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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.

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 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.

Quality 4.0 is a new paradigm of quality management, which emphasises the need to adapt to recent technological innovations by updating traditional quality approaches. Amongst the most important factors for adopting Quality 4.0 is the leveraging of big data to collect insights and quality perceptions from clients. Therefore, user reviews have emerged as a valuable source of information, which can be analysed through machine learning procedures to uncover latent quality dimensions.

This study applies a combination of text mining techniques to analyse Airbnb reviews, identifying service quality attributes and assessing their relation to the users' sentiment. More than two million reviews written by guests in four European cities are analysed. First, topic modelling is applied to find the quality attributes mentioned by reviewers. Then, sentiment analysis is used to assess the positiveness/negativeness of the users' feedback.

A total of 37 quality attributes are identified. Four of them show a significant positive relation to the guest's sentiment: apartment views, host tips and advice, location and host friendliness. On the other hand, the following attributes are negatively correlated with user sentiment: sleep disturbance, website responsiveness, thermal management and hygiene issues.

This paper provides a practical example of how Quality 4.0 can be implemented, proposing a data-driven methodology to extract service quality attributes from user-generated content. Additionally, several attributes that had not appeared in existing Airbnb studies are identified, which can serve as a reference to extend previous quality assessment scales.

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.

The purpose of this paper is to dissect the diffusion of the number of organizations that implemented multiple management systems (MSs), considering the International Organization for Standardization (ISO) 9001, ISO 14001 and OHSAS 18001 standards (quality, environment and safety) in the South European countries: Italy, Portugal and Spain. In addition, based on the data collected, forecasting models were developed to assess at which extent the multiple certifications are expected to occur in each studied country.

Data concerning the evolution of the amount of multiple MSs in Italy, Portugal and Spain were collected for the period between 1999 and 2015. The behavior of the evolution of the number of MSs over the years was studied adopting both the Gompertz and the Logistic models. The results obtained with these two models were compared and analyzed to provide a forecast for the next years.

The diffusion throughout the years of the number of MSs presents an S-shaped behavior. The evolution of the amount of MSs in countries with a lower saturation level are properly fitted by the Gompertz model whereas the Logistic model fits more accurately when considering countries with a larger saturation level.

The data related to the early years are not available in some of the countries. To overcome this shortcoming missing data were extrapolated from the data set provided by the annual ISO survey. Additionally, the integration level attained by each company was not assessed and, on this regard and in the scope of this paper, an integrated management system is understood as implemented when organizations have multiple MSs implemented.

The results provide a cross-sectional portrayal of the diffusion of MSs certifications in the South European countries and enable a forecast for the trend in the next years.

This study aims for the first time, to the best of the authors’ knowledge, to analyze the diffusion of multiple MSs throughout the years.

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.

This study examines the impact of servitization in the form of repair and maintenance services on consumers' quality perceptions, purchase intentions and recommendation intentions while considering consumer frugality as a moderator in the retail ready-to-wear sector.

A quantitative approach based on consumer research was pursued. Study 1 tested the research model using a fictitious ready-to-wear brand within an experimental design. To increase the generalizability of results, Study 2 retested the model with a well-known ready-to-wear brand. For both studies, regression, mediation and moderation analyses were conducted in SPSS.

Both studies showed that servitization positively influences perceived quality. Servitization positively affects purchase intentions and recommendation intentions indirectly via the mediating role of perceived quality. Frugality moderates the relationship between servitization and perceived quality for the fictitious brand (Study 1), whereas it is not significant for a well-known ready-to-wear brand (Study 2). Servitization positively influences perceived quality regardless of consumers' frugality levels for a stronger brand.

This study suggests and tests an original conceptual model that relies on signaling theory. It is among the first studies to examine the impact of servitization on retail fashion consumers' quality perceptions and consequent purchase and recommendation intentions. This study also contributes to the literature by presenting empirical findings based on consumer research on servitization while considering frugality as a moderator.

Bundling products with additional services can contribute to quality perceptions and consequently to purchase and recommendation intentions for ready-to-wear brands.

Despite the widespread application and implementation of servitization strategy by manufacturing firms worldwide, little attention has been devoted to its adoption by European-Mediterranean countries, such as Italy. Thus, the purpose of this paper is to fill this gap by investigating if and how Italian manufacturing firms adopt a servitization strategy.

According to the paper’s aim, the survey methodology has been chosen and a specific questionnaire has been constructed by adopting and adapting the questions used by Baines et al. (2010). Key respondents were CEOs and General Managers of the manufacturing firms surveyed.

Findings show the main features and determinants of the adoption of a servitization strategy by Italian manufacturers as well as a comparison between them and UK manufacturers, determining both theoretical and practical implications.

This paper investigates the manufacturing firms located exclusively in the Italian region of Lazio. Thus, even though it is reasonable to believe that they can be considered as representative of the Italian reality, future enrichment of the sample could provide further insights into the investigation of the Italian case.

The paper examines the little-researched adoption of servitization by Italian manufacturing firms, contributing to the servitization research and providing evidence on its trends in a specific European-Mediterranean region.