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1 – 10 of 935Faraz Sadeghvaziri and Leila Shafeie
The present study aims to deepen the understanding of the relationship between nostalgic brand positioning, nostalgic brand relationship dimensions and brand love.
Abstract
Purpose
The present study aims to deepen the understanding of the relationship between nostalgic brand positioning, nostalgic brand relationship dimensions and brand love.
Design/methodology/approach
This study is based on the data collected from 401 citizens of Tehran aged over 18 years old. Respondents admitted that they have felt love for at least one Iranian brand in their lives. The data collected from a questionnaire and the hypothesized relationships were analyzed using the partial least squares approach using Smart PLS.
Findings
The results showed that nostalgic brand positioning positively and significantly impacts nostalgic brand relationship dimensions. Also, there was a positive and significant relationship between nostalgic brand relationship dimensions and brand love. Nostalgic brand positioning has a significant effect on brand love through the mediating role of the nostalgic brand relationship.
Originality/value
The major contribution of this research is that, based on the construal level theory and literature review, the authors developed a conceptual model in which nostalgic brand relationship dimensions, i.e. emotional attachment, brand local iconness, and brand authenticity, explain how nostalgic brand positioning results in brand love.
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Ezzeddine Delhoumi and Faten Moussa
The purpose of this chapter is to cover banking efficiency using the concept of the Meta frontier function and to study group and subgroup differences in the production…
Abstract
The purpose of this chapter is to cover banking efficiency using the concept of the Meta frontier function and to study group and subgroup differences in the production technology. This study estimates the technical efficiency (TE) and technology gap ratios (TGRs) for banks in Islamic countries. Using the assumption of the convex hull of the Meta frontier production set using the virtual Meta frontier within the nonparametric approach as presented by Battese and Rao (2002), Battese et al. (2004), and O'Donnell et al. (2007, 2008) and after relaxing this assumption, the study investigates if there is a significant difference between these two methods. To overcome the deterministic criterion addressed to nonparametric approach, the bootstrapping technique has been applied. The first part of this chapter covers the analytical framework necessary for the definition of a Meta frontier function and its estimation using nonparametric data envelopment analysis (DEA) in the case where we impose the assumption of the convex production set and follows in the case of relaxation of this assumption. Then we estimated the TE and the TGR in concave and nonconcave Meta frontier cases by applying the Bootstrap-DEA approach. The empirical part will be reserved for highlighting these methods on data bank to study the technical and technological performance level and prove if there is a difference between the two methods. Three groups of banks namely commercial, investment, and Islamic banks in 17 Islamic countries over a period of 16 years between 1996 and 2011 are used.
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The study based on the estimation of the stress–strength reliability parameter plays a vital role in showing system efficiency. In this paper, considering independent strength and…
Abstract
Purpose
The study based on the estimation of the stress–strength reliability parameter plays a vital role in showing system efficiency. In this paper, considering independent strength and stress random variables distributed as inverted exponentiated Rayleigh model, the author have developed estimation procedures for the stress–strength reliability parameter R = P(X>Y) under Type II hybrid censored samples.
Design/methodology/approach
The maximum likelihood and Bayesian estimates of R based on Type II hybrid censored samples are evaluated. Because there is no closed form for the Bayes estimate, the author use the Metropolis–Hastings algorithm to obtain approximate Bayes estimate of the reliability parameter. Furthermore, the author construct the asymptotic confidence interval, bootstrap confidence interval and highest posterior density (HPD) credible interval for R. The Monte Carlo simulation study has been conducted to compare the performance of various proposed point and interval estimators. Finally, the validity of the stress–strength reliability model is demonstrated via a practical case.
Findings
The performance of various point and interval estimators is compared via the simulation study. Among all proposed estimators, Bayes estimators using MHG algorithm show minimum MSE for all considered censoring schemes. Furthermore, the real data analysis indicates that the splashing diameter decreases with the increase of MPa under different hybrid censored samples.
Originality/value
The frequentist and Bayesian methods are developed to estimate the associated parameters of the reliability model under the hybrid censored inverted exponentiated Rayleigh distribution. The application of the proposed stress–strength reliability model will help the reliability engineers and also other scientists to estimate the system reliability.
