Search results

Despite the recent increase in vegetarian food consumption, studies on this topic have focused on the product category. Based on the functional theory of attitude and the cognitive–affective–conative framework, this study investigates the impact of customer individuality (i.e. uniqueness and level of self-monitoring) on cognitive attitude (i.e. social-function attitudes), which leads to conative attitude (i.e. behavioral intentions) via affective attitudes toward vegetarian restaurants.

The sample (n = 176) comprises experienced vegetarian restaurant customers in the USA. Multi-group analysis is used to examine differences between vegetarian and non-vegetarian customers, as well as customers' low and high frequency in visiting vegetarian restaurants.

Using partial least squares structural equation modeling, this study finds the relative impact of customers' personal traits on self-expressive and social-adjustive functions. Results highlight the role of the social-adjustive function as an antecedent of affective attitudes leading to positive behavioral intentions. Last, the findings from a multi-group analysis show that customer self-monitoring is the only significant antecedent of a cognitive attitude among vegetarian customers.

The present study adds to the literature regarding trait attributes and corresponding cognitive, affective and conative attitudes in the context of the vegetarian food service industry.

Young offender mentoring programmes aim to support young people’s desistance from offending, but despite the importance, there remains limited exploration into mentor experiences of supporting the young people. This study aims to explore how a community-based mentoring intervention supports desistance in young offenders by understanding the mentor's experiences, with a specific reflective focus on facilitators and barriers to their work.

Semi-structured interviews were conducted with seven mentors from Northumbria Coalition against Crime, a youth and community service. Interview transcripts were analysed using interpretative phenomenological analysis, with external auditing conducted by the research supervisor.

Two superordinate themes resulted: “Factors for engagement” and “Personal experiences”, with participant disclosures reflecting professional reward and a sense of success. This was interwoven with “burnout”, emotional investment and challenges linked to barriers to effectiveness. Challenges included the young people having external negative influences, multiple individuals involved in a person’s care and the barrier of in person activities during the coronavirus pandemic. The clinical importance of mentoring programmes, implications for future working practice and research limitations are considered.

The clinical importance of mentoring programmes, implications for future working practice and research limitations are considered.

These findings contribute to understanding mentors’ experiences of working with young people in the community, offering critical insight into the mentorship and wider service dynamics. Furthermore, it provides an inaugural evaluation of the Northumbria Coalition against Crime services.

This study aims to analyze the entrepreneurial intention (EI) of Colombian researchers using machine learning (ML) techniques, considering their academic activity, contexts and social norms (SN).

Unsupervised classification techniques were applied, including principal component analysis, hierarchical clustering with the Ward method and a logistic model to evaluate the classification. This was done to group researchers according to their characteristics and EI.

The methodology used allowed the identification of three groups of academics with distinct characteristics, of which two showed a high presence of EI. The results indicate that EI is influenced by the connection with the private sector (consulting, intellectual property and applied research) and by the lack of institutional support from universities. Regarding SN, only the preference for entrepreneurial activity over being an employee and the social appreciation of entrepreneurial dedication were identified as predictors of EI.

The use of ML techniques to study the EI of researchers is uncommon. This study highlights the ability of the methodology used to identify differences between two groups of academics with similar characteristics but different levels of EI. One group was identified that, despite rejecting values associated with entrepreneurs, has a high predisposition to develop a career as an entrepreneur. This provides valuable information for designing policies that promote EI among Colombian researchers.

Cause-related B2B marketing programs involve sponsoring organisations working with B2B suppliers with the help of non-profit organisations (NPOs) on practises relating to environmental friendliness, workforce diversity, human rights, safety, philanthropy and business ethics. The study aims to identify the combinatory factors driving the adoption of Digital B2B platforms for managing cause-related B2B marketing programs.

The study adopts an innovative approach of fuzzy-set qualitative comparative analysis (fsQCA) on data collated from top corporations in India supporting cause-related B2B marketing programs. Sponsoring organisations and NPO dyads (i.e. survey both) filled out an email survey on 264 cause-related B2B marketing programs.

The study establishes that the combination of technological, organisational and environmental factors would lead to the adoption of Digital B2B platforms in managing cause-related B2B marketing programs. The study identifies six combinations of these factors for adopting Digital B2B platforms within and across sponsoring organisations and NPOs.

