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Despite increasing focus among scholars and practitioners on the design of product-service systems (PSS), there exists no compilation of current knowledge on the role played by small and medium-sized enterprises (SMEs) in designing such systems. Thus, this paper sets out to identify and organise the existing research and suggest questions for future research.

A systematic literature review was performed to identify and provide in-depth details on key themes in the literature addressing the design of PSS in SMEs.

This paper identifies five themes in the literature on the design of PSS in SMEs: motives, challenges, SME characteristics, methods and digitalisation. The themes are interrelated, and SME characteristics seem to be at the core as they are related to all the other themes. Gaps in the current knowledge are identified, and questions for future research are suggested.

The suggestions for future research provide a starting point for expanding the research on PSS design and devising practical support for SMEs.

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.

This paper reports a new technique for achieving optimized design for power system stabilizers. In any large scale interconnected systems, disturbances of small magnitudes are very common and low frequency oscillations pose a major problem. Hence small signal stability analysis is very important for analyzing system stability and performance. Power System Stabilizers (PSS) are used in these large interconnected systems for damping out low-frequency oscillations by providing auxiliary control signals to the generator excitation input. In this paper, collective decision optimization (CDO) algorithm, a meta-heuristic approach based on the decision making approach of human beings, has been applied for the optimal design of PSS. PSS parameters are tuned for the objective function, involving eigenvalues and damping ratios of the lightly damped electromechanical modes over a wide range of operating conditions. Also, optimal locations for PSS placement have been derived. Comparative study of the results obtained using CDO with those of grey wolf optimizer (GWO), differential Evolution (DE), Whale Optimization Algorithm (WOA) and crow search algorithm (CSA) methods, established the robustness of the algorithm in designing PSS under different operating conditions.

The purpose of this paper is to increase the knowledge and understanding of organizational and supervisory support in the context of employee deviant workplace behavior (DWB) by examining the potential associations of employees’ cultural value orientations. This paper aims to: clarify DWB; review perceived organizational support (POS) and perceived supervisory support (PSS); discuss the meaning of employees’ cultural value orientations (individualism–collectivism, power distance and paternalism); use the fuzzy logic model to analyze relationships between DWB and POS, as well as PSS and employees’ cultural value orientations.

This research applies a fuzzy-set qualitative comparative analysis.

The results show the role of employee perceived organizational and supervisory support and cultural dimension (power distance and paternalism) configurations on employee DWB.

The main originality of this study is to further increase the understanding of organizational and supervisory support in the context of employee DWB by examining the potential associations of employees’ cultural value orientations. This study extends the previous research by providing evidence that organizational and supervisory support influences employees’ DWB.

Research on workplace stress measurements varied without much accuracy and effectiveness. The purpose of this paper is to introduce a new quantitative assessment tool emWave Pro Plus (Institute of HeartMath) and compare heart rate variability (HRV) results with the Personal and Organizational Quality Assessment (POQA) and the Perceived Stress Scale (PSS).

This research opted for a correlational study which involves 85 full-time employees who were working at least 40 h per week in a large corporation participated in this study. The POQA and PSS were used to correlate with HRV.

Astonishing findings emerged in this study. Significant positive correlations were found between emotional stress and HRV, and between intention to quit and HRV. In other words, the researchers have to make sense the following surprising findings: the higher the emotional stress an employee faces, the healthier they are. Healthier employees may have higher intentions of quitting their jobs. The surprising results may be attributed to personality, culture, emotional regulation and age among others.

This research fulfills an identified need to validate quantifiable stress measurements especially in a corporate environment. The research also shows promising results, and future studies should continue to tap into HRV as an objective measure of mental health and workplace stress.

This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of digital technologies affects the value co-creation (VCC) process.

This study bases on configuration theory, which entails two main methodological phases. In the first phase the authors define the theoretically-derived interpretive framework through a literature review. In the second phase the authors adopt a case study methodology to inductively analyze the theoretically-derived domains and their relationships within a configuration.

