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The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the highest vector embedding. Combining these models is used to optimize the model with increasing accuracy.

The development of the model in the study is divided into seven stages: (1) data collection, (2) pre-processing data, (3) selected pre-trained SentenceTransformers model, (4) semantic similarity (sentence pair), (5) keyword similarity, (6) calculate final score and (7) evaluating model.

The multilingual paraphrase-multilingual-MiniLM-L12-v2 and distilbert-base-multilingual-cased-v1 models got the highest scores from comparisons of 11 pre-trained multilingual models of SentenceTransformers with Indonesian data (Dhini and Girsang, 2023). Both multilingual models were adopted in this study. A combination of two parameters is obtained by comparing the response of the keyword extraction responses with the rubric keywords. Based on the experimental results, proposing a combination can increase the evaluation results by 0.2.

This study uses discussion forum data from the general biology course in online learning at the open university for the 2020.2 and 2021.2 semesters. Forum discussion ratings are still manual. In this survey, the authors created a model that automatically calculates the value of discussion forums, which are essays based on the lecturer's answers moreover rubrics.

Explore the use of Gender-Fair Language (GFL) by influencers on Instagram.

The clustering methodology. A digital Bag-of-Words (BoW) Method called GFL Clustering BoW Methodology to identify whether an inclusive marketing (IM) strategy can be used. Thus, this research has a methodological and practical contribution to increasing the number of marketing technology tools.

This study is original as it proposes an inclusive digital marketing strategy and contributes with methods associated with digital transfers in order to improve marketing strategies, tactics and operations for inclusive content with a data integrity approach.

Due to the limitations of the application programming interface (API) of the social network Instagram, a limited number of text data were used, which allowed for retrieving the last 12 publications of each studied profile. In addition, it should be considered that this study only includes the Spanish language and is applied to a sample of influencers from Chile.

The practical contribution of this study will lead to a key finding for the definition of communication strategies in both public and private organizations.

The originality of this work lies in its attractive implications for nonprofit and for-profit organizations, government bodies and private enterprises in the measurement of the success of campaigns with an IM communicational strategy and to incorporate inclusive and non-sexist content for their consumers so as to contribute to society.

本研究擬探究有影響力的人士在使用即時電報 (Instagram) 時、如何使用性別中立語言。

研究使用了聚類分析法;具體來說, 研究人員採用一個叫 GFL聚類詞袋法的數位詞袋分析法, 去確定研究可否使用信息管理策略。因此, 本研究在行銷科技方面、添加了一個工具, 就此而言, 本研究在學術的研究法和實務方面、均作出貢獻。

本研究建議了一個包括一切的數位行銷策略;研究亦構建了若干與數位傳輸有關的方法, 以能利用數據完整性的理念, 為行銷策略、行銷戰術和市場營銷, 在內容的全面包含度方面取得改善。

因為社交網站即時電報的應用程式介面有其局限, 故使用了少量的文本數據, 這可使每個被探討的傳略的最後12個發佈能被撿回。另外需注意的是、本研究只涵蓋西班牙語, 而且, 研究使用的樣本只是來自智利有影響力的人士。

本研究在實務方面的貢獻是、它為探討在公共機構和私營機構內使用的溝通策略的定義上、帶來重要的啟發和發現。

本研究的原創性在於它給營利和非營利組織、政府機關和私人企業帶來頗具吸引力的啟示。而這些啟示是與測量以包括一切的行銷溝通策略進行的專門活動是否成功有關的。另外, 涵蓋一切和無性別歧視的內容被納入供消費者使用, 以此為社會帶來裨益。

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and observe the important gaps in the literature that can inform a research agenda going forward.

A systematic literature strategy was utilized to identify and analyze scientific papers between 2012 and 2022. A total of 28 articles were identified and reviewed.

The outcomes reveal that while advances in machine learning have the potential to improve service access and delivery, there have been sporadic growth of literature in this area which is perhaps surprising given the immense potential of machine learning within the health sector. The findings further reveal that themes such as recordkeeping, drugs development and streamlining of treatment have primarily been focused on by the majority of authors in this area.

The search was limited to journal articles published in English, resulting in the exclusion of studies disseminated through alternative channels, such as conferences, and those published in languages other than English. Considering that scholars in developing nations may encounter less difficulty in disseminating their work through alternative channels and that numerous emerging nations employ languages other than English, it is plausible that certain research has been overlooked in the present investigation.

This review provides insights into future research avenues for theory, content and context on adoption of machine learning within the health sector.

