Search results for: transparency of the market

Authors: Haitham Assiri, Priyadarsi Nanda

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The world is gradually entering the fourth industrial revolution. E-Government services are scaling government operations across the globe. However, as promising as an e-Government system would be, it is also susceptible to malicious attacks if not properly secured. This study found out that, in Saudi Arabia, the e-Government website, Yesser is vulnerable to external attacks. Obviously, this can lead to a breach of data integrity and privacy. In this paper, a Systematic Literature Review was conducted to explore possible ways the Kingdom of Saudi Arabia can take necessary measures to strengthen its e-Government system using Blockchain. Blockchain is one of the emerging technologies shaping the world through its applications in finance, elections, healthcare, etc. It secures systems and brings more transparency. A total of 28 papers were selected for this SLR, and 19 of the papers significantly showed that blockchain could enhance the security and privacy of Saudi’s e-government system. Other papers also concluded that blockchain is effective, albeit with the integration of other technologies like IoT, AI and big data. These papers have been analysed to sieve out the findings and set the stage for future research into the subject.

Keywords: blockchain, data integrity, e-government, security threats

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Authors: Urvashi Kaushal

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With the entry of multinationals in India, engineering students of Indian universities have opportunity to work with the best and the most innovative industries in the world, but in order to compete in the global job market, they require an added competence of communication skills in English. With work places turning global, competence in English can provide the Indian student the added advantage to begin his/her career in the international market. The present method of teaching English in any engineering college across Gujarat mostly concentrates on developing writing, and reading skills. Developing speech becomes a secondary topic owing to the old trend of lecturing in the class room and the huge strength of the class. This paper aims to highlight the importance of improving speaking skills of engineering students. It also insists that presentations can be used as a viable method to enhance the communication skills of these students. Presentations force students to plan, prepare, practice and perfect their communication skills which will enable them to get a foothold in the industry. The paper also discusses one such experiment carried out at the author’s institute and the response it received. Further, such experimental language learning approach is bound to have some limitations and obstacles. The paper suggests ways to overcome such limitations and strives to develop an interesting means of developing communication skills of the engineering students.

Keywords: engineering, English, presentation, communication skills

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Authors: Manuel Branco

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This paper argues that mainstream economics is one of the reasons that can explain the difficulty in fully realizing human rights because its logic is intrinsically contradictory to human rights, most especially economic, social and cultural rights. First, its utilitarianism, both in its cardinal and ordinal understanding, contradicts human rights principles. Maximizing aggregate utility along the lines of cardinal utility is a theoretical exercise that consists in ensuring as much as possible that gains outweigh losses in society. In this process an individual may get worse off, though. If mainstream logic is comfortable with this, human rights' logic does not. Indeed, universality is a key principle in human rights and for this reason the maximization exercise should aim at satisfying all citizens’ requests when goods and services necessary to secure human rights are at stake. The ordinal version of utilitarianism, in turn, contradicts the human rights principle of indivisibility. Contrary to ordinal utility theory that ranks baskets of goods, human rights do not accept ranking when these goods and services are necessary to secure human rights. Second, by relying preferably on market logic to allocate goods and services, mainstream economics contradicts human rights because the intermediation of money prices and the purpose of profit may cause exclusion, thus compromising the principle of universality. Finally, mainstream economics sees human rights mainly as constraints to the development of its logic. According to this view securing human rights would, then, be considered a cost weighing on economic efficiency and, therefore, something to be minimized. Fully realizing human rights needs, therefore, a different approach. This paper discusses a human rights-based political economy. This political economy, among other characteristics should give up mainstream economics narrow utilitarian approach, give up its belief that market logic should guide all exchanges of goods and services between human beings, and finally give up its view of human rights as constraints on rational choice and consequently on good economic performance. Giving up mainstream’s narrow utilitarian approach means, first embracing procedural utility and human rights-aimed consequentialism. Second, a more radical break can be imagined; non-utilitarian, or even anti-utilitarian, approaches may emerge, then, as alternatives, these two standpoints being not necessarily mutually exclusive, though. Giving up market exclusivity means embracing decommodification. More specifically, this means an approach that takes into consideration the value produced outside the market and an allocation process no longer necessarily centered on money prices. Giving up the view of human rights as constraints means, finally, to consider human rights as an expression of wellbeing and a manifestation of choice. This means, in turn, an approach that uses indicators of economic performance other than growth at the macro level and profit at the micro level, because what we measure affects what we do.

