bluuebunny/crossref_metadata_2025_split huggingface dataset:
Community services during the COVID-19 pandemic in a Norwegian county: impact on users with multiple, complex needs and their service providers – a qualitative study
Authors: Hørsrud Linda Kristin , Bakken Trine Lise 
Published: September 2022

Purpose
The purpose of this paper is to investigate how users with particularly complex needs including intellectual disability (ID) reacted to the changes and restrictions during the COVID-19 pandemic in 2020.

Design/methodology/approach
As few studies of changes during the pandemic include users with ID and multiple, complex needs, the authors adopted a qualitative approach, using a semistructured interview guide. Ten participants were leading ID nurses in residential facilities in community settings. The interviews were taped, transcribed and analyzed using a thematic analysis.

Findings
The thematic analysis generated six main themes, including both user and staff perspectives: daily routines, activities, facilitation of tasks and well-being, from the users perspectives, and use of working hours and positive staff experiences, from the staff perspectives.

Research limitations/implications
Ten residential facilities constituted a convenience sample of services for users with multiple, complex needs. Thus, the authors do not know whether the findings are representative. Further research should include user opinions based on the findings of this study.

Practical implications
The users represented in this study appeared to experience less stress during the pandemic, contrary to the expectations of professional caregivers. The findings indicated more well-being among users. It was noted that receiving services at home, largely flexible schedules, staying in bed a little longer in the morning and avoiding stressful situations, such as travelling in minibuses, was appreciated by the users.

Social implications
Daily schedules with activities throughout the day should be considered for users as represented in this study. Stressful events should also be considered.

Originality/value
The knowledge about pandemic experiences of users with ID and additional complex conditions and hence comprehensive needs is still sparse. This study may add to this knowledge.
Consumers' attitudes to gourmet burgers: the case of the NOMA cheeseburger
Authors: Leer Jonatan , Hoff-Jørgensen Camilla 
Published: September 2022

PurposeThis article explores consumers' attitudes to the trend of gourmet burgers, notably the gourmet burgers' combination of highbrow food (gourmet) and lowbrow food (fast food). The authors use the case of the NOMA cheeseburger from the iconic New Nordic restaurant NOMA.Design/methodology/approachThe data set consists of interviews (n = 20) with urban Danish consumers attending the NOMA burger pop-up.FindingsThe analysis highlights an acceptance among informants of “gourmetfied” burgers. This signals a change in the culinary status of burgers in Danish food culture. The authors also discovered some ambivalence in relation to the highbrow-lowbrow negotiations: while all informants celebrate the casualization of NOMA during the burger pop-up, half of the informants found the burger underwhelming: it did not live up to the edginess of the NOMA brand.Practical implicationsThe authors believe this research can inform people working with culinary highbrow-lowbrow mix in their food designs, notably in relation to developing and matching the relation between symbolic and material aspects of the food design.Originality/valueThe authors argue that the concept of transgression can help us theorize how consumers accept, refuse, and negotiate boundaries in relation to gourmet burgers, and more generally between food consumption mixing highbrow and lowbrow elements. More particularly, the authors propose to distinguish between symbolic, social, and material transgressions. This perspective might also be interesting for practitioners in the field.
Sustainable women empowerment at the bottom of the pyramid through credit access
Authors: Pal Mukesh , Gupta Hemant 
Published: September 2022

PurposeThe importance of gender in inclusive economic growth has been a growing area of research. Finance is seen as an efficacious instrument for social inclusion, and sustainable women empowerment (SWE). The lack of credit access often constrains women to scale up. The objective of this study is to examine the attributes influencing the decision of women to access the credit at the bottom of the pyramid (BoP) and the impact of this credit access on social, psychological and economic dimensions of SWE at the BoP in rural India.Design/methodology/approachThe threshold theory of decision-making in the form of logistic regression (LR) is applied here to analyze the influence of four determinants, namely individual household level (IHLA), social attributes (SA), economic attributes (EA) and ownership of documents (OD) on women’s credit access. Likewise, the same method is applied to study the relationship between credit access and three dimensions of SWE.FindingsThe results have revealed a statistically significant relationship between credit access and studied four attributes. Subsequently, a positive relationship has been observed between credit access and dimensions of SWE.Originality/valueThe present study broadly addresses the concern of accessing credit by women at BoP level, which helps the government and policymakers to promote enabling an environment for women entrepreneurship and comprehensive financial policies for the BoP.
Customer harassment against LGBTQ workers: highlighting its uniqueness as a group-based customer harassment
Authors: Ueno Koji , Ritter Lacey J. , Ingram Randi , Jackson Taylor M. , Šaras Emily Daina , D'Amours Jason V. , Grace Jessi 
Published: September 2022

