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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.

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 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.

This study aims to follow a rigorous approach to identify, critically analyze and synthesize 75 papers published from 2000 to 2022.

The study presents a systematic literature review on identity expressiveness (IE), clarifying and expanding what is currently known about the concept.

To synthesize current knowledge on IE, the study uses the overarching framework of antecedents-phenomenon-consequences, using this same framework to identify gaps and future research directions. The findings show individual and brand-related factors such as the need for uniqueness and anthropomorphism as antecedents of IE, and eWOM/WOM, impulse purchases and upgrading to more exclusive lines as consequences of IE.

The study contributes to theory by synthesizing and mapping current understanding of the state of knowledge on the concept of IE while highlighting gaps in the extant literature and paving future research directions for scholars in the field.

The study offers useful insights for practitioners, broadening marketers’ actionable options in identity-based marketing. Marketers can use insights from this study to inform marketing strategy and communication campaigns for different types of brands.

To the best of the authors’ knowledge, this study is the first of its kind and offers an integrative review of the current literature on IE, thus enhancing understanding of the concept, its antecedents and consequences. The study also contributes to knowledge by highlighting future research priorities for researchers in this field of enquiry.

This paper aims to develop an initial understanding of the Lean Six Sigma methodology since its inception and examine the few Lean Six Sigma dimensions as a research domain through a critical review of the literature.

The paper is structured in two-part. The first part of the paper attempts to dwell on the evolution of the Lean Philosophy and Six Sigma methodology individually and the emergence of Lean Six Sigma methodology, covered under the Lean Six Sigma: a historical outline section. The second part of the study examines the dimensions associated with Lean Six Sigma such as frameworks, critical success factors, critical failure factors, type of industry, performance metric, year, publisher and journal, based on a total of 223 articles published in 72 reputed journals from the year 2000 to 2019 as a literature review.

The adoption of Lean Six Sigma, as a continuous improvement methodology, has grown enormously in the manufacturing and few service sectors such as health care and higher education during the past decade. The study revealed that researchers came out with conceptual frameworks for the implementation of Lean Six Sigma, whereas the validation through case studies seems to be lacking. The integration of Lean Six Sigma and other approaches with a focus on sustainability and the environment has emerged as a research field. A few of the most common critical success and failure factors were identified from the articles studied during the study.

This paper may not have included some of the studies due to the inaccessibility and selection criteria followed for the study.

This paper will provide an initial introduction on Lean, Six Sigma and Lean Six Sigma and research insights Lean Six Sigma to beginners such as students, researchers and entry-level professionals.