Keywords: economic and social rights, political economy, economic theory, markets

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Authors: Miju Choi, Ava Seo

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Japan has been positioned as a major inbound market to Korea, accounting for about 31% of total inbound visitors until 2012. The percentage has sharply dropped each year since and remained in second place, reaching 13.33% in 2016. Meanwhile, China has been boosted as a major inbound market, reaching 46.79% in 2016. Chinese tourists mainly visit Korea with the major purpose of shopping. They consume Korean cosmetic/beauty products and clothes while Japanese tourists prefer to purchase healthy food such as ginseng and seaweed. This study aims to investigate and compare tourist shopping patterns across two major inbound markets, China and Japan. A quantitative approach using survey was applied from 2009 to 2016. Findings suggest Chinese visit Korea due to quality of product, value for money, and accessibility, and trust. Meanwhile, Japanese choose Korea as a shopping destination mainly due to convenience, affordability, and tourist attractions. Also, there were significant differences in shopping venues. For example, Japanese tourists prefer shopping at department stores while Chinese tourists prefer retail outlets and local markets. This study contributes to deeper understanding on two major inbound markets to Korea and suggests future marketing strategies.

Keywords: tourist shopping patterns, Korea, China, Japan, historical data

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Authors: Jun Wang, Ge Zhang

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Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Nabeeha Hassan Abdel Jalil, Robert Barigye, Hamda Al Alawi, Afra Al Dhaheri, Fatma Graiban Al Muhairi, Maryam Al Khateri, Nouf Al Alalawi, Susan Olet, Khaja Mohteshamuddin, Ahmad Al Aiyan, Mohamed Elfatih Hamad

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A serological survey was carried out to determine the seroprevalence of Brucella spp, Coxiella burnetii, Chlamydophila abortus, and Toxoplasma gondii in sheep and goat herds in the UAE. A total of 915 blood samples [n= 222, [sheep]; n= 215, [goats]) were collected from livestock farms in the Emirates of Abu Dhabi, Dubai, Sharjah and Ras Al-Khaimah (RAK). An additional 478 samples (n= 244, [sheep]; n= 234, (goats]) were collected from the Al Ain livestock central market and tested by indirect ELISA for pathogen-specific antibodies with the Brucella antibodies being further corroborated by the Rose-Bengal agglutination test. Seropositivity for the four pathogens is variably documented in sheep and goats from the study area. Respectively, the overall livestock farm prevalence rates for Brucella spp, C. burnetii, C. abortus, and T. gondii were 2.7%, 27.9%, 8.1%, and 16.7% for sheep, and 0.0%, 31.6%, 9.3%, and 5.1% for goats. Additionally, the seroprevalence rates Brucella spp, C. burnetii, C. abortus, and T. gondii in samples from the livestock market were 7.4%, 21.7%, 16.4%, and 7.0% for sheep, and 0.9%, 32.5%, 19.2%, and 11.1% for goats respectively. Overall, sheep had 12.59 more chances than goats of testing seropositive for Brucella spp (OR, 12.59 [95% CI 2.96-53.6]) but less likely to be positive for C. burnetii-antibodies (OR, 0.73 [95% CI 0.54-0.97]). Notably, the differences in the seroprevalence rates of C. abortus and T. gondii in sheep and goats were not statistically significant (p > 0.0500). The present data indicate that all the four study pathogens are present in sheep and goat populations in the UAE where coxiellosis is apparently the most seroprevalent followed by chlamydophilosis, toxoplasmosis, and brucellosis. While sheep from the livestock market were more likely than those from farms to be Brucella-seropositive than those, the overall exposure risk of C. burnetii appears to be greater for goats than sheep. As more animals from the livestock market were more likely to be seropositive to Chlamydophila spp, it is possible that under the UAE animal production conditions, at least, coxiellosis and chlamydophilosis are more likely to increase the culling rate of domesticated small ruminants than toxoplasmosis and brucellosis. While anecdotal reports have previously insinuated that brucellosis may be a significant animal health risk in the UAE, the present data suggest C. burnetii, C. abortus and T. gondii to be more significant pathogens of sheep and goats in the country. Despite this possibility, the extent to which these pathogens may nationally be contributing to reproductive failure in sheep and goat herds is not known and needs to be investigated. Potentially, these agents may also carry a potentially zoonotic risk that needs to be investigated in risk groups like farm workers, and slaughter house personnel. An ongoing study is evaluating the seroprevalence of bovine coxiellosis in the Emirate of Abu Dhabi and the data thereof will further elucidate on the broader epidemiological dynamics of the disease in the national herd.

