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Taiwan’s hotel industry was adversely impacted by the COVID-19 pandemic. This study aims to examine the effect of strategic choices by Taiwanese international tourist hotels before and during the pandemic environments.

A data envelopment analysis (DEA)-based Malmquist methodology is used in this study to provide a mechanism to assess Taiwanese hotel strategy performance. Changes in the productivity and performance of Taiwanese international tourist hotels were analyzed in the periods before and during the pandemic to uncover insights useful should a similar crisis occur in the future. Panel data were obtained from the annual report of international tourist hotels published by the Taiwan Tourism Bureau from 2017–2020. Two groups of hotels were analyzed in this study: city hotels and scenic hotels.

The findings of this study reveal that chain hotels tended to perform better than independent hotels in both city and scenic areas during the global pandemic. Specifically, the crisis caused a substantial decline in productivity and profitability for international tourist hotels in Taipei City during the COVID-19 period. Compared to city hotels, findings also indicate that most international tourist hotels in scenic areas were able to maintain better productivity, including larger-sized scenic hotels.

The DEA-based analysis provides unique and valuable insights for hotel firm leaders on how to better identify and make strategic choices when responding to future crises.

This paper focuses on image-to-text manuscript processing through Handwritten Text Recognition (HTR), a Machine Learning (ML) approach enabled by Artificial Intelligence (AI). With HTR now achieving high levels of accuracy, we consider its potential impact on our near-future information environment and knowledge of the past.

In undertaking a more constructivist analysis, we identified gaps in the current literature through a Grounded Theory Method (GTM). This guided an iterative process of concept mapping through writing sprints in workshop settings. We identified, explored and confirmed themes through group discussion and a further interrogation of relevant literature, until reaching saturation.

Catalogued as part of our GTM, 120 published texts underpin this paper. We found that HTR facilitates accurate transcription and dataset cleaning, while facilitating access to a variety of historical material. HTR contributes to a virtuous cycle of dataset production and can inform the development of online cataloguing. However, current limitations include dependency on digitisation pipelines, potential archival history omission and entrenchment of bias. We also cite near-future HTR considerations. These include encouraging open access, integrating advanced AI processes and metadata extraction; legal and moral issues surrounding copyright and data ethics; crediting individuals’ transcription contributions and HTR’s environmental costs.

Our research produces a set of best practice recommendations for researchers, data providers and memory institutions, surrounding HTR use. This forms an initial, though not comprehensive, blueprint for directing future HTR research. In pursuing this, the narrative that HTR’s speed and efficiency will simply transform scholarship in archives is deconstructed.

Organic food processing must include organic principles to be authentic. This qualitative study aims to understand the processors' understanding of organic food processing quality.

This study is based on semi-structured expert interviews with eight employees of six purely or partly organic dairies from Germany and Switzerland. Interview themes are (1) quality of organic milk processing in general, (2) assessment of specific processing techniques, (3) product quality of organic milk and (4) flow of information between producer and consumer. The interviews have been audio-recorded, transcribed verbatim and thematically analysed.

(1) Experts prefer minimal processing; some prefer artisanal processing, whilst others stress the advantages of mechanisation. (2) High temperature short time (HTST) pasteurisation and mechanical processing techniques are accepted; ultra-high-temperature (UHT) milk processing is partly rejected. (3) Traditional taste and valuable ingredients should be present in the final product. Natural variances are judged positively. (4) Consumers' low level of food technology literacy is challenging for communication.

The results cannot be generalised due to the qualitative study design. Further studies, e.g. qualitative case analyses and studies with a quantitative design, are necessary to deepen the results.

The paper shows which processing technologies experts consider suitable or unsuitable for organic milk. The paper also identifies opportunities to bridge the perceived gap between processors' and consumers' demands.

The study shows the challenges of processors in expressing the processors' understanding of process quality.

This study aims to investigate the influence of specific socioeconomic factors, namely neighborhood, gender roles and affordability, on the continuous use of clean cooking technologies (CCTs) in households, using evidence from Uganda.

This study adopted an explanatory quantitative design. A questionnaire survey with 379 clean household responses was conducted. The data were analyzed using the Smart Partial Least Squares (PLS) software.

The results indicate that the sustained use of clean cooking technologies in households in Uganda is significantly associated with neighborhood influence, shared gender roles and affordability, collectively accounting for 27.7% of the variance.

The three dimensions of socioeconomic factors under study partially explain the sustained use of CCTs in Uganda. The study does not delve into other socioeconomic factors that could probably account for 72.2% of the variance not explained. The quantitative design may have overlooked the social reality perspectives inherent in qualitative studies that other researchers may endeavor to exploit.

The authors integrated three dimensions of socioeconomic factors – neighborhood influence, gender roles and affordability – with the diffusion of innovation theory (DIT) using Smart PLS to explain the continuous use of CCTs within households.