PurposeThe authors aimed to identify the nature of customer harassment against lesbian, gay, bisexual, transgender, and queer (LGBTQ) workers.Design/methodology/approachThe authors analyzed data from in-depth interviews with 30 LGBTQ service workers in the United States who had recently experienced customer harassment.FindingsAmong various forms of customer harassment LGBTQ workers reported, some showed commonalities with previously reported cases of race-based and gender-based customer harassment. However, other cases highlighted unique aspects of LGBTQ-based customer harassment—customers morally condemned their LGBTQ identities, refused their service while displaying emotional disgust, and made sexual advances while imposing sexual stereotypes and fantasies about LGBTQ people. Experiences of customer harassment varied across subgroups of workers who had specific sexual and gender identities, and LGBTQ workers of color were harassed for their LGBTQ and racial identities simultaneously.Originality/valuePast research on group-based customer harassment has focused on incidents against straight, cisgender women and workers of workers of color, but the present study identified the nature of customer harassment that targeted workers' LGBTQ status.
The impact of GDPR infringement fines on the market value of firms
Authors: Ford Adrian , Al-Nemrat Ameer , Ghorashi Seyed Ali , Davidson Julia 
Published: September 2022

Purpose
This paper aims to investigate the impact of the General Data Protection Regulation (GDPR) infringement fine announcements on the market value of mostly European publicly listed companies with a view to reinforcing the importance of data privacy compliance, thereby informing cyber security investment strategies for organisations.

Design/methodology/approach
Previous studies have shown (varying degrees of) evidence of a negative impact of data breach announcements on the share price of publicly listed companies. Following on from this research, further studies have been carried out in assessing the economic impact of the introduction of legislation in this area to encourage firms to invest in cyber security and protect the privacy of data subjects. Existing research has been predominantly US centric.

Findings
Using event study techniques, a data set of 25 GDPR fine announcement events was analysed, and statistically significant cumulative abnormal returns of around 1% on average up to three days after the event were identified. In almost all cases, this negative economic impact on market value far outweighed the monetary value of the fine itself, and relatively minor fines could result in major market valuation losses for companies, even those having large market capitalisations.

Originality/value
This research would be of benefit to business management, practitioners of cyber security, investors and shareholders as well as researchers in cyber security or related fields (pointers to future research are given). Data protection authorities may also find this work of interest.
Appraisal of climate change mitigation and adaptation regulatory frameworks in Ethiopia and their congruency with the UN climate change convention
Authors: Bisare Bitire Bilate 
Published: September 2022

PurposeThe purpose of this paper is to critically investigate the Ethiopia’s climate change adaptation and mitigation regulatory frameworks and their congruency with the guiding principles under the United Nations (UN) Climate Convention, to show the alignment of the regulatory frameworks with the UN Climate Change rules. Rising temperatures, erratic rainfall distribution, recurrent droughts and floods require robust climate change mitigation and adaptation policies and effective implementation in the country.Design/methodology/approachThrough the doctrinal legal research method, the author has used a detailed analysis of primary sources, both national and international legislative enactments. Besides, the research has benefitted from secondary sources like research reports, online publications, scientific journals, international reports, books and journal articles.FindingsThe findings reveal that in Ethiopia, there is no national climate change-specific policy and legislation. Although there are scattered sectoral climate-related policies and strategies, they are not consistent with the principles of the United Nations Framework Convention on Climate Change (UNFCCC).Originality/valueThis study argues that having comprehensive specific climate change policy and legislative frameworks consistent with UNFCCC guiding principles could help to mitigate and adapt to the adverse effects of climate change in the country.
Do efforts to address safety pay off? Evidence from the sharing economy in the post–pandemic world
Authors: Qi Rui , Chen Han 
Published: September 2022

Purpose
Applying the value creation of corporate social responsibility (CSR), this study aims to investigate the direct effect of preventive measures in the postpandemic world on Airbnb consumers’ attitudes toward the host, which may further impact their behavioral intentions. It also examined the mediating role of perceived risk and perceived motives, as well as the moderating role of message strategies and risk tolerance in this process.

Design/methodology/approach
A 2 (preventive measures: basic versus enhanced) × 2 (message strategies: promotional social cause message [PSC] versus partake-in-our-cause message [PIOC]) between-subjects factorial design was conducted with a sample of 476 US Airbnb consumers through an online survey. PROCESS macro was used for hypothesis testing.

Findings
Results demonstrated that enhanced preventive measures had more positive impact on Airbnb consumers’ attitudes toward the host, which was positively related to positive word of mouth and booking intention. Perceived risk and perceived motives mediated the relationship between preventive measures and attitude toward Airbnb hosts. Positive relationships between attitude toward the host and behavioral intentions were strengthened when PIOC was used than PSC. The negative relationship between preventive measures and perceived risk was enhanced when PIOC was used than PSC. Risk tolerance did not interact with messages strategy to impact the relationship between preventive measures and perceived risk.