The study findings would aid cause-related B2B marketers in developing Digital B2B platforms’ capabilities by understanding the different combinations of factors driving adoption. Digital B2B platforms’ capabilities can improve market performance if developed as core competencies.

The study findings would enable improvements in the implementation and performance of cause-related B2B marketing programs. Better management of cause-related B2B marketing programs would help increase beneficiary coverage and the realisation of societal goals.

To the author’s knowledge, this is the first study to apply the TOE framework in conjunction with complexity theory to explain the diffusion of adoption of Digital B2B platforms for managing cause-related B2B marketing programs.

This study offers an empirical framework for how hotel employees CSR perceptions affect their job satisfaction by incorporating the parallel mediating roles of organizational identification and psychological contract fulfillment. In addition, it examines the moderator effects of employees' CSR-induced attributions on the constructed mediated model, providing a powerful lens through which to evaluate when and how employees' CSR perceptions influence organizational identification and psychological contract fulfillment.

The study use PLS-SEM techniques to analyze a sample of 520 employees from 49 luxury hotels with 4–5 stars in Khanh Hoa province, Vietnam.

The results show that CSR positively influences job satisfaction through the mediating role of psychological contract fulfillment and organizational identification. Besides, attachment styles also play moderator role in the relationship between CSR and psychological contract fulfillment/organizational identification.

The discoveries elucidated within this research endeavor proffer actionable discernments to be earnestly contemplated by professionals entrenched in the hotel industry, earnestly aspiring to ameliorate the contentment of their workforce and, concomitantly, augment the overarching efficacy of their organizational operations.

This study provides human resource departments with insights and suggestions for maximizing the efficacy of CSR implementation in the hotel industry.

This paper aims to evaluate the Digital Government Collaborative Platform (DGCP), which facilitates collaborations between the citizens and the government to address environmental issues in Sri Lanka. The DGCP is an artifact developed by the value-sensitive design approach.

The DGCP is evaluated following the Framework for Evaluation in Design Science Research (FEDS). In total, 224 citizens participated in the survey based on the User Experience Questionnaire (UEQ) and open questions about human values embedded in the design. Fifteen government officers were interviewed to enhance the evaluation.

The DGCP received positive evaluations from the citizens and government officers. The platform is attractive, novel and pragmatic, also generating hedonic experiences for the citizens. The users believed that human values are reflected in the DGCP. Furthermore, they shared a few suggestions to improve it.

The paper contributes knowledge to evaluating digital government systems, especially in developing countries. The human-value-centered DGCP was evaluated using multiple methods of quantitative (i.e. UEQ Survey) and qualitative (i.e. qualitative interviews with stakeholders) techniques. Furthermore, the systematic process of DGCP evaluation produces a case-based guideline for evaluating related and similar digital government systems using FEDS.

A novel method has been proposed to reduce the false alarm rate of arrhythmia patients regarding life-threatening conditions in the intensive care unit. In this purpose, the atrial blood pressure, photoplethysmogram (PLETH), electrocardiogram (ECG) and respiratory (RESP) signals are considered as input signals.

Three machine learning approaches feed-forward artificial neural network (ANN), ensemble learning method and k-nearest neighbors searching methods are used to detect the false alarm. The proposed method has been implemented using Arduino and MATLAB/SIMULINK for real-time ICU-arrhythmia patients' monitoring data.

The proposed method detects the false alarm with an accuracy of 99.4 per cent during asystole, 100 per cent during ventricular flutter, 98.5 per cent during ventricular tachycardia, 99.6 per cent during bradycardia and 100 per cent during tachycardia. The proposed framework is adaptive in many scenarios, easy to implement, computationally friendly and highly accurate and robust with overfitting issue.

As ECG signals consisting with PQRST wave, any deviation from the normal pattern may signify some alarming conditions. These deviations can be utilized as input to classifiers for the detection of false alarms; hence, there is no need for other feature extraction techniques. Feed-forward ANN with the Lavenberg–Marquardt algorithm has shown higher rate of convergence than other neural network algorithms which helps provide better accuracy with no overfitting.

Because of the global increase of climate change effects, floods are becoming more frequent and severer, especially in urban areas of coastal cities and islands where floodplains have turned into buildings because of rapid urbanisation, leading to a higher risk of damages. Urban heritage areas should be highly considered in the time of evacuation because of the vulnerability of streets and buildings and limitations on taking counteractions. Given these limitations, this study aims to propose a network of potential evacuation routes based on spatial configuration analysis of the heritage areas.