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Christian Nnaemeka Egwim, Hafiz Alaka, Youlu Pan, Habeeb Balogun, Saheed Ajayi, Abdul Hye and Oluwapelumi Oluwaseun Egunjobi
The study aims to develop a multilayer high-effective ensemble of ensembles predictive model (stacking ensemble) using several hyperparameter optimized ensemble machine learning…
Abstract
Purpose
The study aims to develop a multilayer high-effective ensemble of ensembles predictive model (stacking ensemble) using several hyperparameter optimized ensemble machine learning (ML) methods (bagging and boosting ensembles) trained with high-volume data points retrieved from Internet of Things (IoT) emission sensors, time-corresponding meteorology and traffic data.
Design/methodology/approach
For a start, the study experimented big data hypothesis theory by developing sample ensemble predictive models on different data sample sizes and compared their results. Second, it developed a standalone model and several bagging and boosting ensemble models and compared their results. Finally, it used the best performing bagging and boosting predictive models as input estimators to develop a novel multilayer high-effective stacking ensemble predictive model.
Findings
Results proved data size to be one of the main determinants to ensemble ML predictive power. Second, it proved that, as compared to using a single algorithm, the cumulative result from ensemble ML algorithms is usually always better in terms of predicted accuracy. Finally, it proved stacking ensemble to be a better model for predicting PM2.5 concentration level than bagging and boosting ensemble models.
Research limitations/implications
A limitation of this study is the trade-off between performance of this novel model and the computational time required to train it. Whether this gap can be closed remains an open research question. As a result, future research should attempt to close this gap. Also, future studies can integrate this novel model to a personal air quality messaging system to inform public of pollution levels and improve public access to air quality forecast.
Practical implications
The outcome of this study will aid the public to proactively identify highly polluted areas thus potentially reducing pollution-associated/ triggered COVID-19 (and other lung diseases) deaths/ complications/ transmission by encouraging avoidance behavior and support informed decision to lock down by government bodies when integrated into an air pollution monitoring system
Originality/value
This study fills a gap in literature by providing a justification for selecting appropriate ensemble ML algorithms for PM2.5 concentration level predictive modeling. Second, it contributes to the big data hypothesis theory, which suggests that data size is one of the most important factors of ML predictive capability. Third, it supports the premise that when using ensemble ML algorithms, the cumulative output is usually always better in terms of predicted accuracy than using a single algorithm. Finally developing a novel multilayer high-performant hyperparameter optimized ensemble of ensembles predictive model that can accurately predict PM2.5 concentration levels with improved model interpretability and enhanced generalizability, as well as the provision of a novel databank of historic pollution data from IoT emission sensors that can be purchased for research, consultancy and policymaking.
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Vipin Valiyattoor and Anup Kumar Bhandari
A brief review of earlier studies on the productivity scenario of Indian industry shows that most of the studies analysed are confined to either parametric approach or growth…
Abstract
Purpose
A brief review of earlier studies on the productivity scenario of Indian industry shows that most of the studies analysed are confined to either parametric approach or growth accounting approach of measuring productivity. At the same time, the few studies based on the non-parametric [namely, Malmquist productivity index (MPI)] overlook the returns to scale conditions as well as the bias involved in the estimation of distance functions. Given this backdrop, this study aims to provide a robust measure of productivity, which considers the returns to scale assumptions and correct for the bias involved in the estimation of productivity.
Design/methodology/approach
This study empirically tests for the returns to scale that exists in the chemical and chemical products industry in India. The test result suggests that Ray and Desli (1997) approach of MPI is the appropriate one for the present context. Initially, the conventional Ray and Desli (1997) estimation and decomposition of MPI for the period 2001 to 2017 is being used. Subsequently, to correct for the bias in the estimation of efficiency scores used for the estimation of MPI, the bootstrapping algorithm of Simar and Wilson (2007) has been extended into the context of MPI estimation.
Findings
The results from the conventional Malmquist productivity estimates testifies to an improvement of total factor productivity (TFP) in seven out of 16 years under consideration. On the contrary, TFP growth is recorded only in the four years throughout the period after the bias correction. A greater discrepancy between the two measures has been found in the case of scale change factor component of MPI.
Practical implications
The technical change (TC) component positively influences TFP, whereas scale change factor (SCF) deteriorates the TFP condition of this industry. It will be appropriate for these firms to identify and operate under an optimal scale of operation, along with reaping the benefits of technological change. From a methodological perspective, researchers should consider the potential bias that arise in estimation of TFP and use a larger sample whenever possible.
