Search results

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

This paper employs bibliometric analysis to explore transformative trends and emerging research patterns in the intersection of digital technology and tourism. The goal is to provide insights into the evolving landscape, identify key themes, influential authors and prominent journals, contributing to a nuanced understanding of this dynamic field.

This study rigorously employs bibliometric analysis from 2002 to 2023, using Scopus and Web of Science databases, yielding 2,040 Scopus and 1,389 Web of Science documents. After meticulous data selection, 575 articles were refined. Utilising VOSviewer and Biblioshiny, the analyses focus on publication trends, citations, authorship, collaborations and thematic clusters, addressing four research questions.

This bibliometric analysis reveals a significant growth in annual scientific production on digital technology and tourism, peaking at 100 articles in 2023. Key contributors include LAW R., CHUNG N. and KOO C. China leads in research output, and influential journals include “Current Issues in Tourism” and “Information Technology and Tourism.” Noteworthy trends emphasise the centrality of “smart tourism” and the interconnectedness of technology, hospitality and management in shaping future research directions.

Stakeholders should focus on integrating emerging technologies in tourism, emphasising areas with high research activity. Professionals must stay updated on evolving trends, adopt innovative digital solutions and collaborate to navigate the dynamic landscape.

This study pioneers the first bibliometric analysis on digital technology in the tourism industry, providing a unique and comprehensive exploration of the scholarly landscape from 1998 to 2023, shedding light on key contributors, influential journals and emerging trends.

The blue and green firms are notable contributors to sustainable development. Similar to other businesses in circular economies, blue and green firms also face financing constraints. This paper aims to assess whether blue and green lending help in optimizing the interest rate spreads and the likelihood of default.

This analysis is based on an unbalanced panel of banks from 20 eurozone countries for eleven years between 2012 and 2022. The key indicators of banking include interest rate spread and a market-based probability of default. The paper assesses how these indicators are influenced by exposure to green and blue firms after controlling for several exogenous factors.

The results show a positive relationship between green and blue lending and spread, while there is a negative link with the probability of default. This confirms that the blue and green exposure positively supports the credit portfolio both in terms of profitability and risk management.

The banking system is among the key contributors to corporate finance and to enable continuous access to sustainable finance, the banking firms must be incentivized. While many studies analyze the impact of green lending, to the best of the authors’ knowledge, this study is among the very few that extend this analysis to blue economy firms.

Women’s empowerment remains a key development challenge in Kenya. The purpose of this study is to attempt to understand the status of women’s empowerment and the key contributors to their disempowerment in Kenya’s aquaculture sector.

A cross-sectional survey was conducted on 534 male and female fish farmers from 300 households drawn from six counties in Kenya (Kakamega, Kisumu, Kisii, Kiambu, Meru and Nyeri). The Abbreviated Women’s Empowerment in Agriculture Index (A-WEAI) was adapted to Abbreviated Women’s Empowerment in Fisheries and Aquaculture Index (A-WEFI) to suit the aquaculture and fisheries sub-sector. The adapted A-WEFI was then used to estimate and the status of women’s and men’s using five domains of empowerment (5DE) and a gender parity index (GPI). Data were analysed using descriptive statistics, Cramer’s V and sensitivity analysis as test statistics.

About 86% of the men and 80% of the women were classified as empowered. The mean score of the 5DE was 0.93 and 0.95 for women and men, respectively. In addition, 82% of the households achieved gender parity, suggesting that for such households, empowerment of men was no greater than that of women. Overall, the results suggest no major differences between the empowerment of women and men. Findings suggest areas of improvement in empowerment: when observed separately, women report lack of agency in production, resource, time-use and allocation and leadership.

This paper adapts the A-WEAI to the fisheries and aquaculture context, in bid to bridge the gap in standard women’s empowerment measurement methods in this area. Also, there are limited empirical studies on the multifaceted empowerment of women in aquaculture in Kenya. The findings are meant to serve as a point of reference for policymakers, as they develop gender-responsive intervention programmes, and in implementing gender mainstreaming in Kenya.

Career burnout is prevalent in the PR industry, precisely when demand for professionals is increasing. While career burnout has been included in studies and theorising on professionalism and feminisation, issues with turnover and burnout remain.

Using a grounded theory approach, this qualitative study draws upon the lived experiences of 30 current and former female Australian PR professionals to gain an understanding of how they perceive signs of career burnout and the factors that contribute to it.

Career burnout is an occupational syndrome whereby someone gradually morphs from being highly motivated in their role to emotionally exhausted, cynical and/or experiencing feelings of failure. It is a protracted response to chronic workplace demands and stressors, and includes three dimensions: emotional exhaustion, depersonalisation and reduced personal accomplishment. It is specifically a workplace phenomenon, distinguished from anxiety and depression, which can emerge in any context.

A key contributor to career burnout were PR-specific workplace stressors that were perceived to stem from a lack of respect for, or understanding of, PR as a profession. The stressors included the need to‘prove the spend’of PR, unreasonable deadlines, clients disregarding advice or counsel, as well as broader societal perceptions of PR as ‘spin doctors’. This often led to the PR practitioner undertaking work that went against their own advice or resulted in unsuccessful organisational outcomes they felt could have been avoided had their advice been listened to and valued. The workplace factors contributing to burnout overlap in complex ways and the study supports the idea that burnout is a product of situational contexts, despite being acutely felt at the individual level.

