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This paper aims to identify the antecedents and postcedents of customer satisfaction, including utilitarian, social and emotional factors, in a fair trade (FT) coffee consumption context.

This paper is based on a broad range of 177 consumers of FT coffee in Spain, the data analysis used structural equation modeling (SEM) with SPSS/AMOS 26.0 software.

This paper supports that both customer social value and quality affect perceived value (PV). PV in turn has effects on customer satisfaction and the latter influences loyalty. Conversely, both customer emotional value and customer expectations were not confirmed as antecedents of PV.

The consumer satisfaction analysis conducted differs substantially from those of conventionally traded coffee, as social and emotional factors were considered along with utilitarian factors.

Practitioners, retailers and relevant institutions should design strategies to manage efficiently channel efforts to improve the consumer satisfaction and its loyalty.

This paper contributes to a substantial improvement in the understanding of consumer satisfaction and its consequences, in FT coffee consumption contexts. A new integrated theoretical model on customer satisfaction has been provided, which includes social and emotional perception factors, along with cognitive perception (quality and expectations) factors.

研究旨在確認在公平貿易咖啡消費的課題上，顧客滿意的誘因及其後因，這包括實用的因素，社會的因素和情感的因素。

研究之數據廣泛來自在西班牙177名公平貿易咖啡消費者; 分析則以結構方程模型，並以SPSS Amos 26軟件來進行。

研究結果證實，顧客社會價值和質量是會影響認知價值的;認知價值繼而影響顧客滿意度，而顧客滿意度又進而影響他們的忠誠。相反的，顧客情緒價值或他們的期望、均未能證實是認知價值的先決條件。

本研究所進行的消費者滿意度分析，與其它以傳統方法銷售的咖啡之相關研究有很大的分別，這是因為本研究除了考慮實用的因素外，還納入了社會因素和情感因素。

從業人員、零售商和有關的機構應制訂適切的策略，以能有效地管理各個管道，來提升消費者的滿意度和忠誠。

本研究的貢獻在於它幫助我們在公平貿易咖啡消費的課題上，對消費者滿意及其效果有更深入的認識。研究亦提供了一個探討顧客滿意度的嶄新、綜合的理論模型，而這個理論模型，除了涵蓋知覺認知 (質量和期望) 的因素外，還納入了社會的和情感的知覺因素。

As the world grapples with the pervasive effects of the coronavirus pandemic, a notable disconnect has emerged in the public's understanding of scientific and medical research. Particularly, the travel industry has become unquestionably vulnerable amid the COVID-19 outbreak; this pandemic has interrupted the industry's operations with devastating economic consequences. This paper aims to highlight the importance of deconstructing barriers between medical science and public awareness related to COVID-19, taking tourism as a case in point. It also discusses the role of interdisciplinary research in facilitating the tourism and hospitality industry's recovery and alleviating tourists' uncertainties in the wake of COVID-19.

This paper offers a synthesis of news coverage from several media outlets, framed within the literature on knowledge transformation across disciplines. This framing focuses on the medical sciences (e.g. public health) and social sciences (e.g. tourism management) to identify gaps between medical scientific knowledge and public awareness in the context of COVID-19. The authors' experience in public health and tourism management further demonstrates a missing link between academic research and the information made available in public health and everyday settings. A potential research agenda is proposed accordingly.

This paper summarizes how salient issues related to knowledge transfer can become intensified during a global pandemic, such as medical research not being communicated in plain language, which leads some citizens to feel apathetic about findings. Reporting on the prevalence and anticipated consequences of disease outbreaks can hence be difficult, especially early in the development of diseases such as COVID-19.

By assuming a cross-disciplinary perspective on medical/health and social science research, this paper encourages academic and practical collaboration to bring medical research to the masses. This paper also outlines several research directions to promote public health, safety and sustainability through tourism.

This paper highlights that it is essential for medical knowledge to be disseminated in a manner that promotes public understanding. The tourism and hospitality industry can benefit from an essential understanding of medical findings, particularly during this pandemic. Without a firm grasp on COVID-19's origins and treatment, the tourism and hospitality industry will likely struggle to recover from this catastrophe.

