Md. Wasiul Islam, Md. Mahfuz Ur Rahman and Shakil Ahmed
Visits to locations connected to historical atrocities, tragedy, suffering, or presumably dreadful events are referred to as “dark tourism”. While Bangladesh may not be widely…
Abstract
Visits to locations connected to historical atrocities, tragedy, suffering, or presumably dreadful events are referred to as “dark tourism”. While Bangladesh may not be widely known for dark tourism, several unexplored avenues may be of interest to those who engage in this type of unique and unconventional tourism experience. In addition to creating job opportunities and income generation in Bangladesh, it can achieve educational objectives, communicate with a broad audience, raise awareness of events of the past, and quench people's thirst for information, which can help them to comprehend a society. Though Bangladesh has several somber locations connected to tragic events including World War II, liberation war sites, mass killing sites, shipbreaking yards, Rohingya refugee camps, riots, and the mother language movement, traditional tourism predominates there. If managed responsibly, these varied resources, somber locations, and histories, some of which date back to 1800, could make Bangladesh a dark tourism destination. Although dark tourism in Bangladesh has the potential to contribute to historical awareness, preservation, educational opportunities, and socioeconomic development, it is yet unexplored due to a lack of knowledge, experience, policy, effective marketing, and some controversies. By approaching responsibly, Bangladesh can leverage its history to attract visitors' interests in exploring the darker aspects of the country's past. Hence, this chapter is designed to explore the status and potential significance, prospects, and challenges of dark tourism in Bangladesh. The findings will help policymakers, tourists, and other stakeholders to explore and enjoy enormous benefits from Bangladesh's untapped dark tourism opportunities.
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Goal 16 of the SDGs concerns ‘Peace, Justice and Strong Institutions’. Specifically, Goal 16 states ‘Promote peaceful and inclusive societies for sustainable development, provide…
Abstract
Goal 16 of the SDGs concerns ‘Peace, Justice and Strong Institutions’. Specifically, Goal 16 states ‘Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels’. Among the targets of this goal (Target 16.5) is to ‘Substantially reduce corruption and bribery in all their forms’. Undoubtedly, the recognition and inclusion of corruption and bribery among other relevant governance aspects is laudable and necessary. This chapter examines and analyses the relationship between corruption and sustainable development, assesses regional performance through the indicators for achieving Target 16.5 of the Sustainable Development Goals and proposes other indicators and policy frameworks for improved performance toward substantially reducing corruption and bribery in all their forms.
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Sathies Kumar Thangarajan and Arun Chokkalingam
The purpose of this paper is to develop an efficient brain tumor detection model using the beneficial concept of hybrid classification using magnetic resonance imaging (MRI…
Abstract
Purpose
The purpose of this paper is to develop an efficient brain tumor detection model using the beneficial concept of hybrid classification using magnetic resonance imaging (MRI) images Brain tumors are the most familiar and destructive disease, resulting to a very short life expectancy in their highest grade. The knowledge and the sudden progression in the area of brain imaging technologies have perpetually ready for an essential role in evaluating and concentrating the novel perceptions of brain anatomy and operations. The system of image processing has prevalent usage in the part of medical science for enhancing the early diagnosis and treatment phases.
Design/methodology/approach
The proposed detection model involves five main phases, namely, image pre-processing, tumor segmentation, feature extraction, third-level discrete wavelet transform (DWT) extraction and detection. Initially, the input MRI image is subjected to pre-processing using different steps called image scaling, entropy-based trilateral filtering and skull stripping. Image scaling is used to resize the image, entropy-based trilateral filtering extends to eradicate the noise from the digital image. Moreover, skull stripping is done by Otsu thresholding. Next to the pre-processing, tumor segmentation is performed by the fuzzy centroid-based region growing algorithm. Once the tumor is segmented from the input MRI image, feature extraction is done, which focuses on the first-order and higher-order statistical measures. In the detection side, a hybrid classifier with the merging of neural network (NN) and convolutional neural network (CNN) is adopted. Here, NN takes the first-order and higher-order statistical measures as input, whereas CNN takes the third level DWT image as input. As an improvement, the number of hidden neurons of both NN and CNN is optimized by a novel meta-heuristic algorithm called Crossover Operated Rooster-based Chicken Swarm Optimization (COR-CSO). The AND operation of outcomes obtained from both optimized NN and CNN categorizes the input image into two classes such as normal and abnormal. Finally, a valuable performance evaluation will prove that the performance of the proposed model is quite good over the entire existing model.