The aim of this study was to identify interventions for and mechanisms of the digital transformation of purchasing and supply management (PSM) processes. The digital transformation of tactical and operational PSM processes has often progressed slowly despite the solid knowledge of advanced technologies.

This study used a qualitative exploratory approach based on 14 interviews with PSM executives from firms that are continuously working toward using advanced technologies in their PSM processes but have not yet gained full strategic benefits from digital transformation.

This study formulates five propositions regarding interventions and mechanisms that can positively influence the digital transformation of PSM processes. The main intervention in this regard is the renewal of data infrastructure, including platforms. PSM-related data should meet needs from both tactical and operational viewpoints. When applications serve as a source of data, they support digital transformation. Mechanisms such as supplier measurement and process improvement are outcomes of the digital transformation of PSM processes.

This study highlights the importance of common data sets for tactical and operational purchasing. These purchasing data should be owned and served by a cross-functional team. To create this interoperability, a firm needs global governance of open standards.

This study makes a theoretical contribution to the discussion of what kind of interventions positively influence on the digital transformation of PSM processes. Specifically, this study explains the integration needs of data and applications.

Background: Commodity-driven deforestation is a major driver of forest loss worldwide, and globalisation has increased the disconnect between producer and consumer countries. Recent due-diligence legislation aiming to improve supply chain sustainability covers major forest-risk commodities. However, the evidence base for specific commodities included within policy needs assessing to ensure effective reduction of embedded deforestation.

Methods: We conducted a rapid evidence synthesis in October 2020 using three databases; Google Scholar, Web of Science, and Scopus, to assess the literature and identify commodities with the highest deforestation risk linked to UK imports. Inclusion criteria include publication in the past 10 years and studies that didn't link commodity consumption to impacts or to the UK were excluded. The development of a review protocol was used to minimise bias and critical appraisal of underlying data and methods in studies was conducted in order to assess the uncertainties around results.

Results: From a total of 318 results, 17 studies were included in the final synthesis. These studies used various methodologies and input data, yet there is broad alignment on commodities, confirming that those included in due diligence legislation have a high deforestation risk. Soy, palm oil, and beef were identified as critical, with their production being concentrated in just a few global locations. However, there are also emerging commodities that have a high deforestation risk but are not included in legislation, such as sugar and coffee. These commodities are much less extensively studied in the literature and may warrant further research and consideration.

Conclusion: Policy recommendations in the selected studies suggests further strengthening of the UK due diligence legislation is needed. In particular, the provision of incentives for uptake of policies and wider stakeholder engagement, as well as continual review of commodities included to ensure a reduction in the UK's overseas deforestation footprint.

This chapter examines how darknet drug marketplaces operate within platform capitalism. While capitalist power relations remain underexplored in research on digital drug markets, the analysis shows that the basic foundation of cryptomarkets relies on the infrastructure of platform capitalism. The authors use the concept of platform capitalism to explore cryptomarkets in an ideology-critical way. Platforms are infrastructure for the mediation of buyers and vendors; however, they are designed to extract data on the activities of their users. Platform capitalism refers to the process by which the vast collection of user data feeds into the accumulation of capital. The authors use a dialectical method to examine the constellation of digital drug platforms by disclosing a threefold contradiction: state control and self-regulation; visibility and concealment; and legality and illegality. The analysis reveals that darknet drug platforms make a profit not only from the trade of illicit drugs and the collection of user data, but also based on the illegal status of drugs, the associated ideology, and the closed ecology of darknet platforms. Power relations in cryptomarkets thereby mimic those observed in platform capitalism in general. Finally, the authors discuss the implications of platform capitalism for online drug markets.

This paper aims to explore the extent to which principles of recovery-oriented practice are evident in the published perspectives and experiences of health professionals and service users on seclusion in adult mental health services.

A systematic review informed by PRISMA guidelines was conducted, drawing from four databases, which were searched in August 2018 and August 2022. Only original empirical studies rated as having “major” relevance were included. Data were extracted from 31 studies and qualitatively synthesised through deductive analysis using recovery principles as themes.

There was limited evidence of perceptions of seclusion being being consistent with recovery principles, with greater evidence of perceptions that directly opposed them. Studies of service user perspectives highlighted this more often than staff perspectives. The findings highlight paradoxical relationships between care and control and conflicting rights and emphasise the need to openly acknowledge the complexity of seclusion and its interface with recovery.

This review was developed in line with international best practice and the protocol was registered. Using a search string with only three components maximised sensitivity during searches and minimised the risk of relevant literature being missed. Limitations include the focus on studies where the full text was published in English.