Keywords: Brucella spp, Chlamydophila abortus, goat, sheep, Toxoplasma gondii, UAE

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Authors: Ehsan Daryadel, Hamid Shakeri

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Good governance is considered as one of the necessary prerequisites for promotion of sustainable development programs in countries. Theoretical model of good governance is going to form the best methods for administration and management of subject country. The importance of maintaining the balance between the needs of present and future generation through sustainable development caused a change in method of management and providing service for citizens that is addressed as the most efficient and effective way of administration of countries. This method is based on democratic and equal-seeking sustainable development which is trying to affect all actors in this area and also be accountable to all citizens’ needs. Meanwhile, it should be noted that good governance is a prerequisite for sustainable development. In fact, good governance means impact of all actors on administration and management of the country for fulfilling public services, general needs of citizens and establishing a balance and harmony between needs of present and future generation. In the present study, efforts have been made to present concepts, definitions, purposes and indices of good governance with a descriptive-analytical method.

Keywords: accountability, efficiency and effectiveness, good governance, rule of law, transparency

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Authors: Nicole Anne Bass Monsanto

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The objective of this study were to identify the numerous effective ways of capturing new members to participate in the brand hotel loyalty programs through the following objectives: (1) To differentiate the appropriate approach on selling the loyalty program to the different consumer market within their tier; (2) to evaluate the different behavioural degree of guests from different aspects of class and preference; (3) to compare the 3 hospitality tiers and the best tactic of approach according to their target market; (4) to assess the best practices suitable to the category of hotel in their specific tier. This study is a mixed methods research which involves both qualitative and quantitative. The qualitative research consisted of twelve management level respondents from 6 different hotels. These hotels were subdivided into 3 hotel tiers -- Luxury Hotels Upper Upscale Hotels and Mid-Scale Hotels—and the research studied two hotels of each hotel tier. Meanwhile, the quantitative research was conducted to further confirm and enhance the results by the means of guest post-stay surveys. Research findings of the qualitative research were as follows: (1) There are no differentiated best practices in capturing new enrolments based on the hotel tier. (2) There is only one key tool that determines the hotel loyalty program enrolment success. Meanwhile, the research findings of the quantitative research lead to the conclusion that most guests do not participate in the loyalty program was because they were not invited from the start.

Keywords: best practices, loyalty program, hospitality tier, enrollment success

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Authors: Errol J. Haarhoff

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Housing in New Zealand, particularly in Auckland, is dominated by low-density suburbs. Over the past 20 years, housing intensification policies aimed to curb outward low-density sprawl and to concentrate development within an urban boundary have been implemented. This requires the greater deployment of attached housing typologies such apartments, duplexes and terrace housing. There has been strong market response and uptake for higher density development, with the number of building approvals received by the Auckland Council for attached housing units increasing from around 15 percent in 2012/13, to 54 percent in 2017/18. A key question about intensification and strong market uptake in a city where lower density has been the norm, is whether higher density neighborhoods will deliver necessary housing satisfaction? This paper reports on the findings to a questionnaire survey and focus group discussions probing resident perceptions to living at higher density in relation to their dwellings, the neighborhood and their sense of community. The findings reveal strong overall housing satisfaction, including key aspects such as privacy, noise and living in close proximity to neighbors. However, when residents are differentiated in terms of length of tenure, age or whether they are bringing up children, greater variation in satisfaction is detected. For example, residents in the 65-plus age cohort express much higher levels of satisfaction, when compared to the 18-44 year cohorts who more likely to be binging up children. This suggests greater design sensitivity to better accommodate the range of household types. Those who have live in the area longer express greater satisfaction than those with shorter duration, indicating time for adaption to living at higher density. Findings strongly underpin the instrumental role that the public amenities play in overall housing satisfaction and the emergence of a strong sense of community. This underscores the necessity for appropriate investment in the public amenities often lacking in market-led higher density housing development. We conclude with an evaluation of the PPP model, and its part in delivering housing satisfaction. The findings should be of interest to cities, housing developers and built environment professional pursuing housing policies promoting intensification and higher density.