Findings
From the experimental results, the accuracy of the suggested COR-CSO-NN + CNN was seemed to be 18% superior to support vector machine, 11.3% superior to NN, 22.9% superior to deep belief network, 15.6% superior to CNN and 13.4% superior to NN + CNN, 11.3% superior to particle swarm optimization-NN + CNN, 9.2% superior to grey wolf optimization-NN + CNN, 5.3% superior to whale optimization algorithm-NN + CNN and 3.5% superior to CSO-NN + CNN. Finally, it was concluded that the suggested model is superior in detecting brain tumors effectively using MRI images.
Originality/value
This paper adopts the latest optimization algorithm called COR-CSO to detect brain tumors using NN and CNN. This is the first study that uses COR-CSO-based optimization for accurate brain tumor detection.
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Bangladesh is one of the poorest countries in the world. In 1988‐89, 48 per cent of rural and 44 per cent of urban households had a daily per capita consumption of less than 2,122…
Abstract
Bangladesh is one of the poorest countries in the world. In 1988‐89, 48 per cent of rural and 44 per cent of urban households had a daily per capita consumption of less than 2,122 calories ‐ the cut‐off point for absolute poverty in Bangladesh. Although poverty is prevalent amongst men as well as women, far more women suffer from poverty due to their low socio‐economic status. Social customs and religious beliefs play a dominant role in shaping a society’s attitudes towards women. At the household level, their status significantly varies between educated and uneducated, between employed and unemployed, and between rural and urban women. If one excludes the very small numbers of successful women who are educated and/or active in the workforce, most women have an inferior status to that of men. They are economically dependent on men even for the basic necessities of life such as food, shelter, clothing and medicine. They are bound by various social customs made by men and every facet of life including decision making is determined by men. The central purpose of this paper is to examine the issues relating to the poverty of women in Bangladesh: to analyse the dimensions of poverty in Bangladesh; to evaluate the steps taken by various governmental and non‐governmental agencies to alleviate the poverty of women; and to examine the impact of such steps on the changing status of women in Bangladesh.
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Ellen Francine Rodrigues, Luana Paula Vendruscolo, Kimberly Bonfante, Christian Oliveira Reinehr, Eliane Colla and Luciane Maria Colla
The phycocyanin is a pigment present in the microalga Spirulina that has been studied due to its applicability as food coloring; however, it can be used due to the ability to act…
Abstract
Purpose
The phycocyanin is a pigment present in the microalga Spirulina that has been studied due to its applicability as food coloring; however, it can be used due to the ability to act as an emulsifier or stabilizer in function of its protein characteristic. The purpose of this paper is to use aqueous extracts of Spirulina containing phycocyanin (EP) as a substitute of additives in the production of ice creams.
Design/methodology/approach
The study was divided in two sections: first, the influence of addition of EP in ice cream bases (that represent the ice cream preparation before air incorporation step) and second, the influence of addition of EP in five ice cream formulations, in which the differences were the addition of EP in substitution of stabilizer, Chantilly or emulsifier, one at a time or in substitution of all additives together, by the EP.
Findings
The different ice creams developed presented centesimal composition according to Brazilian legislation in relation to the chemical parameters. The EP presented emulsifying and stabilizing activity in the ice creams formulations acting in substitution of emulsifier and stabilizer presented in the standard formulation, not influencing the overall acceptability of consumers.
Originality/value
The authors demonstrate that the aqueous extract of Spirulina containing phycocyanin can be used as a natural additive in ice cream in substitution of emulsifiers and stabilizers normally used in this product, contributing to produce more healthy foods, once phycocyanin is an protein of high nutritional value.
