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Organizations often introduce performance measurement systems (PMSs) in order to evaluate the level of their performance, make comparison with competitors, and plan their future activities. Since indicators may affect the behaviour of the monitored system, the design and implementation of a PMS should always include the analysis of the impact it may exert on the organization itself. The aim of this paper is to suggest a methodology to evaluate this impact.

The proposed approach is based on an impact reference model derived from the balanced scorecard (BSC) framework. The different perspectives of the BSC are interpreted as areas of impact within an organization. Structured steps for impact evaluation are described and specific techniques of analysis are introduced.

A series of case studies, together with an analysis of advantages and disadvantages of the proposed method, are presented. Results show that, although many sets of indicators are usually able to meet the role of a PMS, they may exert a different impact on the context they are applied. The proposed methodology results to be a useful instrument for choosing the right set of indicators from the impact point of view. Finally, possible research paths to be undertaken for further developments of the proposed methodology are traced.

The application of the method is based on the assumption that managers charged with the analysis have a profound understanding of the specific contextual factors which may determine a reaction of the organization to a performance indicator or a PMS. Furthermore, at the moment, the methodology does not consider the possibility of interaction among different indicators in producing the impact.

This paper may be used to guide the selection of the most appropriate PMS from the impact point of view. The proposed methodology can be very helpful instrument for an organization involved in the design of new PMSs. It guides the decision maker through the various phases: indicators definition, analysis of their properties, impact analysis, and choice of the set with the preferable impact profile.

The issue of impact has been long debated in literature. Many articles try to analyse the operative and strategic consequences of the introduction of a PMS in an organization. This paper proposes a methodology for a more structured and objective evaluation of the impact of new PMS before introducing it in a firm. This can result in a significant help for manager who have to find the best set of indicators for the performance evaluation of their organization or have to choose between two or more sets of indicator satisfying, in principle, the same representation objective.

The purpose of this paper is to attempt to provide a reference framework for the major properties of performance indicators, using the formalism of the Representation Theory.

Performance indicators shown are commonly used in many different areas of operations management in order to analyse process evolution. However, in practical applications many questions arise: “How many indicators should be used for representing a given process?”, “Is there an optimal set?”, “How to check whether the indicators used suitably represent the system investigated?”, etc. In the literature these questions have been addressed in relation to a number of different application fields. This has led to a maze of classifications and properties, which may create confusion in both the academic and the practitioner communities. In a previous work, the paper carried out an analysis of the existing literature, examining and comparing different approaches. This present work identifies and analyses the major properties which effective indicators should exhibit, and suggests an operational methodology to choose the “best” set of indicators.

The findings in this paper produce a detailed analysis of the properties of indicators and establish a schematic methodology facilitating the selection and verification of indicators. To make the process clearer, properties are explained by the use of practical examples.

Indicators are utilized in many different contexts for a variety of purposes (for example, logistics, business management, manufacturing, sports competitions, etc.). The paper provides a general analysis of the most important properties of indicators, without entering into specific application contexts.

The paper proposes an operational methodology to support the selection and testing of the best indicators for a given process. This methodology may also be used for integrating other existing approaches.

Properties of indicators are examined from a mathematical/symbolic point of view, using the formalism of the Representation Theory.

Digital voice-of-customer (digital VoC) analysis is gaining much attention in the field of quality management. Digital VoC can be a great source of knowledge about customer needs, habits and expectations. To this end, the most popular approach is based on the application of text mining algorithms named topic modelling. These algorithms can identify latent topics discussed within digital VoC and categorise each source (e.g. each review) based on its content. This paper aims to propose a structured procedure for validating the results produced by topic modelling algorithms.

The proposed procedure compares, on random samples, the results produced by topic modelling algorithms with those generated by human evaluators. The use of specific metrics allows to make a comparison between the two approaches and to provide a preliminary empirical validation.

The proposed procedure can address users of topic modelling algorithms in validating the obtained results. An application case study related to some car-sharing services supports the description.

Despite the vast success of topic modelling-based approaches, metrics and procedures to validate the obtained results are still lacking. This paper provides a first practical and structured validation procedure specifically employed for quality-related applications.

Service matching is defined in this paper as the process of combining a new service with one or more existing services. A recurring problem for service designer is to match new services with existing ones. This process may be seen as the fundamental action for the development of a service network. The purpose of this paper is to evaluate the consequences that may follow from service matching.

Through an analogy with living organisms in natural ecosystems, the service relationship deployment (SRD) allows the investigation of the possible relationships between matched services.

This paper presents a new method, named SRD, developed to support the process of service matching in the early design phases of a new service. The description of the method is supported by some practical examples.

The focus of the scientific community on the problem of matching new services with existing ones, is very limited. This paper proposes a new methodology to address this issue.

To provide a cross‐section of International Standardization Organization (ISO) 9000 quality certification diffusion over time and its impact on industrial systems.

The starting point of the analysis is “The ISO survey of ISO 9000 and ISO 14001 certificates” document. Available data concur to trace a synthesis of what has happened and what is in process all over the world. Five main aspects are discussed: the correspondence between ISO 9000 standards and total quality management strategy; the effects of ISO 9000 certification on business performance; the ISO 9000 certificates diffusion in the world; the comparison between economical and entrepreneurial structure of different countries and certificates diffusion; the proposal of a prediction model for the diffusion of ISO 9000 certificates.

The evolution curve of the number of certificates over time in each country presents a “saturation effect.” This behavior has been analyzed by a diffusion forecasting model. The analysis of regional share certificates evolution evidences a sensible increase of Far East countries. The analysis of ISO 9000 certificates' share by industrial sector highlights a growth for the most sectors; only a few of them show a negative trend in last two years. A relationship between ISO 9000 certificates and socio‐economic indicators of a country (human development index, gross national product) has been individuated.

