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This study aims to propose guidelines for developing circular products based on waste recovery that are aligned with sustainable production and consumption.

A systematic literature review and case studies on circular product development were conducted. In total, 15 companies with products based on waste recovery and aligned with sustainable production and consumption goal were studied.

The results show the decisions and strategies applied at each stage of the new product development process, including the design for recycling, the use of waste as a raw material for products and the concern for reducing pollution and recovering end-of-life products.

The cases studied meet the goals of efficient use of natural resources and waste reduction by preventing, reducing, recycling and reusing waste. For practitioners, a set of guidelines is proposed to help companies develop circular products based on waste recovery.

Previous studies have not evaluated the new product development process and circularity from the institutional theory and waste valorization perspectives.

Quality management practices (QMP) have stood as one of the critical strategic differentiators for enhancing firm performance. The production and manufacturing industry is the main driving force of economic growth and social development for any developed or developing country. This study aims to focus on two primary dimensions of QMP: soft quality management practices (SQMP) and hard quality management practices (HQMP) from the socio-technical system perspectives. Based on institutional theory perspectives, the study explores the impact of SQMP and HQMP on quality performance (QP), innovation performance (IVP) and financial performance (FP) in Indian oil processing organizations.

A proposed research model is validated using 289 cross-sectional survey data collected from the senior officials of oil processing firms in India. Covariance-based structural equation modeling is used to verify the proposed theoretical model.

SQMP, directly and indirectly, influenced QP and IVP while only indirectly to FP mediated through QP. HQMP directly impacted only QP while indirectly to IVP and FP mediated through QP.

Impact of organizational legitimacy in proper utilization or application of QMP in achieving the firm sustainable growth. The future study may address the following Research Question (RQ) also: How do QMP enhance the legitimacy of organizations operating in the oil processing industries? Are there specific mechanisms or pathways through which improved performance contributes to enhanced organizational legitimacy? How does legitimacy impact the success and sustainability of organizations, particularly, within the context of the oil processing industries? Are there regulatory requirements or industry certifications that organizations must adhere to in order to maintain legitimacy?

Similarly, manufacturing firms establish QMP of interaction and maintaining relationships with all the stakeholders, total employee empowerment and involvement, workforce commitment and workforce management, helping to control their reputations and maintain legitimacy (Li et al., 2023). Similarly, in the health industry, the health management information system (HMIS), which uses the DHIS2 platform, establishes that isomorphism legitimizes data QMP among health practitioners and, subsequently, data quality. Further, it was concluded that mimetic isomorphism led to moral and pragmatic legitimacy. In contrast, normative isomorphism led to cognitive legitimacy within the HMIS structure and helped to attain the correctness and timeliness of the data and reports, respectively (Msendema et al., 2023). Quality, flexibility and efficiency of Big Data Analytics through better storage, speed and significance can optimize the operational performance of a manufacturing firm (Verma et al., 2023).

The study provides the academician with the different dimensions of QMP. The study demonstrates how a firm develops multiple performance capabilities through proper QMP. Also, it shows how vital behavioral and managerial perspectives are to QMP and statistically solid tools and techniques. The study draws their importance to risk factors involved in the firms. Since the SQMP play a vital role, thus, emphasis on the behavioral dimension of quality requires more investigation and is in line with hard technological advancements in the quality field.

The study of the impact of HQMP and SQMP on performance is still not established. There are inconsistencies in the findings. The study of the impact of HQMP and SQMP in oil processing industries has not dealt with before. The effects of HQMP and SQMP on the firm’s FP have least been dealt. In context to the intended influence of QM implementation, QP has not been examined as a potential mediator between FP. Research carried out in the past is limited to American and European countries. However, a limited study was done in Asia, and no study has been conducted in the Indian context.

This study aims to extend the cognitive appraisal theory by developing and validating a conceptual framework to illustrate how travelers' behavioral intention is generated via a multi-stage evaluation of health-related variables.

SEM and moderator analysis were conducted to examine the theoretical framework (post-intervention event travel intention) and to investigate how the appraisal process differs across travelers with various attitudes toward vaccination.