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E. Ianni, I. Ortolan, M. Scimone and E. Feoli
Purpose – The purpose of this paper is to present an application of spatial decision support system tools (SDSS) for assessing management option to reduce the nitrogen load from…
Abstract
Purpose – The purpose of this paper is to present an application of spatial decision support system tools (SDSS) for assessing management option to reduce the nitrogen load from agricultural sources. The SDSS has been developed within a case study for the drainage basin of the Grado and Marano Lagoon (N‐E Italy). Design/methodology/approach – The problem is at least partially solvable replacing some actual cash crops with alternative crops requiring lower nitrogen input but which are economically profitable. The decision support was designed with two components: a non‐spatial one (DSS) to support the choice among alternative crops (within different scenarios), and a spatial one (SDSS) to analyse and evaluate the spatial distribution of the cash crops finding suitable areas for the alternative crops. Findings – The use of alternative crops for reducing nitrogen loads to the Grado and Marano lagoon waters seems feasible and appropriate. A mosaic of poplar, grassland and cash crop areas in these areas of the pollution risk is the best alternative both in terms of total nitrogen reduction and in terms of farmers' income. Research limitations/implications – The paper proposes a SDSS to implement alternative crops in an area where the cash crops constitute a very strong consolidated agricultural system. The feasibility of the alternatives is dependent on the willingness of farmers to participate in the research and then to exploit its results. The availability of data only at municipal level limited the research, thus imposing a spatial resolution constraint. Originality/value – It is so far the first attempt, in Friuli Venezia Giulia region, to develop a spatial decision support system to mitigate the pollution of a lagoon from agricultural sources by trying to find suitable alternatives to well consolidated agricultural practices. It also constitutes a model that can be applied in similar contexts by coupling ecological and economic considerations.
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Farid Ahmed, Felicitas Evangelista and Daniela Spanjaard
Relationship marketing has been playing an important role in the development of marketing theory and practice. Though the concept has been extensively applied in international…
Abstract
Purpose
Relationship marketing has been playing an important role in the development of marketing theory and practice. Though the concept has been extensively applied in international marketing in understanding the dynamics of exporter-importer relationships, few studies have looked at dyadic data to investigate the impact of mutuality of relational variables on the exporter-importer relationships. The objective of this study is to understand the impact of mutuality of key relational variables on exporter-importer relationship performance. A dyadic model of mutuality is proposed. The model highlights the impact of balance, level and quality of perceptual bi-directionality of relational variables.
Design/methodology/approach
The model was tested using dyadic data collected from exporter-importer relationships involving Australian exporters and their Southeast Asian import partners through a cross-sectional, quantitative survey. Mutuality of relationship constructs was measured using the perceptual bi-directionality (PBD) method.
Findings
The results support the central hypothesis that mutuality of relational constructs has an impact on relationship performance.
Originality/value
The study is the first to apply the perceptual bi-directionality method to measure mutuality of relational constructs in an exporter-importer setting. The study contributes to the general understanding of international business and exporter-importer relationship performance in particular.
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Nusrat Hafiz, Md. Fazla Mohiuddin, Ahmad Shaharudin Abdul Latiff, Ida Md. Yasin, Sazali Abd Wahab and Ahmed Razman Abdul Latiff
Although scaling is considered a “hot topic”, very little is known about how knowledge management (KM) assists in scaling social impact. To fill this gap, the authors draw on…
Abstract
Purpose
Although scaling is considered a “hot topic”, very little is known about how knowledge management (KM) assists in scaling social impact. To fill this gap, the authors draw on knowledge-based and social capital theories and investigate how various KM practices and external networks (e.g. bridging social capital) affect scaling social impact in developing countries.
Design/methodology/approach
Applying structural equation modeling (SEM) with AMOS version 23, the authors conducted a survey with 354 women leaders who are working in women-led social enterprises in Dhaka, Bangladesh.