The stunning growth of ISO 9000 certifications all over the world confirms a strong polarization of enterprises' interest in this practice. Looking at the empirical data, some questions come out about the future. Will the certification market go on? Will certified enterprises continue to be interested to the certification process?

This paper analyzes the worldwide evolution of ISO 9000 certification and suggests a new prediction model for the diffusion of ISO 9000 certificates.

The paper attempts to address the following research questions (RQs): RQ1: What are the main research topics within PSS research? RQ2: What are future trends for PSS research?

Twenty years of research (1999–2018) on product-service systems (PSS) produced a significant amount of scientific literature on the topic. As the PSS field is relatively new and fragmented across different disciplines, a review of the prior and relevant literature is important in order to provide the necessary framework for understanding current developments and future perspectives. This paper aims to review and organize research contributions regarding PSS. A machine-learning algorithm, namely Latent Dirichlet Allocation, has been applied to the whole literature corpus on PSS in order to understand its structure.

The adopted approach resulted in the definition of eight distinct and representative topics able to deal adequately with the multidisciplinarity of the PSS. Furthermore, a systematic review of the literature is proposed to summarize the state-of-the-art and limitations in the identified PSS research topics. Based on this critical analysis, major gaps and future research challenges are presented and discussed.

On the basis of the results of the topic landscape, the paper presents some potential research opportunities on PSSs. In particular, challenges, transversal to the eight research topics and related to recent technology trends and digital transformation, have been discussed.

The aim of this study is to enhance the product quality management by proposing a framework for the classification of anomalies in digital voice of customer (VoC), i.e. user feedback on product/service usage gathered from online sources such as online reviews. By categorizing significant deviations in the content of digital VoC, the research seeks to provide actionable insights for quality improvement.

The study proposes the application of topic modeling algorithms, in particular the structural topic model, to large datasets of digital VoC, enabling the identification and classification of customer feedback into distinct topics. This approach helps to systematically analyze deviations from expected feedback patterns, providing early detection of potential quality issues or shifts in customer preferences. By focusing on anomalies in digital VoC, the study offers a dynamic framework for improving product quality and enhancing customer satisfaction.

The research categorizes anomalies into spike, level, trend and seasonal types, each with distinct characteristics and implications for quality management. Case studies illustrate how these anomalies can signal critical shifts in customer sentiment and behavior, highlighting the importance of targeted responses to maintain or enhance product quality.

Despite its contributions, the study has some limitations. The reliance on historical data may not hold in rapidly changing markets. Additionally, text mining techniques may miss implicit customer sentiment.

The findings suggest that companies can enhance their quality tracking tools by digital VoC anomaly detection into their standard practices, potentially leading to more responsive and effective quality management systems.

This paper introduces a novel framework for interpreting digital VoC anomalies within the Quality 4.0 context. By integrating text mining techniques with traditional quality tracking, it offers a novel approach for leveraging customer feedback to drive continuous improvement.

The purpose of this paper is to provide an overview of the recent research on the interaction between flight mechanics and sensory/control systems in flies. It furthermore, explores the application to biomimetic micro‐air vehicles (MAVs).

A review of recent literature on flight in flies is given first, whereafter two biomimetic case studies are discussed; the optic flow sensor developed by a French team and the micro‐mechanical flying insect project at the University of Berkeley.

The paper discusses the many areas where biological knowledge on flight in flies can be used by designers of MAVs.

Fully autonomous MAVs, inspired by insect flight, could be useful in a wide range of areas including search‐and‐rescue, surveillance and for military purposes.

The paper gives an up to date overview of dipteran flight behaviour and points to ways in which this knowledge can be applied to MAVs. The paper should thus be useful for biologists wishing to collaborate with engineers as well as for engineers and sensor designers seeking inspiration from nature.

Analysis and comparison of three existing indicators of the air quality: the American air quality index, the French Atmo, and the Italian Indice di Qualità dell'Aria.

International general and organic regulations to control air quality do not exist yet. Consequently many countries have independently implemented specific indicators to monitor the air pollution and then alert people of resulting health risks. The paper focuses on three of them. Each one is independently presented showing the peculiarities. Therefore, these indicators are compared to identify the features they have in common, as well as those that set them apart, and to figure out which are either restrictive or permissive, and what are their qualities and drawbacks.

The three mentioned indicators convert the real health risk due to air pollution into numerical information, in different ways. Doing this, they carry out some simplifications or assumptions, which can be questionable. The main difficulty is to understand if the indicators aggregate the different pollutant concentrations consistently with the real effects on human health.

This paper analyses only three specific indicators of the air quality, selected among the existing ones.

Indicators should carefully be analysed to understand if they properly represents the real effects of pollutants on human health. The most critical aspect to consider is the aggregation of the different pollutant concentrations in one information.

This paper analyses the efficacy of representation of some air quality indicators. It discusses if indicators aggregation is consistent with the real effects on human health.

Outsourcing is a management approach by which an organization delegates some non‐core functions to specialized and efficient service providers. In the era of “global market” and “e‐economy”, outsourcing is one of the main pillars of the new way to conceive the relationships among companies. Despite outsourcing large diffusion, huge business cases and big deals of documentation available on network or press, there is no structured procedure able to support the govern of the evolution of a generic outsourcing process. In accordance with the principles of total quality management, this paper describes a proposal of a new approach for managing outsourcing processes. The model, which can be easily adapted to different application fields, has been conceived with the main aim of managing strategic decisions, economic factors and human resources. The approach is supported by different decision and analysis tools, such as benchmarking techniques, multiple criteria decision aiding (MCDA) methods, cost analysis, and other process‐planning methodologies. An application of the method to a real case is also provided.