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The purpose of this paper to analyze the effect of Soret with heat and mass transfer on an unsteady two-dimensional Magnetohydrodynamics flow through a porous medium under the influence of the uniform transverse magnetic field in a rotating parallel plate is considered.

A mathematical model was developed using the slip conditions under unsteady state situations. Analytical expressions for the velocity, temperature and concentration profiles, wall shear stress, rates of heat and mass transfer and volumetric flow rate were obtained and computationally discussed with respect to the non-dimensional parameters. Further, the velocity reduces with increasing Hartmann number M and increases with Grashof number Gr and permeability parameter K.

It is observed that temperature reduces with an increase in Prandtl number Pr and ω. It is noted that the thermal radiation increases with increase in Soret number Sr, Schmidt number Sc, Prandtl number pr and ω.

Concentration decreases with an increase in radiation parameter R and chemical reaction parameter Kc.

There are calls for irradiated food labelling due to a significant need for food safety and extensive procedures to safeguard consumer health. Additionally, there is a strong push from producers for mandatory Country of Origin (COO) labelling. The study examines how the COO and Radura labels influence consumer behaviour and shows the interplay between these influences. Using Attitude-Behavior-Context theory, a conceptual model is proposed and tested to evaluate these factors. The use of multiple labels allows for more choices. How the information presented on labels corresponds to consumers' pre-purchase information search is tested on regular label users.

Structural Equation Modelling (SEM), Generalised Linear Modelling and Cluster Analysis were used to analyse the data on a sample of 322 Australian respondents.

The study revealed that COO labelling had a significant positive relationship with attitudes but a negative relationship with WTP, acting as a suppressed mediator between attitudes and WTP. Interestingly, while knowledge was not found significant, label confidence emerged as a significant factor. Furthermore, the research suggests that regular users may prioritize COO labels over Radura labels.

This research contributes novelty by being the first to address the interplay between COO and irradiated labels, complementing the growing body of literature on irradiation labelling. It also offers valuable insights for retail practitioners, providing an understanding that can facilitate the delivery of high-value multiple labels at the point of purchase.

The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.

Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.

Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.

The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.

This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.

This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.

This research demonstrates the theoretical merit of a reference architecture-based approach to life cycle cost (LCC) analysis system provision in the built environment. LCC insight is considered fundamental to sustainable decision making by asset managers; however, the current capabilities in practice do not align with the political ambition and the scale of competencies required to realise sectoral emissions–reduction targets.

In pursuing practical outcomes, the study employs a custom design science research-inspired methodology. Domain requirements are gathered via literature research as an initial top-down software reference architecture which is refined, bottom-up, through testing and implementation in a representative case study. A prototype IT system and reference architecture artefact are developed and used to evaluate the concept qualitatively through broad practitioner focus groups.

Sentiment analysis of the expert opinions is broadly positive and helps to substantiate the proposal’s theoretical suitability in addressing the scalability challenge. Additionally, constructive feedback provides guidance towards this trajectory, highlighting the importance of aligning with existing communities and standards, broadening future research scope to consider further scenarios and prioritisation of efforts to build trust around contracts and data quality.

The novelty of the work is the provision of the reusable LCC reference architecture development methodology.

The concept has the potential to provide LCC capabilities to industry at scale while the artefacts developed herein can be appended to existing LCC standards as implementation guidance to support IT system developers. Furthermore, the developed methodology can be employed in harmonisation efforts between policy and practice.

This study aims to investigate which configurations of organizational-level and group-level management controls support an identity fit for management accountants in the management accounting profession. It aims to complement recent qualitative management accounting research. This stream just begun to use role and identity theory to investigate role expectations, conflicts and coping strategies of management accountants when they struggle with their work identity.

Based on configuration theory, this study uses a fuzzy-set qualitative comparative analysis to indicate all possible configurations of formal and informal management controls that improve management accountants’ sense of their identity in an organization. The analyses are based on the results of a cross-sectional survey of 277 management accountants from Germany, Austria, Switzerland and Liechtenstein.

The results show that a strong group culture and high psychological safety at the group level are relevant conditions for a high identity fit. Further, the configurations differ regarding the career stages of management accountants.

This study contributes to work identity research of management accountants and to research on formal and informal control configurations as a control package. It is of particular importance for various professions that are affected by role change, as from the findings on management accountants’ identity fit, implications can also be made for other organizational functions that need to engage in identity work.

A limited number of studies have aimed at understanding behavior towards animal welfare. However, there are indications that consumers make an important distinction between land animals and fish. As no studies have attempted to explain the factors that influence consumer behavior towards the welfare of fish, this study aims to explain the behavior using the value–belief–norm (VBN) model. In addition, we extend the model by using empathy as a factor influencing the formation of personal norms. This study argues that by adding empathy to the model, we will improve the ability of the VBN to explain moral behavior.

