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1 – 10 of 140This study aims to explore the relationship between promoter share pledging and the company’s dividend payout policy in India. Furthermore, this study also analyses the moderating…
Abstract
Purpose
This study aims to explore the relationship between promoter share pledging and the company’s dividend payout policy in India. Furthermore, this study also analyses the moderating impact of family involvement in business on the association between share pledging and dividend payout.
Design/methodology/approach
A sample of 236 companies from the S&P Bombay Stock Exchange Sensitive (BSE) 500 Index (2014–2023) has been analysed through fixed-effects panel data regression. For additional testing, robustness checks include alternative measures of dividend payout and promoter share pledging, as well as alternative methodologies such as Bayesian regression. Lastly, to address potential endogeneity, instrumental variables with a two-stage least squares (IV-2SLS) methodology have been implemented.
Findings
Upholding the agency perspective, a significantly negative impact of promoter share pledging on corporate dividend payouts in India has been uncovered. Moreover, family involvement in business moderates this relationship, highlighting that the negative association between promoter share pledging and dividend payouts is more pronounced in family companies. The findings are consistent throughout the robustness testing.
Originality/value
The present study represents a pioneering endeavour to empirically analyse the link between promoter share pledging and dividend payouts in India. It enhances the theoretical underpinnings of the agency relationship, particularly by substantiating the existence of Type II agency conflicts between majority and minority shareholders. The findings of this research bear significant implications for investors, researchers and policymakers, particularly in light of the widespread prevalence of promoter-controlled entities in India.
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Ataul Karim Patwary, Muharis Mohamed, Md Karim Rabiul, Waqas Mehmood, Muhammad Umair Ashraf and Adamu Abbas Adamu
This study aims to examine the effects of green marketing tools on tourists’ behavioural intention to buy green products by measuring individuals’ subjective norms, attitudes and…
Abstract
Purpose
This study aims to examine the effects of green marketing tools on tourists’ behavioural intention to buy green products by measuring individuals’ subjective norms, attitudes and perceived behavioural control.
Design/methodology/approach
A total of 421 international tourists from several tourist attractions in Malaysia, selected through convenience sampling, participated in a survey.
Findings
The analysis results using partial least squares structural equation modelling suggest that behavioural intention of international tourists is firmly influenced by attitude, perceived behavioural control, subjective norms and green marketing tools. However, the subjective norm does not work as a mediator.
Practical implications
The relationships established in this study provide insight into hoteliers’ knowledge for further implementation of green marketing strategies (eco-label, eco-brand, environmental advertising), which can enhance green attitudes and behavioural intention of purchasing green products in the hospitality industry.
Originality/value
This study expands the theory of planned behaviour by including green marketing tools to measure international tourists’ green buying tendency in Malaysia.
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Although previous studies have examined the influence of celebrity involvement in behavioural intentions, the role of celebrity dimensions such as attraction, self-expression and…
Abstract
Purpose
Although previous studies have examined the influence of celebrity involvement in behavioural intentions, the role of celebrity dimensions such as attraction, self-expression and centrality in influencing tourists’ intention in the context of developing countries such as Tanzania remains largely unaddressed. This study, therefore, examined the relationship between celebrity involvement and domestic tourists' intentions to visit tourist attractions, attitude being the mediating variable.
Design/methodology/approach
A questionnaire was self-administered on a convenient sample of 279 domestic tourists in the Tanzania’s four largest regions, namely, Dar es Salaam, Mbeya, Arusha and Mwanza. Employing a quantitative research approach, structural equation modelling was performed to test the cause-and-effect relationships between celebrity involvement and tourists’ intentions before testing the mediating role of attitude in such a relationship. Confirmatory factor analysis was also performed to test the measurement models.
Findings
Attraction emerged to be the main determinant of the celebrity dimension that significantly influenced domestic tourists’ travel intentions, whereas attitude partially mediates such a relationship. Moreover, Bongo Fleva musicians, particularly Diamond Platnumz, one of the leading celebrities in this genre, were found to influence most of the respondents’ travel intentions – he posted a picture on his Instagram account of him touring the Serengeti National Park.
Research limitations/implications
The study focused on domestic tourists residing in four of the Mainland Tanzania’s largest regions, hence excluding those residing on the islands of Unguja and Pemba. Due to cultural differences, including the islands not only could unleash new perspectives on celebrity involvement dimensions but also could have introduced new determinants of travel intentions.
Practical implications
This study offers guidance to tourism businesses on designing their marketing campaigns that they should harness celebrity’s attractive qualities effectively. The focus should be directed not only towards linking destinations with celebrities but also on stimulating positive perception of those destinations, aligning with the attitudes of their followers.
Social implications
The study has set out a new perspective for researchers, practitioners and tourism businesses to refine their promotional strategies and for academicians to gain a deeper understanding of visitor behavioural intention dynamics.
Originality/value
This study has proposed and verified that attraction is a dominant determinant compared to self-expression and centrality in explaining tourists’ travel intentions and attitudes, which play a significant role in explaining such a relationship. Although the study employed a modified theory of planned behaviour in a celebrity involvement study, the findings have broadened the understanding and its applicability in the context of a developing country.