ML enables multi-directional knowledge flows among value co-creators and expands the scope of VCC beyond the boundaries of the firm-client relationship. However, it determines a substantive imbalance in knowledge management power among the actors involved in VCC. ML positively impacts value co-creators’ performance but also requires significant organizational changes. To benefit from VCC via ML, value co-creators must be aligned in terms of digital maturity.

The paper answers the call for more theoretical and empirical research on the impact of the introduction of Industry 4.0 technology in companies and their ecosystem. It intends to improve the understanding of how ML technology affects the determinants and the process of VCC by providing both a static and dynamic analysis of the topic.

The purpose of this paper is to show that the computation of time-periodic signals for coupled antenna-circuit problems can be substantially accelerated by means of the single shooting method. This allows an efficient analysis of nonlinearly loaded coupled loop antennas for near field communication (NFC) applications.

For the modelling of electrically small coupled field-circuit problems, the partial element equivalent circuit (PEEC) method shows to be very efficient. For analysing the circuit-like description of the coupled problem, this paper developed a generalised modified nodal analysis (MNA) and applied it to specific NFC problems.

It is shown that the periodic steady state (PSS) solution of the resulting differential-algebraic system can be computed very time efficiently by the single shooting method. A speedup of roughly 114 to conventional transient approaches can be achieved.

The proposed approach appears to be an efficient alternative for the computation of time PSS solutions for nonlinear circuit problems coupled with discretised conductive structures, where the homogeneous solution is not of interest.

The present paper explores the implementation and application of the shooting method for nonlinearly loaded coupled antenna-circuit problems based on the PEEC method and shows the efficiency of this approach.

Introduction: The birth of a preterm child requires hospitalization in a neonatal intensive care unit (NICU), which is a very stressful experience for parents. Aim: To determine the stress level of parents of preterm babies admitted to intensive and sub-intensive units in two hospitals in Northern Italy and its association with their sociodemographic variables and the clinical conditions of their newborns.

The sampling was non-probabilistic and included parents of preterm babies admitted to intensive and/or sub-intensive care for at least 10 days. Instruments: (1) information deduced from the clinical record of preterm newborns; (2) sociodemographic determinants of parents' well-being deduced from a questionnaire; (3) parental stress scale: neonatal intensive care unit (PSS:NICU), which measures the perception of parents about stressors from the physical and psychological environment of the NICU.

Results: A total of 104 parents of 59 hospitalized preterm babies participated in the study. The average parental stress level was 1.87 ± 0.837. The subscale score that got higher was parent-infant relationship subscale. Concerning the infant characteristics, the birth weight of the babies and the length of their hospitalization affected the parents' stress level. Looking at parents' sociodemographic characteristics instead, the greater predictors were gender, age and occupational social class.

The parental role alteration caused by infant premature birth and consequent hospitalization is a major stressor for parents and in particular for mothers. The variables that resulted positively associated with higher stress in parents of preterm infants hospitalized are specific parental characteristics, including not adequately or previously studied ones, and infant characteristics.

This paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines.

The Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives.

The interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies' necessities.

The paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.

The circular economy (CE) has been endorsed as representing a model that is able to achieve environmental protection through decreased use of raw materials, together with changing economic values and social inclusion thanks to its demand for a wide variety of skill profiles. This has motivated many policy initiatives to support the implementation of the CE. The purpose of this study is to follow such policy initiatives in three geographically anchored industry-specific networks.

The study contributes to the research debate on the CE through a spatial approach with a focus on how the implementation of the CE is conditioned by spatial and regional contexts. The authors investigate three different networks in Sweden for CE with different locations and industrial profiles.

The findings reveal the difficulty that exist in relation to the implementation of the CE. The network and support functions in combination with private industry are vital. The risk of sustaining an uneven regional economic development is evident.

Although research on the development of the CE has proliferated, geographical approaches to this development are comparably rare to date. The authors seek to contextualise the strategy development and policy implementation of a CE policy.