This study found that cruise travel intention was positively influenced by the perceived hedonic value and perceived trustworthiness and negatively influenced by perceived infection risk. Furthermore, whereas perceived hedonic value, perceived trustworthiness and perceived risk of infection were all predicted by crisis management, the dimensions of crisis management operated differently. In addition, vaccination attitudes amplified the unfavorable effect of perceived risk on intention.

Drawing on the CAT, this study developed and validated a conceptual framework to integrate crisis management with customers' behavioral intentions. This study extends existing cruise travel intention theory by demonstrating how post-pandemic travelers' behavioral intention is generated via a multi-stage appraisal-reappraisal process based on the evaluations of infection risks and cruise line crisis management.

This paper determines how travel intentions can be predicted using self-disclosure behaviour, trust and intimacy. This case study focuses on Tinder users who utilised the application's Passport feature which allowed them to travel virtually and interact with other users around the globe amid global travel restrictions.

This quantitative research conveniently sampled 294 Tinder users who used the Passport feature during COVID-19 pandemic lockdowns. Data were analysed using PLS-SEM.

This study revealed that self-disclosure had a significant influence towards future travel intentions. Findings show that the more users self-disclose, the more their intent to travel increase. Trust and intimacy also had significant relationship on travel intentions while intimacy had a mediating effect between self-disclosure and travel intentions.

Tourism-oriented establishments and destination marketers should consider Tinder users as a market segment of future tourists. These users have developed travel intentions through in-app interactions and thus comprise an untapped market of potential tourists seeking for meet-ups and niche experiences in a post-pandemic era.

This study provides novelty in showing the predictive relationship of self-disclosure, trust and intimacy towards travel intentions. A model consisting of these constructs in the context of online interactions was also empirically tested and found adequate to predict travel intentions.

This study aims to test the first and second-stage moderating effects of tourists’ past travel experiences on the relationships between national responses, destination trust and tourists’ willingness to pay in the post-pandemic recovery era.

The proposed model was tested with a sample of 398 tourists in Vietnam. The path analysis was applied to investigate the mediating and moderating effects.

The findings emphasise the mediating effect of destination trust in the relationships between national responses and tourists’ willingness to pay. With the moderating effect of past travel experience, all the first-stage indirect effects are significant, but the second-stage indirect effects are significant only at a high level of past travel experience.

This study provides theoretical implications for solving the puzzle about the paradox of trust in the government’s responses in the post-pandemic era. Practical implications for destination marketing organisations in the post-pandemic recovery era are then discussed.

The purpose of this study is to explore the associations between leadership, trustworthiness, and employee engagement during COVID-19.

In this cross-sectional, quantitative study, surveys of Sri Lankan male and female managers were conducted via standardized questionnaires. The sample size was 297 respondents. The Smart-PLS version 3.36 structural equation model analyzed the data set.

Both leadership and employee engagement and trustworthiness and employee engagement were found to have a statistically significant relationship. It has been found that leadership indirectly contributes to a higher degree of employee engagement through increased trustworthiness. According to the findings, employee engagement rises when they have the trustworthiness of the leadership in the virtual environment.

According to the findings of this study, organizations need to introduce rules to improve leadership manager roles in a virtual environment, which can improve trustworthiness and employee engagement. It also suggests that organizations should build trustworthiness between employees and leadership through a positive culture in a virtual environment that can improve employee engagement and organizational performance.

Research on leadership and trustworthiness improves employee engagement in a virtual environment is the contribution of this study.

The patient flow performance achievable by care pathways is constrained by competing flow and resource efficiency, which can negatively impact improvements. This paper probes the divergence between resource and flow efficiency and how care pathways can lead to improved patient flow. By framing the problem through the lens of paradox theory, a set of design principles is proposed to assist decision-makers in care pathway implementation. Implications are derived for research and practice.

The authors used conceptual research to develop design principles for care pathways based on a systematic review of relevant care pathway research. The initial search contained 515 unique articles, resulting in a final sample of 56 studies.

When applying care pathways, patient flow may be negatively affected in relation to the dimensions of bottlenecks, non-value-adding activities, and variability. However, the findings also indicate methods that can be applied to manage organizational paradoxes, which can contribute to more efficient patient flow along each of the three dimensions.