Originality/value
The study uncovered the mechanisms by which consumers form their responses toward different safety information of Airbnb accommodations postpandemic and the role of message strategies in the process. It provided implications for the Airbnb platform and hosts in the postpandemic period.
Exploring customers' switching from native to lightweight apps: a push–pull–mooring framework perspective
Authors: Chen Yuan , Li Xiaodong , Li Qi , Li Wenjie 
Published: September 2022

PurposeLightweight apps such as WeChat mini programs (WMPs) are an emerging mobile channel (m-channel) touchpoint that have gained remarkable popularity among consumers. Despite the focus of migration research on traditional m-channel touchpoints (e.g. native apps and mobile websites), but few researchers have examined why consumers switch from native to lightweight apps. Drawing on the push-pull-mooring framework, this study aims to identify the key factors influencing consumers' switching related to lightweight apps.Design/methodology/approachThe data were collected using a questionnaire survey of 416 WMP consumers and the proposed model was analyzed through structural equation modeling.FindingsThe results show that the push effect, specifically, high privacy concern, nudges consumers away from native apps, whereas the pull effects, including relative ease of use, convenience of access and exit and socially-oriented interaction, entice consumers to lightweight apps. Further, consumer switching intention is influenced by habit and perceived technology control, both of which reflect the mooring effects. Switching intention also stands as an important precedent of actual behavior.Originality/valueThis study is among the first theoretical explorations of consumer switching across m-channel touchpoints in the context of mobile commerce. For information system practice, these findings provide new insights for both incumbent providers and newcomers on how to retain existing shoppers as well as attract potential shoppers effectively.
Robot programming by demonstration with a monocular RGB camera
Authors: Wang Kaimeng , Tang Te 
Published: September 2022

Purpose
This paper aims to present a new approach for robot programming by demonstration, which generates robot programs by tracking 6 dimensional (6D) pose of the demonstrator’s hand using a single red green blue (RGB) camera without requiring any additional sensors.

Design/methodology/approach
The proposed method learns robot grasps and trajectories directly from a single human demonstration by tracking the movements of both human hands and objects. To recover the 6D pose of an object from a single RGB image, a deep learning–based method is used to detect the keypoints of the object first and then solve a perspective-n-point problem. This method is first extended to estimate the 6D pose of the nonrigid hand by separating fingers into multiple rigid bones linked with hand joints. The accurate robot grasp can be generated according to the relative positions between hands and objects in the 2 dimensional space. Robot end-effector trajectories are generated from hand movements and then refined by objects’ start and end positions.

Findings
Experiments are conducted on a FANUC LR Mate 200iD robot to verify the proposed approach. The results show the feasibility of generating robot programs by observing human demonstration once using a single RGB camera.

Originality/value
The proposed approach provides an efficient and low-cost robot programming method with a single RGB camera. A new 6D hand pose estimation approach, which is used to generate robot grasps and trajectories, is developed.
An explainable attention-based bidirectional GRU model for pedagogical classification of MOOCs
Authors: Sebbaq Hanane , El Faddouli Nour-eddine 
Published: September 2022

Purpose
The purpose of this study is, First, to leverage the limitation of annotated data and to identify the cognitive level of learning objectives efficiently, this study adopts transfer learning by using word2vec and a bidirectional gated recurrent units (GRU) that can fully take into account the context and improves the classification of the model. This study adds a layer based on attention mechanism (AM), which captures the context vector and gives keywords higher weight for text classification. Second, this study explains the authors’ model’s results with local interpretable model-agnostic explanations (LIME).

Design/methodology/approach
Bloom's taxonomy levels of cognition are commonly used as a reference standard for identifying e-learning contents. Many action verbs in Bloom's taxonomy, however, overlap at different levels of the hierarchy, causing uncertainty regarding the cognitive level expected. Some studies have looked into the cognitive classification of e-learning content but none has looked into learning objectives. On the other hand, most of these research papers just adopt classical machine learning algorithms. The main constraint of this study is the availability of annotated learning objectives data sets. This study managed to build a data set of 2,400 learning objectives, but this size remains limited.

Findings
This study’s experiments show that the proposed model achieves highest scores of accuracy: 90.62%, F1-score and loss. The proposed model succeeds in classifying learning objectives, which contain ambiguous verb from the Bloom’s taxonomy action verbs, while the same model without the attention layer fails. This study’s LIME explainer aids in visualizing the most essential features of the text, which contributes to justifying the final classification.