Taking COVID-19 as a case in point, this study advocates leveraging the strengths of disparate domains to bring medical findings to a wider audience and showcase cutting-edge developments for the greater good. This study also emphasizes the importance of engaging the general public in reputable scientific research findings to increase public awareness in a professional and accurate manner.

This paper presents a unique and critical discussion of the gap between medical science knowledge and public awareness, as well as its implications for tourism and hospitality recovery after COVID-19, with a focus on applying medical scientific knowledge to post-pandemic industry recovery.

當全球正與冠狀病毒流行病所帶來的廣泛影響抗衡之際，公眾對科學和醫學研究的理解卻出現了一個令人關注的脫節現象。在2019冠狀病毒病爆發期間，旅遊業無疑格外受到影響。這流行病中斷了旅遊業的運作，給業界帶來毀滅性的經濟影響。本文旨在以旅遊業為一個適時的例子、強調我們必須剖析與2019冠狀病毒病相關的醫學與公共意識之間的障礙。本文亦討論跨學科研究對促進2019冠狀病毒病疫情後旅遊及酒店業的復甦、及減低旅客的不確定性所扮演的角色。

本文提供一個來自數個媒體管道的新聞報導的綜合論述，而這論述是在與跨學科知識轉化相關的文獻領域內陳述而成的。論述的重點放在醫學科學(例如公共衛生) 和社會科學(例如觀光管理) 上，目的是確定在2019冠狀病毒病的背景下、醫學知識與公共意識之間的差距。作者們在公共衛生及觀光管理方面的經歷進一步顯示學術研究、與公共衛生和日常環境上的公開資訊之間缺乏銜接，本文就此提出一個研究議程。

本文總結與知識轉化相關的顯著問題如何會在全球流行病爆發期間變得更嚴重。譬如、醫學研究的資訊會因沒有以通俗語言來傳遞而令有些國民對其研究結果漠不關心。因此，關於疾病的傳播和爆發所預期的影響的信息是難於廣傳的，特別是在像2019冠狀病毒病等疾病形成的初期。

本文就醫學知識與公共意識之間的差距作出了一個獨特、有批判性的討論，亦論述這差距對2019冠狀病毒病疫情過後旅遊及酒店業復甦的意義。討論的焦點放在如何應用醫學知識在疫情後幫助產業復甦上。

作者們採用涵蓋醫學/衛生和社會科學研究的跨學科角度，鼓勵學者與從事實務人員相互合作、以便把醫學研究帶給廣泛的民眾。本文亦概述多個研究方向，透過旅遊業來推動公共衛生、公眾安全及可持續性。

本文強調醫學知識必須透過能提高公共意識的方式來傳遞。旅遊及酒店業會因我們對醫學研究結果擁有必要的認識而受惠，尤其是在這流行病蔓延的期間。若我們對2019冠狀病毒病的病源和療法沒有確切的了解，則旅遊及酒店業將難從這災難中恢復過來。

本研究利用2019冠狀病毒病這個適時的例子，來提倡借助各個不同領域的優點，為了謀求公眾的利益、把醫學的研究結果帶給更多民眾、及傳達醫療最新發展的信息。本研究亦強調以專業、精準的方法，引起公眾對可信賴的科學研究結果產生興趣，從而提高公共意識至為重要。

This editorial for the 6th World Conference on Production and Operations Management (P&OM) 2022 Special Issue delves into the transformative role of advanced artificial intelligence (AI)-driven chatbots in reshaping operations, supply chain management and logistics (OSCM). It aligns with the conference’s theme of exploring the intersection between P&OM and strategy during the Technological Revolution.

Utilizing a conceptual approach, this paper introduces the “ERI Framework,” a tool designed to evaluate the impact of AI-driven chatbots in three critical operational dimensions: efficiency (E), responsiveness (R) and intelligence (I). This framework is grounded in disruptive debottlenecking theory and real-world applications, offering a novel structure for analysis.