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Habeeb Balogun, Hafiz Alaka and Christian Nnaemeka Egwim
This paper seeks to assess the performance levels of BA-GS-LSSVM compared to popular standalone algorithms used to build NO2 prediction models. The purpose of this paper is to…
Abstract
Purpose
This paper seeks to assess the performance levels of BA-GS-LSSVM compared to popular standalone algorithms used to build NO2 prediction models. The purpose of this paper is to pre-process a relatively large data of NO2 from Internet of Thing (IoT) sensors with time-corresponding weather and traffic data and to use the data to develop NO2 prediction models using BA-GS-LSSVM and popular standalone algorithms to allow for a fair comparison.
Design/methodology/approach
This research installed and used data from 14 IoT emission sensors to develop machine learning predictive models for NO2 pollution concentration. The authors used big data analytics infrastructure to retrieve the large volume of data collected in tens of seconds for over 5 months. Weather data from the UK meteorology department and traffic data from the department for transport were collected and merged for the corresponding time and location where the pollution sensors exist.
Findings
The results show that the hybrid BA-GS-LSSVM outperforms all other standalone machine learning predictive Model for NO2 pollution.
Practical implications
This paper's hybrid model provides a basis for giving an informed decision on the NO2 pollutant avoidance system.
Originality/value
This research installed and used data from 14 IoT emission sensors to develop machine learning predictive models for NO2 pollution concentration.
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Femi Monday Ilevbare, Oluwatosin Eniola Ilevbare, Caleb Muyiwa Adelowo and Favour P. Oshorenua
This paper aims to examine the determinants of entrepreneurial intention among students of a university in Nigeria, with particular emphasis on their risk-taking propensity…
Abstract
Purpose
This paper aims to examine the determinants of entrepreneurial intention among students of a university in Nigeria, with particular emphasis on their risk-taking propensity, social support and demographic variables.
Design/methodology/approach
Data for the study were collected from 350 undergraduates across seven faculties in Obafemi Awolowo University, Nigeria, through a self-reported questionnaire. Descriptive and regression statistical analysis were used to estimate and test the relationship among entrepreneurial intention and social support, risk-taking propensity and demographic variables.
Findings
The results showed high entrepreneurial intention among the students. The push factors, such as perceived social support from families, risk-taking propensity and previous engagement in business, are key determinants of entrepreneurship intention among the students. The age and father’s occupation also showed a significant relationship with the level of entrepreneurial intention.
Practical implications
This result suggests that strengthening social support for entrepreneurship among students could enhance their desire to own a business during and after graduation. Improving entrepreneurship ecosystems in the university could further motivate those already practicing entrepreneurship while also stimulating intentions among others. For instance, provision of entrepreneurship infrastructure and incentives such as business incubators, innovation hubs, science parks and competitive business grants could enhance the risk-taking propensity among students and motivate them for venture creation.
Originality/value
Understanding the influence of social support and risk-taking propensity on entrepreneurial intention among undergraduates is important for policy and practice. The result further reinforces the need to promote entrepreneurship education to create a critical mass of potential entrepreneurs in the university.
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Siti Hajar Hussein, Suhal Kusairi and Fathilah Ismail
This study aims to develop an educational tourism demand model, particularly in respect to dynamic effects, university quality (QU) and competitor countries. Educational tourism…
Abstract
Purpose
This study aims to develop an educational tourism demand model, particularly in respect to dynamic effects, university quality (QU) and competitor countries. Educational tourism has been identified as a new tourism sub-sector with high potential, and is thus expected to boost economic growth and sustainability.
Design/methodology/approach
This study reviews the literature on the determinants of educational tourism demand. Even though the existing literature is intensively discussed, mostly focusing on the educational tourism demand from an individual consumer's perspective, this study makes an innovation in line with the aggregate demand view. The study uses data that consist of the enrolment of international students from 47 home countries who studied in Malaysia from 2008 to 2017. The study utilised the dynamic panel method of analysis.
Findings
This study affirms that income per capita, educational tourism price, price of competitor countries and quality of universities based on accredited programmes and world university ranking are the determinants of educational tourism demand in both the short and the long term. Also, a dynamic effect exists in educational tourism demand.
Research limitations/implications
The results imply that government should take the quality of services for existing students, price decisions and QU into account to promote the country as a tertiary education hub and achieve sustainable development.
Originality/value
Research on the determinants of the demand for educational tourism is rare in terms of macro data, and this study includes the roles of QU, competitor countries and dynamic effects.
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Fatimah Zulkifli, Rosfariza Radzali, Alhan Farhanah Abd Rahim, Ainorkhilah Mahmood, Nurul Syuhadah Mohd Razali and Aslina Abu Bakar
Porous silicon (Si) was fabricated by using three different wet etching methods, namely, direct current photo-assisted electrochemical (DCPEC), alternating CPEC (ACPEC) and…
Abstract
Purpose
Porous silicon (Si) was fabricated by using three different wet etching methods, namely, direct current photo-assisted electrochemical (DCPEC), alternating CPEC (ACPEC) and two-step ACPEC etching. This study aims to investigate the structural properties of porous structures formed by using these etching methods and to identify which etching method works best.