Originality/value
In this study, the main objective is to propose a model that outperforms the baseline models for learning objectives classification based on the six cognitive levels of Bloom's taxonomy. In this sense, this study builds the bidirectional GRU (BiGRU)-attention model based on the combination of the BiGRU algorithm with the AM. This study feeds the architecture with word2vec embeddings. To prove the effectiveness of the proposed model, this study compares it with four classical machine learning algorithms that are widely used for the cognitive classification of text: Bayes naive, logistic regression, support vector machine and K-nearest neighbors and with GRU. The main constraint related to this study is the absence of annotated data; there is no annotated learning objective data set based on Bloom’s taxonomy's cognitive levels. To overcome this problem, this study seemed to have no choice but to build the data set.
Interconnections and continuity among planning documents of Kota Lama Semarang development within the context of urban heritage conservation
Authors: Kartikasari Anisa Nurul , Wibisono Bambang Hari 
Published: September 2022

PurposeUrban conservation is an integral part of urban development planning and it is incorporated into land use rules and plans. In order to achieve the goals of an ideal heritage conservation policy, there are spatial plans, building codes and relevant regulations that should be well prepared as reference for development projects. Kota Lama Semarang (Old City of Semarang) area has been recognized as part of the origin of the development of Semarang City, the capital city of Central Java. This area has been designated as a cultural heritage area both at the city and national level since 2020. The Heritage City Conservation Program (P3KP) encourages Kota Lama Semarang Area to experience fairly massive development since 2013. On one hand, to control and manage the area, the Semarang City Government issued several official planning documents, i.e. (a) Kota Lama Semarang Area RTBL documents (2003); (b) Kota Lama Semarang Grand Design (2011); and (c) Kota Lama Semarang Site RTBL (2020), which consecutively were used as references of development projects. On the other hand, the results of development projects indicated that there are no coherent physical improvements in the area. The study was conducted to show whether there are consistencies or mismatches between the three planning documents.Design/methodology/approachThis study used a qualitative deductive method with content analysis technique to compare three planning documents, using the predetermined variables.FindingsThe results showed that the consistency between the three planning documents was not fully demonstrated, but they are mutually interconnected.Research limitations/implicationsThe research focused only on three formal planning documents, for which comparative analysis was undertaken using content analysis to identify consistencies and inconsistencies based on determined 9 variables.Practical implicationsGood planning documents should be consistent, since they are used as development references. Inconsistencies among planning documents produced segmented urban environments in Kota Lama Semarang Area/Site, which are mostly due to the different institutions preparing the documents.Social implicationsThe segmented urban development in the area has reduced the historical and cultural values of the area. Revitalization program that was undertaken has some implication to the sustainability of the local economy.Originality/valueThe paper explores both the consistencies and mismatches among the three planning documents, which have been used as references in implementing development projects in Kota Lama Semarang Area. Failures in maintaining consistencies among documents are supposed to produce inconsistent physical development in the area, unless adjustment to current development has to be made.
Digital media recording and broadcasting classroom using Internet intelligent image positioning and opinion monitoring in communication
Authors: Wu Huanchao 
Published: September 2022

PurposeThe digital media recording and broadcasting classroom using Internet real-time intelligent image positioning and opinion monitoring in communication teaching is researched and analyzed.Design/methodology/approachFirst, spatial grid positioning and monitoring and image intelligent recognition technologies were used to extract and analyze teaching images by mastering Internet of Things (IoT) technology and establishing an intelligent image positioning and opinion monitoring digital media recording and broadcasting system framework. Next, a positioning node algorithm was utilized to measure the image distance, and then a moving node location model under the IoT was established. In addition, a radial basis function (RBF) neural network was used to realize the signal transmission function. The experimental data of the adopted RBF based on the optimization of the adaptive cuckoo search (ACS-RBF) neural network, particle swarm algorithm neural network, and method of least squares optimization were compared and analyzed. In addition, a more efficient RBF neural network was adopted. Finally, the digital media recording and broadcasting classroom scheme of real-time intelligent image positioning and opinion monitoring was designed. In addition, the application environment of digital media actual teacher teaching was detected, and recording and broadcasting pictures were analyzed and researched.FindingsThe actual value, predicted value, and the number of predicted samples of the ACS-RBF model were all better than those of the two other neural networks. According to the analysis and comparison of the sampling optimization Monte Carlo localization (SOMCL), Monte Carlo, and genetic algorithm optimization-based Monte Carlo positioning algorithms, the SOMCL algorithm showed better robustness, and its positioning efficiency was superior to that of the two other algorithms. In addition, the SOMCL algorithm greatly reduced the positioning and monitoring energy consumption.Originality/valueThe application of real-time intelligent image positioning and monitoring technology in actual communication teaching was realized in the study.