Findings
The authors found that knowledge codification, training and mentoring, and bridging social capital are positively and significantly associated with scaling social impact.
Originality/value
This is one of the pioneering study that explore how KM impacts scaling social impact for women-led social enterprises in the context of a developing country. The authors also extend knowledge-based theory by applying it at the individual level. Finally, the authors enhance the understanding of women entrepreneurship by showing that women entrepreneurs in developing countries are also utilizing bridging social capital to overcome challenges associated with scaling social impact.
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This paper aims to contribute to the current debate between the mainstream and the non-mainstream literature on the effect of the growth of finance on the level of income…
Abstract
Purpose
This paper aims to contribute to the current debate between the mainstream and the non-mainstream literature on the effect of the growth of finance on the level of income inequality, for which the empirical evidence has also been providing mixed results.
Design/methodology/approach
We estimate a linear model and a non-linear model by employing a panel autoregressive distributed lag approach and relying on the dynamic fixed-effects estimator because of the existence of variables that are stationary in levels and stationary in the first differences.
Findings
Our findings confirm that finance, economic growth, educational attainment and degree of trade openness have a positive long-term effect on the level of income inequality in the European Union countries, whilst government spending has a negative impact in the short term.
Research limitations/implications
Our findings imply that policy makers should rethink the functioning of the financial system in order to restore a supportive relationship between finance and income inequality and adopt public policies that are more in favour of the poor in order to constrain the growth of income inequality in the European Union countries.
Originality/value
To the best of our knowledge, this is the first paper that, simultaneously, focuses on the European Union countries, assesses the nexus between finance and income inequality, uses three different variables as proxies for the level of income inequality (the Gini coefficient, the top 1% income share and the top 10% income share), measures the variables that are proxies for the level of income inequality in terms of pre-tax and pre-transfer values and as post-tax and post-transfer values, takes into account four different variables as proxies for the role of finance (credit, credit-to-deposit ratio, liquid liabilities and stock market capitalisation) and identifies the long-term and short-term determinants of income inequality.
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Md. Shamim Hossen, AKM Mahmudul Haque, Imran Hossain, Md. Nuruzzaman Haque and Md. Kamal Hossain
Despite city authorities in Bangladesh being concerned about urban sustainability, they often face difficulties in addressing predominant urban challenges threatening urban…
Abstract
Purpose
Despite city authorities in Bangladesh being concerned about urban sustainability, they often face difficulties in addressing predominant urban challenges threatening urban sustainability, due to limited relevant literature. To reduce this gap, this study aims to address the predominant urban challenges and assess their severity levels in four city corporations of Bangladesh, e.g. Rajshahi, Sylhet, Barishal, and Gazipur.
Design/methodology/approach
Using a mixed-method approach, this study rigorously analyzed field-level data obtained from 1,200 residents across selected cities using diverse statistical techniques. The quantitative analysis included descriptive analysis, exploratory factor analysis, and chi-square tests, whereas qualitative insights were derived through thematic analysis.
Findings
The study uncovered nine predominant urban challenges under two crucial factors “Feeble Urban Management” and “Illicit Activities” that collectively explain 62.20% variance. “Feeble Urban Management” explains 44.17% variance, whereas “Illicit Activities” accounts for 18.13%. Within these challenges, uncontrolled urban sprawl, inadequate disaster management, congested roads, and shabby drainage and waste management pose significant threats to urban sustainability. Illicit activities, manifested by encroachment on water sources, grabbing roadside, destruction of natural properties, and activities undermining social security, compound the urban sustainability issue. Severity analysis reveals Sylhet (54.5%), Rajshahi (46.4%), and Barishal (31.2%) as highly impacted, whereas Gazipur exhibits moderate severity (66.7%).
Originality/value
The findings of this study reveal intrinsic insights into urban challenges in Bangladesh that will provide valuable guidance to city authorities, equipping them to implement integrated and effective initiatives and programs that overcome these predominant urban challenges, with a specific focus on Rajshahi, Sylhet, and Barishal city corporations.