analyses and studies with a quantitative design, are necessary to deepen the results.

The paper shows which processing technologies experts consider suitable or unsuitable for organic milk. The paper also identifies opportunities to bridge the perceived gap between processors' and consumers' demands.

The study shows the challenges of processors in expressing the processors' understanding of process quality.

The purpose is to understand how the role of quality functions might evolve amidst digitalisation and an increased focus on services. This study focuses on customer feedback and how it can function as activation triggers for developing absorptive capacity, as well as how it relates to the value creation processes.

Following a qualitative research design, the authors gathered primary data from interviews with quality managers at 17 UK and Swedish firms and triangulated it with secondary information from the firms' web pages.

The findings show that customer feedback-based activation triggers can support development of absorptive capacity in the quality function if there are established processes for acting on customer feedback. This is often the case for codified feedback, which normally concerns products. However, digitalisation offers new opportunities of engaging in value co-creation, and firms need to develop digital capabilities to manage new technologies and data analytic tools. For personalised feedback (the main category of service-related feedback), established processes are missing.

This study work contributes to knowledge about how quality functions respond to customer feedback on both products and services. It clarifies why the quality function sometimes struggles to contribute to service quality as much as to product quality. From a theory development perspective, the authors contribute to understanding customer feedback-based activation triggers, how they lead to development of absorptive capacity and their relation to value co-creation on a functional level.

This article investigates the quality of stakeholder engagement (SE) process disclosure in the context of non-financial reporting (NFR) introduced by Directive 2014/95/EU (NFRD). SE implies the involvement of the subjects interested in the organization's activity, according to the principle of inclusiveness and the key concepts of the stakeholder theory (ST).

The authors conducted a content analysis on 75 non-financial statements (NFSs) published by companies listed on the Italian Stock Exchange in 2018 and 2021 to evaluate the evolutionary profiles of SE quality through the years.

The average level of SE is not significantly high. The research showed an overall poor quality of disclosure concerning stakeholders' key expectations and issues to be addressed and answered. Furthermore, a certain variability emerged in the quality of the disclosure between the various reports, and no significant improvements in SE quality were noted from 2018 to 2021.

The conclusions provide a replicable method for the analysis of SE quality in NFSs and the development of new standpoints in the ongoing debate on the implications of mandatory legislative frameworks for NFR. Content analyses intrinsically present margins of subjectivity. The sample was limited to a subset of NFS from Italy; hence, the results could be country specific.

This work suggests some possible ways of improvement of SE practices by companies.

Original assessment model based on eight variables identified from the academic literature and the most common international sustainability reporting standards. These variables were stakeholder identification, stakeholder selection process, degree of involvement, SE approach, dialogue channels, SE results, different points of view and integration of the SE process.

This study aims to investigate why and how shared service centres (SSCs) are implemented as well as how they affect audit firm practice and audit quality.

In this qualitative study guided by the theoretical framework of institutional theory, the authors conducted 25 semi-structured interviews in seven European countries, including 16 interviews with audit partners from Big 4 firms, 6 with audit team members, 2 with interviewees from second-tier audit firms and 1 with a member of an oversight body.

The authors show that the central rationale for audit firms to implement SSCs is economic rather than external legitimacy. The authors find that SSC implementation has substantial effects on audit practices, particularly those related to standardisation, coordination and monitoring activities. The authors also highlight the potential impacts on audit quality.

By exploring the motivation for and effects of SSC implementation amongst audit firms, the authors offer insights into the best practices related to subsequent change processes and audit quality.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

This study aims to investigate the relationships between firms’ strategic planning (SP), leadership and technology transfer competence (TTC) by specifically incorporating the mediating role of strategic quality management (SQM).

This study performs structural equation modeling using AMOS on survey data collected from 200 Turkish firms operating in multiple industries and sectors.

This study finds that leadership in Turkish firms operating in multiple sectors is positively associated with SQM. This study further finds that SQM positively influences Turkish firms’ TTC and mediates the roles of SP and leadership in TTC.

A key research implication from this study relates to the mediating role of SQM in TTC in an emerging economy context. This study highlights that SP and leadership can play an essential role in TTC through the mediating mechanism of SQM. Consequently, SQM emerges as a crucial linking pin in conveying the impact of quality management practices on technology transfer in emerging markets.

An essential managerial implication of this study relates to the critical roles of leadership, SP and SQM in TTC. For the managers of firms operating in a relatively uncertain emerging context such as Turkey, it is essential to adopt a supportive and empowering leadership style, where open communication and innovative activities are viewed positively and SQM is adopted holistically. Also, SP should be streamlined throughout the firm and followed by SQM to support TTC.

This paper links the technology (and knowledge) management and the strategy and leadership literature streams by focusing on the mechanisms of technology transfer and delving into the linkages between SQM, leadership, SP and TTC. It specifically presents SP and leadership as precursors to SQM in their joint influence on TTC. Accordingly, this research bridges technology, strategy and leadership research and provides a broader picture of technology transfer that encompasses the joint role of different processes in firms’ TTC.

The purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.

An extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.

The human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.

The results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.

While previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.

The quality of the customer journey has become a critical determinant of successful service delivery in contemporary business. Extant journey research focuses on the customer path to purchase, but pays less attention to the touchpoints related to service delivery and consumption that are key for understanding customer experiences in service-intensive contexts. The purpose of this study is to conceptualize service journey quality (SJQ), develop measures for the construct and study its key outcomes.

The study uses a discovery-oriented research approach to conceptualize SJQ by synthesizing theory and field-based insights from customer focus group discussions. Next, using consumer survey data (N = 278) from the financial services context, the authors develop measures for the SJQ. Finally, based on an additional survey dataset (N = 239), the authors test the nomological validity and predictive relevance of the SJQ.

SJQ comprises of three dimensions: (1) journey seamlessness, (2) journey personalization and (3) journey coherence. This study demonstrates that SJQ is a critical driver of service quality and customer loyalty in contemporary business. This study finds that the loyalty link is partially mediated through service quality, indicating that SJQ explains loyalty above and beyond service quality.

Since service quality only partially mediates the link between service journey quality and customer loyalty, future studies should examine alternative mediators, such as customer experience, for a more comprehensive understanding of the performance effects.

The study offers concrete tools for service managers who wish to understand and develop the quality of service journeys.

This study advances the service journey concept, demonstrates that the quality of the service journey is a critical driver of customer performance and provides rigorous journey constructs for future service research.

This study aims to properly and objectively assess the students’ study progress in bachelor programmes by applying statistical process control (SPC). Specifically, the authors focused their analysis on the variation in performance rates in business studies courses taught at a Spanish University.

A qualitative methodology was used, using an action-based case study developed in a public university. Previous research and theoretical issues related to quality indicators of the training programmes were discussed, followed by the application of SPC to assess these outputs.

The evaluation of the performance rate of the courses that comprised the training programs through the SPC revealed significant differences with respect to the evaluations obtained through traditional evaluation procedures. Similarly, the results show differences in the control parameters (central line and control interval), depending on the adopted approach (by programmes, by academic year and by department).

This study has inherent limitations linked to both the methodology and selection of data sources.

The SPC approach provides a framework to properly and objectively assess the quality indicators involved in quality assurance processes in higher education.

This paper contributes to the discourse on the importance of a robust and effective assessment of quality indicators of the academic curriculum in the higher education context through the application of quality control tools such as SPC.