Keywords: medium density, housing satisfaction, neighborhoods, sense of community

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Authors: Jerlin George, R. Chitra

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The devices with sensors that can monitor your temperature, heart rate, and other vital signs and link to the internet, known as the Internet of Things (IoT), have completely transformed the way we control health. Providing real-time health data, these sensors improve diagnostics and treatment outcomes. Security and privacy matters when IoT comes into play in healthcare. Cyberattacks on centralized database systems are also a problem. To solve these challenges, the study uses blockchain technology coupled with proxy re-encryption to secure health data. ThingSpeak IoT cloud analyzes the collected data and turns them into blockchain transactions which are safely kept on the DriveHQ cloud. Transparency and data integrity are ensured by blockchain, and secure data sharing among authorized users is made possible by proxy re-encryption. This results in a health monitoring system that preserves the accuracy and confidentiality of data while reducing the safety risks of IoT-driven healthcare applications.

Keywords: internet of things, healthcare, sensors, electronic health records, blockchain, proxy re-encryption, data privacy, data security

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Authors: S. Tavuyanago

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Cartels within the international competition law framework have been dubbed the most egregious of competition law violations; this is because they entail a concerted effort by two or more competitor firms to knowingly ‘rob’ consumers of their welfare through their cooperation instead of competition. The net effect of cartel conduct is that the market is distorted as the colluding firms gain enough market power to constrain the supply of goods or services, ultimately driving up prices. As a result, consumers end up paying inflated prices for goods and services, which eventually affects their welfare. It is against this backdrop that competition authorities worldwide have mounted a robust fight against the proliferation of cartels. In South Africa, the fight against cartels saw an amendment to the Competition Act to allow for criminal prosecution of individuals who cause their firms to take part in cartels. The Competition Amendment Act 1 of 2009 introduced section 73A into the principal Competition Act, making it a criminal offence to engage in cartel conduct. This paper assesses the rationale for criminalisation of cartel conduct, discusses the challenges or potential challenges associated with criminalisation, and provides an evaluation of the efficacy of criminalisation of cartel conduct. It questions whether criminal sanctions for cartel conduct as a competition enforcement tool aimed at deterring such conduct are generally effective and whether they have been effective in South Africa specifically. It concludes by offering recommendations on how to effectively root out cartels.

Keywords: cartels, criminalisation, competition, deterrence, South Africa

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Authors: Sohanur Rahman, Elisabeth Sinnewe, Larelle (Ellie) Chapple, Sarah Osborne

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Greater political attention to global climate change exposes firms to a higher level of political uncertainty, which can lead to adverse capital market consequences. However, a higher level of discourse on environment-specific political risk (EPR) between management and investors can mitigate information asymmetry, followed by less stock price crash risk. This study examines whether EPR discourse in discourse in the earnings conference calls (ECC) reduces firm-level stock price crash risk in the US market. This research also explores if adverse disclosures via media channels further moderates the association between EPR on crash risk. Employing a dataset of 28,933 firm-year observations from 2002 to 2020, the empirical analysis reveals that EPR discourse in ECC reduces future stock price crash risk. However, adverse disclosures via media channels can offset the favourable effect of EPR discourse on crash risk. The results are robust to the potential endogeneity concern in a quasi-natural experiment setting.

Keywords: earnings conference calls, environment, environment-specific political risk discourse, environmental disclosures, information asymmetry, reputation risk, stock price crash risk

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Authors: Hanen Khanchel, Karim Ben Kahla

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Pharmaceutical companies are facing competition. Indeed, the price differences between competing products can be such that it becomes difficult to compensate them by differences in value added. The conditions of competition are no longer homogeneous for the players involved. The price of a product is a given that puts a company and its customer face to face. However, price fixing obliges the company to consider internal factors relating to production costs and external factors such as customer attitudes, the existence of regulations and the structure of the market on which the firm evolved. In setting the selling price, the company must first take into account internal factors relating to its costs: costs of production fall into two categories, fixed costs and variable costs that depend on the quantities produced. The company cannot consider selling below what it costs the product. It, therefore, calculates the unit cost of production to which it adds the unit cost of distribution, enabling it to know the unit cost of production of the product. The company adds its margin and thus determines its selling price. The margin is used to remunerate the capital providers and to finance the activity of the company and its investments. Production costs are related to the quantities produced: large-scale production generally reduces the unit cost of production, which is an asset for companies with mass production markets. This shows that small and medium-sized companies with limited market segments need to make greater efforts to ensure their profit margins. As a result, and faced with high and low market prices for raw materials and increasing staff costs, the company must seek to optimize its production time in order to reduce loads and eliminate waste. Then, the customer pays only value added. Thus, and based on this principle we decided to create a project that deals with the problem of waste in our company, and having as objectives the reduction of production costs and improvement of performance indicators. This paper presents the implementation of the Value Stream Mapping (VSM) project in a pharmaceutical company. It is structured as follows: 1) determination of the family of products, 2) drawing of the current state, 3) drawing of the future state, 4) action plan and implementation.