With the emergence of big data analytics and the importance of analytics-driven decisions, the travel industry is swiftly jumping on and adopting the bandwagon. However, research in this domain is limited. Accordingly, the present research seeks to understand how big data analytics capabilities (BDAC) add value to tourism supply chains (TSCs) and can dynamic capabilities (DC) improve the triple bottom line.

Data from 218 valid responses were collected from different Indian tourism industry units. Confirmatory factor analysis (CFA) was applied to confirm the constructs, followed by partial least squares structural equation modelling (PLS-SEM) to check the mediating effect of DC on TSCs performance.

The findings show that BDAC significantly influence the performance of TSCs and that DC plays a critical role in strengthening the impact of BDAC on TSCs' economic performance. These results corroborate that DC plays a key moderating role.

This study contributes significantly to the tourism sector in India, where tourism is a key contributor to the country's gross domestic product. Theoretically, this study contributes to the resource-based view (RBV) and practically encourages professionals in the tourism sector to promote the use of BDAC to enhance the performance of TSCs.

The originality of the study is that it has tried to comprehend the moderating role of dynamic capabilities which impact BDAC to improve TSC performance.

The shift toward a circular economy (CE) represents a collaborative endeavor necessitating the presence of efficient frameworks, conducive contexts and a common comprehension. This research serves as a pivotal stride towards this goal, presenting an exclusive prospect for the investigation and fusion of these frameworks, with particular emphasis on the Quintuple Helix Model (5HM), into a unified theoretical framework that underscores the core principles of the CE. This study is centered on three pivotal questions aimed at decoding the CE transition in specific regional settings.

Adopting an abductive approach firmly anchored in a two-stage qualitative process, this study specifically merges the foundational principles from institutional theory, entrepreneurship literature and CE frameworks to provide insights into the dynamics of circular ecosystems, with a specific focus on the Huelva region in Spain.

The findings demonstrate significant potential in the CE, ranging from the integration of product and service systems to innovations in eco-industrial practices. Yet, a notable deficiency exists: the absence of institutional entrepreneurs, highlighting the essential role that universities can play. As recognized centers of innovation, universities are suggested to be key contributors to the transformation toward a CE, aligning with their societal and economic responsibilities.

This study highlights the importance of managing relationships with entities like SMEs and policymakers or academia for effective CE adoption. Policymakers can refine strategies based on the research’s insights, while the impact of university-driven circular ecosystems on sustainable societies is another crucial area for research.

The sustainability models cited in CE literature may not be comprehensive enough to prevent problem shifting, and it can be argued that they lack a sound theoretical and conceptual basis. Furthermore, the connections between sustainability objectives and the three levels of the CE operating system remain vague. Additionally, there is insufficient information on how regions foster the involvement of the environment in fivefold helix cooperation and how this impacts the CE.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

Fuzzy-set qualitative comparative analysis (fsQCA) is explored as a transformative tool rooted in complexity theory, shedding light on uncertainties shaping real-world decisions in tourism, with a focus on its application in the hospitality domain.

This study systematically evaluates fsQCA’s application in hospitality and tourism research, employing bibliometric analysis to scrutinize the published literature since its induction in 2011. The research seeks to understand the evolving usage by qualitatively reviewing impactful studies based on total citations.

The study reveals the ascendancy of fsQCA as a predominant approach in hospitality and tourism studies, particularly in illuminating decision-making paradigms in key sectors like destination and hotel selections and entrepreneurial orientations. However, an absence of fsQCA applications in gastronomy and wine tourism is identified, signaling uncharted territories for future inquiry.

Theoretical implications include paradigm shifts to complexity theory, configural analysis and asymmetric algorithms. Practical implications involve improved decision-making and tailored marketing, benefiting industry practitioners. Limitations include potential academic bias, while future research suggests exploring sub-sectors, sustainability and emerging technologies.

This study identifies gaps in the fsQCA application and pioneers its examination within the hospitality domain, offering a unique perspective on understanding intricate relationships and configurations among variables. The study emphasizes the efficacy of asymmetric methodologies in elucidating behavioral nuances in hospitality and tourism, providing a foundation for future inquiries to expand horizons and unravel the nuanced applications of fsQCA in this research domain.

Food waste in the hospitality sector has emerged as a global concern. Various technology-driven online food services such as the food delivery apps (FDA) contribute to hospitality food waste. FDA users might behave irresponsibly by ordering more foods than required which may lead to food waste generation. To date, limited studies have been attempted to understand how consumers’ over-ordering behavior through FDA result in hospitality food waste.

The authors used partial least squares structural equation modeling (PLS-SEM) to analyze survey data from 248 FDA users.

The results indicated that perceived convenience and trust positively influence consumers' attitude toward FDA, which in turn promotes over-ordering behavior. Interestingly, the anticipated positive relationship between price advantage and attitude toward FDA was not supported by the data. Furthermore, the authors confirmed that over-ordering behavior contributes to food waste, an outcome that has crucial implications for both the hospitality sector and sustainability efforts.

The current study employs the stimulus-organism-behavior-consequence (SOBC) theory to investigate the catalysts and consequences of over-ordering behavior via FDA. This study thus highlights the importance of the SOBC model in understanding consumer behavior.