The conceptual analysis suggests immediate benefits of chatbots in enhancing decision-making and resource allocation, thereby alleviating operational bottlenecks. However, it sees challenges such as workforce adaptation and potential impacts on creativity and sustainability.

The paper suggests that while chatbots present opportunities for optimizing operational processes, organizations must thoughtfully address the emerging challenges to maintain productivity and foster innovation. Strategic implementation and employee training are highlighted as key factors for successful integration.

Bridging the gap between the burgeoning proliferation of chatbots and their practical implications in OSCM, this paper offers a first perspective on the role of AI chatbots in modern business environments. By providing insights into both the benefits and challenges of chatbot integration, it offers a preliminary view essential for academics and practitioners in the digital age.

This exploratory study examines and comprehends the relative importance of mobile app attributes from a consumer perspective. Both quantitative and qualitative analysis approaches explore users' behavior and attitudes toward the priorities of mobile app attributes and preferences, identifying correlations between attributes and aggregating individual attributes into groups.

Online convenience sampling and snowball sampling resulted in 417 valid responses. The numerical data are analyzed using the relative to an identified distribution (RIDIT) scoring system and gray relational analysis (GRA), and qualitative responses are investigated using text-mining techniques.

This study finds enhanced nuances of user preferences and provides data-driven insights that might help app developers and marketers create a distinct app that will add value to consumers. The latent semantic analysis indicates relationship structure among the attributes, and text-based cluster analysis determines the subsets of attributes that represent the unique functions of the mobile app.

This study reveals the essential components of mobile apps, paying particular attention to the consumer value component, which boosts user approval and encourages prolonged use. Overall, the results demonstrate that developers must concentrate on its functional, technical and esthetic features to make an app more exciting and practical for potential users.

Most scholarly research on apps has focused on their technological merits, aesthetics and usability from the user's perspective. A post-adoption multi-attribute app analysis using both structured and unstructured data is conducted in this study.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

This study aims to gain an understanding of success factors and barriers to public private collaboration in the context of zero emission neighbourhood.

Qualitative research method: narrative literature study.

On the basis of the identified success factors and barriers, a model with the following five interconnected themes is developed: (1) supportive public policy, (2) stakeholder management, (3) creation of a common ground for understanding, (4) knowledge sharing and learning and (5) uncertainty management.

The model can be further developed and tested. In-depth conceptual/empirical study on the five themes can shed more light on the topic.

This model is one of the several ways to understand, structure and simplify the reality (of public private collaboration in the context of zero emission neighbourhood). These five themes are arranged in the model in such a way to represent strategic, tactical and operational levels. This model can be useful to identify measures (steps, concrete actions, etc.) To address issues related to the five themes in a given organisational context. Focusing adequately on these five themes can contribute to successful public private collaboration in the context of zero emission neighbourhoods.

This study/model provides an overall, holistic approach to address/improve public private collaborative endeavours in the context of developing zero emission neighbourhoods.

This study aims to examine the linkages between port aesthetics, destination image, tourist satisfaction and tourist loyalty in Hong Kong.

To achieve this objective, the authors surveyed 247 tourists in Hong Kong. Using factor analysis and structural equation model (SEM) to identify the constructs of port aesthetics and analyze its relationship with destination image, tourist satisfaction and tourist loyalty.

Five-port aesthetics constructs were identified, namely, leisure and culture, design and cognition, atmosphere, recreational facilities and memory. The results of SEM revealed the following: port aesthetics positively influenced destination image; destination image positively influenced tourist satisfaction; and tourist satisfaction had a positive influence on tourist loyalty. This research also found that the indirect effect of port aesthetics on tourist loyalty via destination image and tourist satisfaction.

While the environmental qualities of a port could potentially affect destination image, tourist satisfaction and loyalty, this study developed and validated a measurement instrument of perceived port aesthetics from a tourist’s perspective. Specifically, this research proposed a structural model to explain the relationships between port aesthetics, destination image, tourist satisfaction and loyalty.