Keywords: VSM, waste, production time, kaizen, cartography, improvement

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Authors: Matteo Bonaventura, Giancarlo Giudici

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This paper analyses the valuation process of companies listed on the Italian Exchange in the period 2000-2009 at their Initial Public Offering (IPO). One the most common valuation techniques declared in the IPO prospectus to determine the offer price is the Discounted Cash Flow (DCF) method. We develop a ‘reverse engineering’ model to discover the short term profitability implied in the offer prices. We show that there is a significant optimistic bias in the estimation of future profitability compared to ex-post actual realization and the mean forecast error is substantially large. Yet we show that such error characterizes also the estimations carried out by analysts evaluating non-IPO companies. The forecast error is larger the faster has been the recent growth of the company, the higher is the leverage of the IPO firm, the more companies issued equity on the market. IPO companies generally exhibit better operating performance before the listing, with respect to comparable listed companies, while after the flotation they do not perform significantly different in term of return on invested capital. Pre-IPO book building activity plays a significant role in partially reducing the forecast error and revising expectations, while the market price of the first day of trading does not contain information for further reducing forecast errors.

Keywords: initial public offerings, DCF, book building, post-IPO profitability drop

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Authors: Anh Dao Vu, Bill Ryan

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The Vietnamese government struggles to grapple with the problem of rampant corruption, one of the most challenging difficulties the country faces. According to Transparency International’s Corruption Perceptions Index (CPI) 2014, Vietnam ranks 119 out of 175 countries. The CPI gives Vietnam a score of 31 on a scale from 0 to 100, where 0 indicates ‘highly corrupt’ and 100 represents ‘very clean’. Corruption eats into the national GDP of Vietnam, causing a loss of 3% to 4% of GDP per annum. In general, the Vietnamese people’s trust in their government to wage an effective fight against corruption, especially in the public sector, has been greatly eroded in recent years. Some substantial public demonstrations persuaded the government to implement strong anti-corruption measures. However, so far those measures have not been particularly successful. One of the main reasons for this shortcoming is that neither the Communist Party of Vietnam nor the government has demonstrated sufficiently strong ‘political will’ in fighting corruption. There remains a large gap between rhetoric and reality. This paper will examine the reasons why insufficient ‘political will’ is displayed in the ostensible fight against public sector corruption, and how certain anti-corruption strategies will both strengthen levels of political commitment to the fight against corruption while enhancing the effectiveness of that essential national endeavor.

Keywords: corruption, political will, Vietnam, anti-corruption

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Authors: Julio Aguirre, Yohnny Campana, Elmer Guerrero, Daniel De La Torre Ugarte

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A well-developed transportation network is a necessary condition for a country to derive full benefits from good trade and macroeconomic policies. Road infrastructure plays a key role in the economic development of rural areas of developing countries; where agriculture is the main economic activity. The ability to move agricultural production from the place of production to the market, and then to the place of consumption, greatly influence the economic value of farming activities, and of the resources involved in the production process, i.e., labor and land. Consequently, investment in transportation networks contributes to enhance or overcome the natural advantages or disadvantages that topography and location have imposed over the agricultural sector. This is of particular importance when dealing with countries, like Peru, with a great topographic diversity. The objective of this research is to estimate the impacts of road infrastructure on the performance of the agricultural sector. Specific variables of interest are changes in travel time, shifts of production for self-consumption to production for the market, changes in farmers income, and impacts on the diversification of the agricultural sector. In the study, a cross-section model with instrumental variables is the central methodological instrument. The data is obtained from agricultural and transport geo-referenced databases, and the instrumental variable specification utilized is based on the Kruskal algorithm. The results show that the expansion of road connectivity reduced farmers' travel time by an average of 3.1 hours and the proportion of output sold in the market increases by up to 40 percentage points. The increase in connectivity has an unexpected increase in the districts index of diversification of agricultural production. The results are robust to the inclusion of year and region fixed-effects, and to control for geography (i.e., slope and altitude), population variables, and mining activity. Other results are also very eloquent. For example, a clear positive impact can be seen in access to local markets, but this does not necessarily correlate with an increase in the production of the sector. This can be explained by the fact that agricultural development not only requires provision of roads but additional complementary infrastructure and investments intended to provide the necessary conditions so that producers can offer quality products (improved management practices, timely maintenance of irrigation infrastructure, transparent management of water rights, among other factors). Therefore, complementary public goods are needed to enhance the effects of roads on the welfare of the population, beyond enabling them to increase their access to markets.

