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This paper aims to demonstrate how customer knowledge management (CKM) can assist destination management organizations (DMOs) in the smart management of the tourist experience to contribute to the creation of smart solutions and the promotion of smart tourism destinations (STDs). To accomplish it, a CKM conceptual framework aligned with smart tourism and composed of eight processes is developed to guide managers in this management.

This research adopts the design science research methodology and applies its steps. It was supported by a systematic integrative literature review on CKM models and frameworks and their main elements, as well as by semi-structured interviews with tourism specialists in the context of Santa Catarina, Brazil.

From the literature it appears that tourist experiences are customer knowledge essential to the improvement and innovation of tourism products and services, and that CKM, still little explored in this scenario, tends to contribute to the management of this crucial knowledge for smart tourism. The analyses and improvements to the structure developed by specialists show its applicability and contributions to the management of STD experiences.

This paper offers an original contribution to the integration of the theoretical constructs of CKM, tourist experience and STDs by showing how the CKM, from tourism experiences, technologies and social networks, can assist DMOs in the management of experiences and promotion of STDs.

The value chain is an essential management tool for the elaboration of strategic organizational planning. However, there are few published works providing methods for the development of value chains. This research aims to present a model to develop the value chain for the public sector.

Action research was used with case study in the evaluation step.

This research presents a model for value chain development along seven steps, covering data collection planning to the formalization of final product acceptance. The model suggests executing these seven steps in three iteration levels: operational, tactical and strategic. Through case studies, six practical insights were also highlighted in this work.

Given the absence of related work, one of the limitations is the lack of comparison with other methods of value chain development in the public sector.

There are practical guides to value chain development in the public sector; however, to the best of authors’ knowledge, such guides have not been developed using research methods. In the literature, no works provide details on how value chain can be developed in the public sector. In addition, the constraints of face-to-face contacts during the COVID-19 pandemic led the research team to conduct remotely the model's development and evaluation in the case studies. The model presents elements that enable value chain development without face-to-face contact between the execution team and public institution's stakeholders.

The purpose of this paper is to provide a systematic and updated assessment of studies on key exporting stimuli for small and medium enterprises (SMEs) and to propose a research agenda on this topic.

The authors develop a review of empirical articles on SMEs’ exporting stimuli and outline future research directions based on key emerging drivers.

Research on SMEs’ exporting drivers focuses mainly on human resources’ competences, skills and subjective characteristics and on the role of relevant network actors (customers, intermediaries).

This paper provides an original contribution with regard to updating the framework on export drivers by Leonidou et al. (2007), highlighting an emerging research perspective based on internal/external network dimensions and proposing future research directions on internal individual and organisational actors and on new external network actors.

This systematic literature review aims to synthesise, organise and structure the stock of knowledge relating to leadership and design for Lean Six Sigma (DFLSS) and to understand leadership’s role, traits, skills, competencies and styles within the context for DFLSS program success.

The research is based on a systematic literature review of 67 papers that were published on leadership and DFLSS, demonstrating the importance of leadership for successful DFLSS programs.

The key findings show that leadership plays a critical role in launching and sustaining a DFLSS program in organisations, while illustrating the leadership traits, skills, competencies and styles that are more conducive to a successful DFLSS program.

The study has identified several gaps in the literature from a practical approach and an empirical validation of the critical factors of leadership when applying and supporting DFLSS efforts supporting future initiatives.

The purpose of this study is to present the state of the art for fiber Bragg grating (FBG) acceleration sensing technologies from two aspects: the principle of the measurement dimension and the principle of the sensing configuration. Some commercial sensors have also been introduced and future work in this field has also been discussed. This paper could provide an important reference for the research community.

This review is to present the state of the art for FBG acceleration sensing technologies from two aspects: the principle of the measurement dimension (one-dimension and multi-dimension) and the principle of the sensing configuration (beam type, radial vibration type, axial vibration type and other composite structures).

The current research on developing FBG acceleration sensors is mainly focused on the sensing method, the construction and design of the elastic structure and the design of a new information detection method. This paper hypothesizes that in the future, the following research trends will be strengthened: common single-mode fiber grating of the low cost and high utilization rate; high sensitivity and strength special fiber grating; multi-core fiber grating for measuring single-parameter multi-dimensional information or multi-parameter information; demodulating equipment of low cost, small volume and high sampling frequency.

The principle of the measurement dimension and principle of the sensing configuration for FBG acceleration sensors have been introduced, which could provide an important reference for the research community.

This study aims to apply Process Mining (PM) techniques to identify the critical elements that primarily affect the trials’ duration and suggest the best practices to enable their more efficient execution, reduce their duration and, consequently, create public value, through a case study conducted in an Italian Civil Court.