This review makes a unique contribution, highlighting that, to the best of the authors’ knowledge, no studies to date have explicitly explored the perspectives and experiences of staff and service users on the use of seclusion in the context of recovery-oriented practice. The findings are relevant to clinical practice, policy and future research, including amending procedures and practices to partially reconcile seclusion and recovery where the seclusion is deemed necessary.

The tourism and hospitality sectors are experiencing radical innovation boosted by the advancements in Information and Communication Technologies. Increasingly sophisticated chatbots are introducing novel approaches, re-shaping the dynamics among tourists and service providers, and fostering a remarkable behavioral change in the overall sector. Therefore, the objective of this paper is two-folded: (1) to highlight the academic and industrial standing points with respect to the current chatbots designed/deployed in the tourism sector and (2) to develop a proof-of-concept embodying the most prominent opportunities in the tourism sector.

This work elaborates on the outcomes of a Systematic Literature Review (SLR) and a Focus Group (FG) composed of experts from the tourism industry. Moreover, it presents a proof-of-concept relying on the outcomes obtained from both SLR and FG. Eventually, the proof-of-concept has been tested with experts and practitioners of the tourism sector.

Among the findings elicited by this paper, we can mention the quick evolution of chatbot-based solutions, the need for continuous investments, upskilling, system innovation to tackle the eTourism challenges and the shift toward new dimensions (i.e. tourist-to-tourist-to-chatbot and personalized multi-stakeholder systems). In particular, we focus on the need for chatbot-based activity and thematic aggregation for next-generation tourists and service providers.

Both academic- and industrial-centered findings have been structured and discussed to foster the practitioners' future research. Moreover, the proof-of-concept presented in the paper is the first of its kind, which raised considerable interest from both technical and business-planning perspectives.

This study aims to examine the factors that influence the relationship between sustainability and financial performance (FP) of the European listed companies.

This study analyzed data from 795 companies in 21 European countries by applying linear mixed-effects multilevel regressions, a two steps system generalized method of moments and quantile regression models to uncover the links between sustainability and FP.

The past four decades have witnessed abundant research to determine the relationship between corporate sustainability and FP. Thus, conducting further research in 2023 could be seen as “reinventing the wheel.” Yet, earlier research considered firms as isolated entities with sustainability and FP being dependent only on that firm’s actions. By contrast, with the help of network governance theory, this study shows that a firm’s sustainability and FP depend on an interplay among interorganizational actors, such as institutional qualities, macroeconomic factors and an embrace of sustainability. Here, large firms play an essential role. Three significant findings are drawn. First, sustainability performance has a significant impact on FP in the European context. Second, the institutional quality (IQ) of the rule of law and control of corruption plays a crucial role in enhancing sustainability and FP, and finally the interaction of IQ and economic growth helps to increase companies’ market value (Tobin’s Q). The consistent and empirically robust findings offer key lessons to policymakers and practitioners on the interplay among multiple actors in corporate sustainability and FP.

A synergetic multifaced relationship between governmental institutions and corporations is inevitable for ensuring sustainable development. The degree of intimacy in the relationship, of course, will be determined by the macroeconomic environment.

In this research, this study theoretically and empirically identified that corporate sustainability and FP are not solely dependent on corporate operation. Rather, it is transformed, modified and shaped through an interaction of multiple actors’ trajectories in the macro business environment.

The aim of this paper is to understand if service innovation (Helkkula et al., 2018), based on artificial intelligence (AI) systems, may guarantee healthcare service ecosystem (H-SES) well-being (Frow et al., 2019; Beirão et al., 2017), taking into account that many doubts relieved in terms of transparency may compromise the patients' perceived quality of health services provided through AI systems.

A literature review on service innovation, detected in terms of value co-creation, and service ecosystem, investigated in terms of well-being, is drawn. To analyze the implications of service innovation on a H-SES well-being, through the technology acceptance degree and predisposition to use by actors, a case study based on TAM-model 3 determinants as categories is carried out.

AI-based service innovation archetypes in healthcare may be considered as antecedents of the service ecosystem well-being conditions as long as they enable actors to co-create value. To make it possible, a patient-driven service innovation is necessary in order to mitigate the risks of its inactivity due to fears in terms of transparency.

Service innovation and service ecosystem well-being may be studied in an integrated way, with a multidisciplinary approach, and are linked by value co-creation, because only thanks a patient-driven service innovation is possible to foster service ecosystem well-being in healthcare.