Penang Island's heritage site, namely, George Town, located on the northwest coast of Malaysia, is chosen as the case study. By using an approach of spatial configuration analysis using space syntax techniques in addition to considering the potential starting points for evacuation and flood risk map of the area, this study analysed the area's street network values for evacuation function during flood crisis time.

Potential evacuation routes were identified for flood disasters in the George Town heritage area. Furthermore, the proposed evacuation routes were evaluated in terms of time for evacuation by metric step-depth analysis of space syntax.

A few studies have focused on practical guidelines for evacuation routes based on spatial configuration analysis, an important yet neglected approach in this regard, especially concerning urban island areas. This study can contribute to providing strategies to reduce vulnerability and casualties in urban heritage areas.

The commercialization of research produced by universities constitutes a core facet of academic entrepreneurship (AE). Academic literature reveals the need to shed light on entrepreneurial processes in higher education institutions (HEIs). This study intends to fill this gap by researching the mechanisms for facilitating AE and the variables that can moderate the relationship between such mechanisms and AE in Portuguese HEIs.

Our research model aims to assess the mechanisms of academic entrepreneurship (AE) within a sample of 125 Portuguese public higher education institutions (HEIs). To test our research hypotheses, we employed a structural equation model (SEM) using the partial least squares (PLS) method. Additionally, our evaluation examines the potential moderating effects of incubator programs, support initiatives, and proof-of-concept programs (PoCs). Our research model seeks to evaluate the mechanisms for facilitating AE and explore the effects of including incubator programs, support initiatives, and PoCs as moderators. The seven variables (Research mobilization, Unconventionality, Industry collaboration, University policies, Incubator programs and support initiatives, Proof-of-concept programs, and academic entrepreneurship) were measured using a 7-point Likert scale.

The results revealed that different drivers of AE influence the creation and development of entrepreneurial activities. Our findings also show the moderating effects of incubator programs, support initiatives, and proof-of-concept programs on AE. We find that incubator programs, other support initiatives, and PoCs maintain a moderating effect on AE and benefit their respective HEIs.

The study examines only the Portuguese HEI context. Therefore, generalizing these results necessitates reservations. However, the responses came from various actors in HEIs, from different academic backgrounds and research interests. This makes the results more generalizable. Limitations are evident in external validity, given that we gathered the data over a relatively short period.

Observed factors are explored to gain a deeper understanding of their influence on the mechanisms of AE. The implications arise from the new perspective presented and the methodology used to identify mechanisms capable of fostering AE. We hope this research will encourage other researchers to study this topic further.

the engagement of universities at the global level should be emphasised in future policy. While universities in innovation systems often have a local focus, their engagement in innovation ecosystems transcends the boundaries of geographic locations.

PoCs had a significant positive moderating effect on the impact of research mobilization and university policies on AE. Thus, we find interactions between universities and industry boost AE. This study demonstrates how AE benefits HEIs by extending orientation towards mobilizing research, unconventional approaches, cooperation with industry, and university policy implementation. We thus advocate a new approach, demonstrating the influence that the mobility of research, unconventionality, industry collaboration, and university policies hold over AE.

This study aims to investigate the behavior of different types of stone columns, including the short and floating columns, as well as the ordinary and the geosynthetic encased stone columns (OSC and GESC). The effectiveness of the geosynthetic encasement and the impact of the installation using the lateral expansion method on the column performance is evaluated through a three-dimensional (3D) unit cell numerical analysis.

A full 3D numerical analysis is carried out using the explicit finite element code PLAXIS 3D to examine the installation influence on settlement reduction (ß), lateral displacement (U_x) and vertical displacement (U_z) relative to different values of lateral expansion of the column (0% to 15%).

The findings demonstrate the superior performance of GESC, particularly short columns outperforming floating counterparts. This enhanced performance is attributed to the combined effects of geosynthetic encasement and increased lateral expansion. Notably, these strategies contribute significantly to decreasing lateral displacement (U_x) at the column’s edge and reducing vertical displacement (U_z) under the rigid footing.

In contrast to previous studies that examined the installation effect of OSC contexts, this paper presents a comprehensive investigation into the effect of geosynthetic encasement and the installation effects using the lateral expansion method in very soft soil, using 3D numerical simulation. The study emphasizes the significance of the consideration of geosynthetic encasement and lateral expansion of the column during the design process to enhance column performance.