Identifying car-sharing quality determinants: a data-driven approach to improve engineering design

Purpose - This study aims at identifying the quality determinants of car-sharing services, analyzing unstructured User-Generated Contents (UGCs) and, more specifically, online reviews generated by users of the same car-sharing service. Moreover, this paper discusses the implication of the proposed data-driven approach on engineering design. Methodology - A large dataset of car-sharing users' online reviews was analyzed by means of the Structural Topic Model (STM), i.e. a variant of Latent Dirichlet Allocation (LDA) technique which discovers underlying topics in a collection of documents also using document-level covariate information. Findings - This paper reports an analysis of UGCs related to different car-sharing services. The analysis unveils 20 determinants of car-sharing quality: customer service (physical office); accident & damages management; registration process; charges & fees; parking areas; app reliability; end trip issues; car condition; convenience; use rates; car proximity; car availability; efficacy; sharing benefits; customer service responsiveness; intermodal transportation; car start-up issues; customer service courtesy; billing and membership; car reservation. Originality – This paper proposes a novel approach to identify quality determinants by analyzing UGCs. The study of the quality determinants of a car-sharing service is a scarcely discussed field of research although the car-sharing sector is an increasingly important part of the transport economy

A worldwide survey on manufacturing servitization

Manufacturing servitization is defined as the process of innovating companies’ capabilities and procedures to support the shift from providing products to providing Product-Service Systems. Many studies have focused on this process, with particular regard to the potential benefits. Despite this general interest, a major void still concerns the quantification of its extent, e.g. in terms of involved companies and geographical diffusion. This study is based on the analysis of secondary data of a large sample of manufacturing companies from almost all over the world

A General Overview of Manufacturing Servitization in Italy

The process that involves companies developing the capabilities to provide services and solutions that supplement their traditional product offerings is commonly called servitization. With regards to manufacturing, the servitization process has been found to provide many advantages, such as: increasing the value of the offering, enhancing product customization, developing customers’ loyalty, generating profits throughout the whole product life cycle, etc. Despite the many studies related to this process, there is a major lack concerning its quantification. Through an in-depth analysis of medium-large size Italian companies in the manufacturing sector, this paper examines the process of servitization proposing (i) an assessment of its extent in terms of percentage of servitized companies (ii) a taxonomy of the services offered and (iii) an estimation of their relative diffusion. Also, the paper offers a perspective on the effects that this process may have on production technologies and systems

Categorizing Quality Determinants in Mining User-Generated Contents

User-Generated Contents (UGCs) are gaining increasing popularity as a source of valuable information for companies to manage the quality of their products, services and Product-Service Systems (PSS). This paper aims at proposing a novel approach to identify and categorize quality determinants through the analysis of an extensive database of UGCs. In detail, this paper applies a topic modeling algorithm (Structural Topic Model) to identify quality determinants and introduces the Mean Rating Proportion measurement for their classification into three categories: negative, positive and neutral quality determinants. The application of the proposed methodology is exemplified through the analysis of a PSS case study (car-sharing)

A service network perspective to evaluate service matching in early design

Purpose – 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. Design/methodology/approach – Through an analogy with living organisms in natural ecosystems, the service relationship deployment (SRD) allows the investigation of the possible relationships between matched services. Findings – 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. Originality/value – 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

Mining quality determinants of product-service systems from user-generated contents

The concurrent availability of an ever-increasing volume of User-Generated Content (UGC) and text mining techniques has enabled methods to conduct both qualitative and quantitative research that was unimaginable a few years ago. These investigations have proved to generate interesting insights with potential implications in manufacturing and engineering design. This paper introduces a novel practical methodology to address the following research issue: how to infer the quality determinants of a Product-Service System (PSS) from UGCs? Analyzing a sample of UGCs by means of a topic modelling method, the idea of this study is to produce and examine the set of determinants relevant to the perception of the quality of a specific PSS. The application of the proposed approach is exemplified on a specific use-oriented PSS: car-sharing

Enabling factors of manufacturing servitization: Empirical analysis and implications for strategic positioning

The introduction of advanced technologies and new production paradigms has led an increasing number of manufacturing companies to adopt business models that include an integrated provision of products and services. This process is generally referred to as servitization. This article addresses two primary research questions: (a) How do the commodity sector, geographical location and company dimension affect the variety of services offered by manufacturing companies? (b) What is the impact of these structural factors on the type of services offered by manufacturing companies? To address these questions, this article provides new insights into the understanding of the servitization process. The main elements of originality of this study are (a) an unprecedented size of the analysed sample, composed of more than 190,000 manufacturing companies; (b) a quantitative analysis of the effects of the three aforementioned factors on the servitization process and (c) a definition of a pair of indicators for evaluating and benchmarking the strategic position of manufacturing companies with respect to their service provision

A bio-inspired reinterpretation of symbiotic human-robot collaboration in assembly processes

The emergence of collaborative robotics allowed humans and robots to work closely together to perform manufacturing activities. By combining their distinctive strengths and abilities, humans and robots can support each other in completing complex tasks. The relationship between humans and robots is frequently described in the literature as symbiotic. However, the concept of symbiosis, originally conceived in natural science, is often oversimplified as the mere exchange of mutual benefits. In practice, the term ‘symbiosis’ encompasses a wide range of nteractions, ranging from relationships with positive impacts to relationships with negative impacts. Understanding the foundation of Human-Robot Symbiosis is crucial for its management. Two are the primary aims of this paper: (i) reinterpreting the collaborative tasks in assembly processes according to the properties of symbiotic elationships; (ii) proposing a novel approach for evaluating assembly tasks based on the bio-inspired features of symbiotic Human-Robot collaborative systems

Applications of Affective Computing in Human-Robot Interaction: state-of-art and challenges for manufacturing

The introduction of collaborative robots aims to make production more flexible, promoting a greater interaction between humans and robots also from physical point of view. However, working closely with a robot may lead to the creation of stressful situations for the operator, which can negatively affect task performance. In Human-Robot Interaction (HRI), robots are expected to be socially intelligent, i.e., capable of understanding and reacting accordingly to human social and affective clues. This ability can be exploited implementing affective computing, which concerns the development of systems able to recognize, interpret, process, and simulate human affects. Social intelligence is essential for robots to establish a natural interaction with people in several contexts, including the manufacturing sector with the emergence of Industry 5.0. In order to take full advantage of the human-robot collaboration, the robotic system should be able to perceive the psycho-emotional and mental state of the operator through different sensing modalities (e.g., facial expressions, body language, voice, or physiological signals) and to adapt its behaviour accordingly. The development of socially intelligent collaborative robots in the manufacturing sector can lead to a symbiotic human-robot collaboration, arising several research challenges that still need to be addressed. The goals of this paper are the following: (i) providing an overview of affective computing implementation in HRI; (ii) analyzing the state-of-art on this topic in different application contexts (e.g., healthcare, service applications, and manufacturing); (iii) highlighting research challenges for the manufacturing sector