The study is limited to care pathways and therefore could have missed relevant studies in similar fields, such as care coordination.

Health care managers, politicians, and IT developers can apply the proposed design principles when developing, implementing, and improving care pathways and supporting technologies.

While existing research has studied care pathways from a medical perspective, this is the first paper to the author’s knowledge that addresses care pathways directly by considering paradox theory and in light of the operations management literature.

Social media platforms that disseminate scientific information to the public during the COVID-19 pandemic highlighted the importance of the topic of scientific communication. Content creators in the field, as well as researchers who study the impact of scientific information online, are interested in how people react to these information resources and how they judge them. This study aims to devise a framework for extracting large social media datasets and find specific feedback to content delivery, enabling scientific content creators to gain insights into how the public perceives scientific information.

To collect public reactions to scientific information, the study focused on Twitter users who are doctors, researchers, science communicators or representatives of research institutes, and processed their replies for two years from the start of the pandemic. The study aimed in developing a solution powered by topic modeling enhanced by manual validation and other machine learning techniques, such as word embeddings, that is capable of filtering massive social media datasets in search of documents related to reactions to scientific communication. The architecture developed in this paper can be replicated for finding any documents related to niche topics in social media data. As a final step of our framework, we also fine-tuned a large language model to be able to perform the classification task with even more accuracy, forgoing the need of more human validation after the first step.

We provided a framework capable of receiving a large document dataset, and, with the help of with a small degree of human validation at different stages, is able to filter out documents within the corpus that are relevant to a very underrepresented niche theme inside the database, with much higher precision than traditional state-of-the-art machine learning algorithms. Performance was improved even further by the fine-tuning of a large language model based on BERT, which would allow for the use of such model to classify even larger unseen datasets in search of reactions to scientific communication without the need for further manual validation or topic modeling.

The challenges of scientific communication are even higher with the rampant increase of misinformation in social media, and the difficulty of competing in a saturated attention economy of the social media landscape. Our study aimed at creating a solution that could be used by scientific content creators to better locate and understand constructive feedback toward their content and how it is received, which can be hidden as a minor subject between hundreds of thousands of comments. By leveraging an ensemble of techniques ranging from heuristics to state-of-the-art machine learning algorithms, we created a framework that is able to detect texts related to very niche subjects in very large datasets, with just a small amount of examples of texts related to the subject being given as input.

With this tool, scientific content creators can sift through their social media following and quickly understand how to adapt their content to their current user’s needs and standards of content consumption.

This study aimed to find reactions to scientific communication in social media. We applied three methods with human intervention and compared their performance. This study shows for the first time, the topics of interest which were discussed in Brazil during the COVID-19 pandemic.

While extant literature explores the influence of institutions on the national innovation system (NIS), most research has either focused on specific institutional aspects or treated institutions as a unified entity. This study aims to examine the effect of various institutional factors on a country’s NIS.

The conceptual model was empirically validated using regression analysis. The study sample comprised a total of 84 countries.

This study identifies and empirically validates a comprehensive set of institutional factors. It also highlights the significant institutional factors (including political stability, government effectiveness, ease of resolving insolvency and the rule of law) that can help improve a country’s NIS.

The research provides practical implications for organizations and policymakers seeking to understand and foster an innovative culture within the NIS. Policymakers are encouraged to develop a nurturing environment within the NIS by focusing on significant institutional factors. Organizations are encouraged to closely monitor developments in the NIS of a country to make informed strategic decisions at the business, corporate and international levels.

This study aims to highlight the influence of co-creation experience (CCE) on tourists’ citizenship behavior (TCB), emphasizing the Indonesian ecotourism sector during the post-COVID pandemic.

By using a judgmental sampling, data were collected from 150 visitors who visits Indonesian ecotourism resort and acquired the wildlife experience through co-creation process. To evaluate the relationship model, partial least squares-structural equation modeling by SmartPLS 3rd version was used in this study.

The result indicated that CCE in terms of Indonesian ecotourism had an effect on involvement (INV) and satisfaction (SAT). Result ascertain INV and SAT direct effect on TCB. Multigroup analysis indicated that perceived risk of COVID-19 could moderate insignificantly the relationship among INV, SAT on TCB.