Design/methodology/approach
Si n(100) was used to fabricate porous Si using three different etching methods (DCPEC, ACPEC and two-step ACPEC). All the samples were etched with the same current density and etching duration. The samples were etched by using hydrofluoric acid-based electrolytes under the illumination of an incandescent lamp.
Findings
Field emission scanning electron microscopy (FESEM) images showed that porous Si etched using the two-step ACPEC method has a higher porosity and density than porous Si etched using DCPEC and ACPEC. The atomic force microscopy results supported the FESEM results showing that porous Si etched using the two-step ACPEC method has the highest surface roughness relative to the samples produced using the other two methods. High resolution X-ray diffraction revealed that porous Si produced through two-step ACPEC has the highest peak intensity out of the three porous Si samples suggesting an improvement in pore uniformity with a better crystalline quality.
Originality/value
Two-step ACPEC method is a fairly new etching method and many of its fundamental properties are yet to be established. This work presents a comparison of the effect of these three different etching methods on the structural properties of Si. The results obtained indicated that the two-step ACPEC method produced an etched sample with a higher porosity, pore density, surface roughness, improvement in uniformity of pores and better crystalline quality than the other etching methods.
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Kyle C. McDermott, Ryan D. Winz, Thom J. Hodgson, Michael G. Kay, Russell E. King and Brandon M. McConnell
The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand…
Abstract
Purpose
The study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.
Design/methodology/approach
This work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.
Findings
This research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.
Research limitations/implications
This research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.
Originality/value
This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.
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Rexford Abaidoo and Elvis Kwame Agyapong
The study examines the effect of macroeconomic risk, inflation uncertainty and instability associated with key macroeconomic indicators on the efficiency of financial institutions…
Abstract
Purpose
The study examines the effect of macroeconomic risk, inflation uncertainty and instability associated with key macroeconomic indicators on the efficiency of financial institutions among economies in sub-Saharan Africa (SSA).
Design/methodology/approach
Data for the empirical inquiry were compiled from 35 SSA economies from 1996 to 2019. The empirical estimates were carried out using pooled ordinary least squares (POLS) with Driscoll and Kraay’s (1998) standard errors.
Findings
Reported empirical estimates show that macroeconomic risk and exchange rate volatility constrain the efficiency of financial institutions. Further results suggest that inflation uncertainty has a significant influence on the efficiency of financial institutions among economies in the subregion. Additionally, reviewed empirical estimates show that institutional quality positively moderates the nexus between inflation uncertainty and financial institution efficiency. At the same time, political instability is found to worsen the adverse effect of macroeconomic risk on the efficiency of financial institutions.
Practical implications
For policymakers and governments, improved institutional structures are recommended to ensure the operational efficiency of financial institutions, especially during an inflationary period. For decision-makers among financial institutions, the study recommends policies that have the potential to make their institutions less vulnerable to macroeconomic risk and exchange rate fluctuations.
Originality/value
The approach adopted in this study differs significantly from related studies in that the study examines and reviews interactions and relationships not readily found in the reviewed literature.
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Slawomir Koziel and Anna Pietrenko-Dabrowska
This study aims to propose a computationally efficient framework for multi-objective optimization (MO) of antennas involving nested kriging modeling technology. The technique is…
Abstract
Purpose
This study aims to propose a computationally efficient framework for multi-objective optimization (MO) of antennas involving nested kriging modeling technology. The technique is demonstrated through a two-objective optimization of a planar Yagi antenna and three-objective design of a compact wideband antenna.
Design/methodology/approach
The keystone of the proposed approach is the usage of recently introduced nested kriging modeling for identifying the design space region containing the Pareto front and constructing fast surrogate model for the MO algorithm. Surrogate-assisted design refinement is applied to improve the accuracy of Pareto set determination. Consequently, the Pareto set is obtained cost-efficiently, even though the optimization process uses solely high-fidelity electromagnetic (EM) analysis.
Findings
The optimization cost is dramatically reduced for the proposed framework as compared to other state-of-the-art frameworks. The initial Pareto set is identified more precisely (its span is wider and of better quality), which is a result of a considerably smaller domain of the nested kriging model and better predictive power of the surrogate.
Research limitations/implications
The proposed technique can be generalized to accommodate low- and high-fidelity EM simulations in a straightforward manner. The future work will incorporate variable-fidelity simulations to further reduce the cost of the training data acquisition.
Originality/value
The fast MO optimization procedure with the use of the nested kriging modeling technology for approximation of the Pareto set has been proposed and its superiority over state-of-the-art surrogate-assisted procedures has been proved. To the best of the authors’ knowledge, this approach to multi-objective antenna optimization is novel and enables obtaining optimal designs cost-effectively even in relatively high-dimensional spaces (considering typical antenna design setups) within wide parameter ranges.
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