Keywords: agriculture devolepment, market access, road connectivity, regional development

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Authors: Duduku Krishnaiah, S. M. Anisuzzaman, Kumaran Govindaraj, Chiam Chel Ken, Zykamilia Kamin

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Pure essential oil is highly demanded in the market since most of the so-called pure essential oils in the market contains alcohol. This is because of the usage of alcohol in separating oil and water mixture. Removal of pure essential oil from water without using any chemical solvent has become a challenging issue. Adsorbents generally have the properties of separating hydrophobic oil from hydrophilic mixture. Polypropylen nanofiber is a thermoplastic polymer which is produced from propylene. It was used as an adsorbent in this study. Based on the research, it was found that the polypropylene nanofiber was able to adsorb peppermint oil from the aqueous solution over a wide range of concentration. Based on scanning electron microscope (SEM), nanofiber has very small nano diameter fiber size in average before the adsorption and larger scaled average diameter of fibers after adsorption which indicates that smaller diameter of nanofiber enhances the adsorption process. The adsorption capacity of peppermint oil increases as the initial concentration of peppermint oil and amount of polypropylene nanofiber used increases. The maximum adsorption capacity of polypropylene nanofiber was found to be 689.5 mg/g at (T= 30°C). Moreover, the adsorption capacity of peppermint oil decreases as the temperature of solution increases. The equilibrium data of polypropylene nanofiber is best represented by Freundlich isotherm with the maximum adsorption capacity of 689.5 mg/g. The adsorption kinetics of polypropylene nanofiber was best represented by pseudo-second order model.

Keywords: nanofiber, adsorption, peppermint essential oil, isotherms, adsorption kinetics

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Authors: Jayanta Pokharel, Gokarna Aryal, Netra Kanaal, Chris Tsokos

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Investment in stocks and shares aims to seek potential gains while weighing the risk of future needs, such as retirement, children's education etc. Analysis of the behavior of the stock market returns and making prediction is important for investors to mitigate risk on investment. Historically, the normal variance models have been used to describe the behavior of stock market returns. However, the returns of the financial assets are actually skewed with higher kurtosis, heavier tails, and a higher center than the normal distribution. The Laplace distribution and its family are natural candidates for modeling stock returns. The Variance-Gamma (VG) distribution is the most sought-after distributions for modeling asset returns and has been extensively discussed in financial literatures. In this paper, it explore the other Laplace family, such as Asymmetric Laplace, Skewed Laplace, Kumaraswamy Laplace (KS) together with Variance-Gamma to model the weekly returns of the S&P 500 Index and it's eleven business sector indices. The method of maximum likelihood is employed to estimate the parameters of the distributions and our empirical inquiry shows that the Kumaraswamy Laplace distribution performs much better for stock returns modeling among the choice of distributions used in this study and in practice, KS can be used as a strong alternative to VG distribution.

Keywords: stock returns, variance-gamma, kumaraswamy laplace, maximum likelihood

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Authors: Cheng-yu Hsieh, Bo Zhang, Ahmed Hambaba

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Stock market prediction has long been an area of interest for both expert analysts and investors, driven by its complexity and the noisy, volatile conditions it operates under. This research examines the efficacy of combining the Patch Time Series Transformer (PatchTST) with wavelet transforms, specifically focusing on Haar and Daubechies wavelets, in forecasting the adjusted closing price of the S&P 500 index for the following day. By comparing the performance of the augmented PatchTST models with traditional predictive models such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Transformers, this study highlights significant enhancements in prediction accuracy. The integration of the Daubechies wavelet with PatchTST notably excels, surpassing other configurations and conventional models in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE). The success of the PatchTST model paired with Daubechies wavelet is attributed to its superior capability in extracting detailed signal information and eliminating irrelevant noise, thus proving to be an effective approach for financial time series forecasting.