This study focuses on CCE, INV, SAT and TCB in Indonesian ecotourism with wildlife attraction and contributes an insight for tourism research; thus, the results cannot be generalized for other ecotourism worldwide.

The proposed model of this study suggests the need to review the current condition of citizenship behavior at destination level, especially regarding to cleanliness and crowd controlling on post-COVID pandemic to maintain tourists’ health and safety while traveling.

Achieving TCB in different types of destination (ecotourism) requires specific development models concerning environmental conditions.

Though CCE, INV, SAT and TCB have identified as main topics for tourism research especially in ecotourism sector, the related factors of TCB in post-COVID-19 era are remain limited.

本研究旨在强调共创体验（CCE）对游客公民行为（TCB）的影响, 重点是后疫情期间印尼生态旅游中的游客公民行为（TCB）。

通过判断抽样, 从访问印尼生态旅游胜地的 150 名游客收集了数据, 并通过共创过程获得了其野生动物体验。 为了评估关系模型, 本研究使用了 SmartPLS 第三版的偏最小二乘结构方程建模 (PLS-SEM)。

结果表明, 印尼生态旅游的 CCE 对参与度（INV）和满意度（SAT）有影响。 结果确定了INV和SAT对TCB的直接影响。 多组分析表明, covid-19 的感知风险对 INV 和 SAT 与 TCB 的关系影响不大。 本研究还描述了中介作用。

该研究重点关注印尼生态旅游中野生动物吸引力的CCE、INV、SAT, TCB, 为旅游研究提供见解; 因此, 研究结果不能推广到全世界其他生态旅游。

该研究提出的模型表明, 有必要审查目的地层面公民行为的现状, 特别是在新冠大流行后的卫生和人群控制方面, 以维护游客在旅行时的健康和安全。

在不同类型的目的地（生态旅游）中实现游客的公民行为需要针对不同的环境条件而选择开发模式。

尽管 CCE、INV、SAT 和 TCB 是旅游研究中, 特别是在生态旅游领域的重点研究对象, 但在后疫情旅游过程中, 其与目的地公民行为相关的因素研究仍然有限。

Este estudio pretende poner de relieve la influencia de la experiencia de cocreación (CCE) en el comportamiento ciudadano de los turistas (TCB) haciendo hincapié en el sector del ecoturismo indonesio durante el periodo post-pandémico de la COVID-19.

Mediante el uso de un muestreo de juicio, se recopilaron datos de 150 visitantes que visitaron un centro de ecoturismo en Indonesia y adquirieron la experiencia de la vida silvestre a través del proceso de co-creación. Para evaluar el modelo de relación, en este estudio se utilizó el modelo de ecuaciones estructurales de mínimos cuadrados parciales (PLS-SEM) de SmartPLS 3.^a versión.

El resultado indicó que la CCE en términos de ecoturismo indonesio tuvo un efecto sobre la implicación (INV) y la satisfacción (SAT). El resultado determinó que INV y SAT tienen un efecto directo sobre el TCB. El análisis multigrupo indicó que el riesgo percibido del covid-19 modera de forma insignificante la relación INV y SAT con el TCB. Papel mediador también descrito en este estudio.

el estudio se centra en CCE, INV, SAT, TCB en el ecoturismo indonesio con atracción de vida silvestre y aporta información para la investigación turística; por lo tanto, los resultados no pueden generalizarse para otros ecoturismos en todo el mundo.

el modelo propuesto en el estudio sugiere la necesidad de revisar la condición actual del comportamiento ciudadano a nivel de destino, especialmente en lo relativo a la limpieza y el control de multitudes en la etapa poscovid para mantener la salud y la seguridad de los turistas durante el viaje

lograr un comportamiento ciudadano de los turistas en diferentes tipos de destino (ecoturismo) requiere modelos de desarrollo específicos en relación con las condiciones ambientales.

aunque CCE, INV, SAT y TCB se identifican como una prioridad para la investigación turística, especialmente en el sector del ecoturismo, los factores relacionados en el curso del turismo post-covid-19 que se relacionan con la ciudadanía a nivel de destino siguen siendo limitados.