Through PM analyses and in-depth discussions with the court staff, we analysed the trials with the longest duration and those belonging to a specific subject matter to identify peculiar features and inefficiencies that prolong the trials’ duration.

Our results highlight how innovative tools like PM can revolutionise the judicial system by providing judges with objective trials data that can support and facilitate the entire trials’ definition. However, many issues, especially related to the little spread data culture and process-oriented approach in courts, are highly present, leading to data inconsistencies and subsequent difficulties in trials’ analysis and interpretation.

Little research has devoted attention to the PM potential to enhance the judiciary. Our study contributes to this strand, yet adopting a different approach: it investigates the trials’ excessive length by focusing on bottlenecks and inefficient activities that slow down trials and identifies activities’ thresholds to monitor the trials’ execution and limit delays.

This study aimed to assess the potential of the Clinical Dementia Rating (CDR) Scale in the prognosis of dementia in elderly subjects.

Dementia staging severity is clinically an essential task, so the authors used machine learning (ML) on the magnetic resonance imaging (MRI) features to locate and study the impact of various MR readings onto the classification of demented and nondemented patients. The authors used cross-sectional MRI data in this study. The designed ML approach established the role of CDR in the prognosis of inflicted and normal patients. Moreover, the pattern analysis indicated CDR as a strong cohort amongst the various attributes, with CDR to have a significant value of p < 0.01. The authors employed 20 ML classifiers.

The mean prediction accuracy varied with the various ML classifier used, with the bagging classifier (random forest as a base estimator) achieving the highest (93.67%). A series of ML analyses demonstrated that the model including the CDR score had better prediction accuracy and other related performance metrics.

The results suggest that the CDR score, a simple clinical measure, can be used in real community settings. It can be used to predict dementia progression with ML modeling.

Frequent renegotiations within public-private partnership (PPP) have been recognised and affect project efficiency. Literature has focussed on diverse issues associated with renegotiation within PPP, especially in Latin America and Europe. However, a systematic summary what they have already provided appears lacking. Thus, the paper aims to conduct a critical review of publications concerning PPP renegotiation and explore the status quo, future interests and gaps in research.

This study carried out a four-phase literature review research framework to identify the quality PPP-renegotiation articles published from 2003 to 2020. Assessing the full articles for eligibility by providing a structured summary including: background; objectives; data sources; study appraisal; results; limitations; conclusions and implications of key findings. After that, filtering papers associated with PPP renegotiation in terms of the structured summary, and a total of 60 research papers were selected in the database of web of science and Scopus for review.

Methods adopted by researchers, research topics and theoretical foundations of PPP renegotiation research in different disciplines were identified through content analysis. Amongst the popular research topics identified were renegotiation factors, the outcomes with renegotiations, the framework to deal with renegotiations and contract design dealing with renegotiation based on rigid or flexible contracts.

This study contributes to the current body of PPP knowledge by revealing the research trend in the past 20 years. It also points out the directions that the renegotiations of PPP research may go towards in the future. Moreover, this study is very valuable in understanding how governments and concessionaires effectively handle renegotiations.

Head and neck cancers are multi-factorial diseases that can affect many sides of people's life and are due to a lot of risk factors. According to their characteristics, the treatment can be surgical, use of radiation or chemotherapy. The use of a surgical treatment can lead to surgical infections that are a main theme in medicine. At the University hospital of Naples “Federico II”, two antibiotics were employed to tackle the issue of the infections and they are compared in this paper to find which one implies the lowest length of hospital stay (LOS) and the reduction of infections.

The Six Sigma methodology and its problem-solving strategy DMAIC (define, measure, analyse, improve, control), already employed in the healthcare sector, were used as a tool of a health technology assessment between two drugs. In this paper the DMAIC roadmap is used to compare the Ceftriaxone (administered to a group of 48 patients) and the association of Cefazolin plus Clindamycin (administered to a group of 45 patients).

The results show that the LOS of patients treated with Ceftriaxone is lower than those who were treated with the association of Cefazolin plus Clindamycin, the difference is about 41%. Moreover, a lower number of complications and infections was found in patients who received Ceftriaxone. Finally, a greater number of antibiotic shifts was needed by patients treated with Cefazolin plus Clindamycin.

While the paper enhances clearly the advantages for patients' outcomes regarding the LOS and the number of complications, it did not analyse the costs of the two antibiotics.

Employing the Ceftriaxone would allow the Department of Maxillofacial Surgery to obtain lower LOS and a limited number of complications/infections for recovered patients, consequently reducing the hospitalization costs.

There is a double value in this paper: first of all, the comparison between the two antibiotics gives an answer to one of the main issues in medicine that is the reduction of hospital-acquired infections; secondly, the Six Sigma through its DMAIC cycle can be employed also to compare two biomedical technologies as a tool of health technology assessment studies.