Originality/value
This paper brings in a new perspective to the existing literature on industrial productivity. As against earlier studies, this study empirically tests the returns to scale of the sector under consideration and uses the most appropriate approach to measure productivity. The effect of sampling bias on TFP and its components is analysed.
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Olufemi Adewale Aluko, Muazu Ibrahim and Xuan Vinh Vo
In this study, the authors examine how economic freedom mediates the impact of foreign direct investment (FDI) on economic growth in Africa.
Abstract
Purpose
In this study, the authors examine how economic freedom mediates the impact of foreign direct investment (FDI) on economic growth in Africa.
Design/methodology/approach
By using data from 41 countries over the period 2000–2017, the authors invoke Seo and Shin's (2016) sample splitting approach while relying on the recently developed Seo et al.'s (2019) computationally robust bootstrap algorithm to achieve the purpose of this study.
Findings
The authors find evidence of economic freedom threshold that bifurcates the link between FDI and economic growth in Africa. More precisely, FDI does not improve overall economic growth for African countries whose economic freedom index is below the estimated threshold while significantly spurring growth for African countries with economic freedom above this threshold.
Practical implications
African countries need to strive towards improving their level of economic freedom through the strengthening of rule of law, reducing government size, promoting regulatory efficiency and further opening of the goods and capital markets.
Originality/value
The association between FDI and economic growth has been well documented. While the positive theoretical postulations are almost conclusive, empirical literature on the precise effect of FDI remains contentious and far from being settled. What is missing in the existing literature in Africa is whether countries' level of economic freedom mediates how FDI explains the variations in economic growth across African countries. The authors fill this research gap.
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Emir Malikov, Shunan Zhao and Jingfang Zhang
There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework…
Abstract
There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.
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Siqi Wang, Jun-Hwa Cheah, Chee Yew Wong and T. Ramayah
This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).
Abstract
Purpose
This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).
Design/methodology/approach
Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.
Findings
LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.
Originality/value
This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.
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Javier Hidalgo, Heejun Lee, Jungyoon Lee and Myung Hwan Seo
The authors derive a risk lower bound in estimating the threshold parameter without knowing whether the threshold regression model is continuous or not. The bound goes to zero as…
Abstract
The authors derive a risk lower bound in estimating the threshold parameter without knowing whether the threshold regression model is continuous or not. The bound goes to zero as the sample size n grows only at the cube-root rate. Motivated by this finding, the authors develop a continuity test for the threshold regression model and a bootstrap to compute its p-values. The validity of the bootstrap is established, and its finite-sample property is explored through Monte Carlo simulations.
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Sayeda Zeenat Maryam and Ashfaq Ahmad
In the current era of technological advancement, it is becoming essential for financial institutions to serve through financial technology (Fintech). This study aims to integrate…
Abstract
Purpose
In the current era of technological advancement, it is becoming essential for financial institutions to serve through financial technology (Fintech). This study aims to integrate Fintech with value chain in existing system of Islamic financial institutions (IFIs) and to determine the adoption of Fintech value chain financing (FVCF) by IFIs in the presence of mediators.
Design/methodology/approach
This paper examines a conceptual model by performing a self-administration survey for 393 sample size. After the completion of data collection 263 suitable responses are used for analysis. The hypotheses are tested by applying algorithm, bootstrapping and blindfolding techniques.
Findings
The findings of structural model demonstrate that trust, information sharing (IS) and information and communication technology (ICT) are important for adoption of FVCF in the perspective of IFIs. Secondly, innovativeness is partially mediating the relationship of trust, IS and ICT for adoption of FVCF. Thirdly, competitiveness is fully mediating the relationship of trust, IS and ICT with agility for adoption of FVCF by IFIs.
Research limitations/implications
Theoretically, this research is developing a conceptual model that is providing a new way to integrate value chain partners. This study is demonstrating the sequential mediation for the adoption of FVCF. Practically, this research is giving meaningful insight to policymakers of IFIs by suggesting a way forward to adopt FVCF. However, there is need to know the perception of other stakeholders that may involve in FVCF.
Originality/value
Because there exists limited work in the context of integration and adoption of Fintech by organizations, this study is a pioneer that is taking the perspective of financial institutions for FVCF.
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