The study is based on survey data from 416 Norwegian consumers. A structural equation modeling analysis with latent constructs is used to test the hypotheses.

The findings validate the ability of the VBN model to explain consumer intention to buy products containing fish with better welfare. We also showed that empathy and beliefs strongly influence personal norms. The extended VBN model increased the explained variance of personal norm by 11,54%. Consumers with biospheric values are strongly likely to have empathetic feelings towards fish suffering and believe that fish can feel pain. However, consumers with hedonistic values are significantly negatively related to beliefs and empathy.

By understanding the role of empathy, companies can develop marketing strategies that appeal to consumers' values, empathy and beliefs and ultimately encourage them to make purchases that support fish welfare.

Practically, this study explores consumers' beliefs towards fish welfare and identifies consumers who are more likely to purchase products containing fish with better welfare based on their values.

This study uses bibliometric visualization techniques to comprehensively review the intertwined concepts of dark tourism, thana tourism and ghost tourism from 2000 to 2023. The research seeks to clarify the ambiguity and inconsistencies arising from the interchangeable use of these terms and sets forth a roadmap for future research endeavors.

This study meticulously extracts research keywords from 634 scholarly papers in the Scopus database. It undertakes a thorough bibliometric analysis utilizing the visualization of similarities (VOS) viewer and RStudio to map the interconnectedness of these tourism phenomena.

The study identifies and explores contemporary theories such as self-categorization theory, stimulus-organism-response theory, embodiment theory, self-determination theory, socio-cognitive theory, risk perception theory, services theory, dark tourism theory, social and cultural theory, push-pull theory, performance theory, and wound culture theory. The research reveals four primary clusters through keyword co-occurrence and bibliographic coupling analyses: dark tourism insights, dynamics of dark tourism, dark tourism review and dark tourism experiences, illustrating their interrelationships and robustness.

Dark tourism insights can guide ethical practices, ensuring respectful site management and accurate historical representation. Integrating dark tourism into broader destination strategies can diversify offerings, attract niche markets and contribute to preserving historical memory through reflective experiences.

This study's outcomes significantly contribute to tourism literature by enhancing our understanding of the overlapping terminologies associated with dark, thana and ghost tourism. This improved comprehension sheds light on the importance of the research agenda surrounding the concept of dark, thana and ghost tourism.

In this article, the research objective is to empirically investigate the effect of the adoption of the Brazilian instant payment system, Pix, on the local credit market structure and the diversification of the banking system in Brazilian municipalities.

By analyzing the data, in this study, we compile and align data from supervisory and public sources, covering the period from 2019 to 2022 in Brazil. As of 2014, Brazil was comprised of 5568 municipalities distributed across five regions: North (450 municipalities), Northeast (1792), Midwest (467), Southeast (1668) and South (1191), according to the Brazilian Institute of Geography and Statistics (IBGE). Our analysis relies on the volume and quantity of Pix to the outstanding credit operations in Brazil.

This article provides evidence that the widespread adoption of Pix has impacted the financial structure of municipalities. This analysis of banking concentration in the country and municipalities, based on banking relationships, helped us assess whether the adoption of Pix had any correlation with the increase in credit lines. Overall, the results from the statistical tables suggest that the adoption of Pix may be having a positive impact on the local credit market structure.

The originality contribution of the study is to initiate an investigation into the impact of this instant payment system, Pix, on the Brazilian reality. Pix was launched in 2020, amid the COVID-19 pandemic, and had significant numbers, such as over 61% of the adult population having at least one Pix key registered in a little over a year; about 100 million people made at least one payment with Pix; and more than 1.4 billion transactions per month, with 72% between individuals, as presented by the REB 2021.

Text classification is a widely accepted and adopted technique in organizations to mine and analyze unstructured and semi-structured data. With advancement of technological computing, deep learning has become more popular among academicians and professionals to perform mining and analytical operations. In this work, the authors study the research carried out in field of text classification using deep learning techniques to identify gaps and opportunities for doing research.

The authors adopted bibliometric-based approach in conjunction with visualization techniques to uncover new insights and findings. The authors collected data of two decades from Scopus global database to perform this study. The authors discuss business applications of deep learning techniques for text classification.

The study provides overview of various publication sources in field of text classification and deep learning together. The study also presents list of prominent authors and their countries working in this field. The authors also presented list of most cited articles based on citations and country of research. Various visualization techniques such as word cloud, network diagram and thematic map were used to identify collaboration network.

The study performed in this paper helped to understand research gaps that is original contribution to body of literature. To best of the authors' knowledge, in-depth study in the field of text classification and deep learning has not been performed in detail. The study provides high value to scholars and professionals by providing them opportunities of research in this area.