Keywords: deep learning, financial forecasting, stock market prediction, patch time series transformer, wavelet transform

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Authors: Petr Konvalina, Jan Moudry

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As organic farmers are searching foregoing crops for horticultural crops, there is possible to choice neglected wheat species and also have a new market and sale opportunities. Concerning wheat, there are landraces so called hulled wheat species (einkorn, emmer wheat, spelt) comprising parts of collections of the world gene banks. The advantage of this wheat species are small demands on growing conditions and also droughtiness in conditions of changing climate. Our paper aims at presenting the results of the study and the assessment of spring wheat forms, four einkorn cultivars, eight emmer wheat cultivars, seven spelt wheat cultivars in particular, as compared to modern bread wheat variety. Small-plot trials were established at two different localities within the Czech Republic and Austria in 2009 and 2012. The results of the trials show that some varieties were inclined to lodging. On the other hand, they were resistant to common wheat diseases (mildew, brown rust). Hulls served as barriers and obstacles against the DON grain contamination. The yield rate was lower. The grains were characterized by a high proportion of protein in grain (up to 18.1 %). However, they may be difficult to use for common baking. Moreover, new food products demonstrating a different technological quality of the hulled wheat species have to be launched on the market. They will be suitable for regional marketing.

Keywords: organic farming, hulled wheat species, einkorn, emmer, spelt

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Authors: Stéphanie Looser, Walter Wehrmeyer

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Given the limited research on Small and Mediumsized Enterprises’ (SMEs) contribution to Corporate Social Responsibility (CSR) and even scarcer research on Swiss SMEs, this paper helps to fill these gaps by enabling the identification of supranational SME parameters and to make a contribution to the evolving field of these topics. Thus, the paper investigates the current state of SME practices in Switzerland and across 15 other countries. Combining the degree to which SMEs demonstrate an explicit (or business case) approach or see CSR as an implicit moral activity with the assessment of their attributes for “variety of capitalism” defines the framework of this comparative analysis. According to previous studies, liberal market economies, e.g. in the United States (US) or United Kingdom (UK), are aligned with extrinsic CSR, while coordinated market systems (in Central European or Asian countries) evolve implicit CSR agendas. To outline Swiss small business CSR patterns in particular, 40 SME owner-managers were interviewed. The transcribed interviews were coded utilising MAXQDA for qualitative content analysis. A secondary data analysis of results from different countries (i.e., Australia, Austria, Chile, Cameroon, Catalonia (notably a part of Spain that seeks autonomy), China, Finland, Germany, Hong Kong (a special administrative region of China), Italy, Netherlands, Singapore, Spain, Taiwan, UK, US) lays groundwork for this comparative study on small business CSR. Applying the same coding categories (in MAXQDA) for the interview analysis as well as for the secondary data research while following grounded theory rules to refine and keep track of ideas generated testable hypotheses and comparative power on implicit (and the lower likelihood of explicit) CSR in SMEs retrospectively. The paper identifies Swiss small business CSR as deep, profound, “soul”, and an implicit part of the day-to-day business. Similar to most Central European, Mediterranean, Nordic, and Asian countries, explicit CSR is still very rare in Swiss SMEs. Astonishingly, also UK and US SMEs follow this pattern in spite of their strong and distinct liberal market economies. Though other findings show that nationality matters this research concludes that SME culture and its informal CSR agenda are strongly formative and superseding even forces of market economies, nationally cultural patterns, and language. In a world of “big business”, explicit “business case” CSR, and the mantra that “CSR must pay”, this study points to a distinctly implicit small business CSR model built on trust, physical closeness, and virtues that is largely detached from the bottom line. This pattern holds for different cultural contexts and it is concluded that SME culture is stronger than nationality leading to a supra-national, monolithic SME CSR approach. Hence, classifications of countries by their market system or capitalism, as found in the comparative capitalism literature, do not match the CSR practices in SMEs as they do not mirror the peculiarities of their business. This raises questions on the universality and generalisability of management concepts.

Keywords: CSR, comparative study, cultures of capitalism, small, medium-sized enterprises

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Authors: Mohammad Abdulaziz Algrnas, Emma Mulliner

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Housing projects have been established in Saudi Arabia, by both government and private construction companies, to meet the increasing demand from Saudi inhabitants across the country. However, the real estate market supply does not meet consumer preference requirements. Preferences normally differ depending on the consumer’s situation, such as the household’s sociological characteristics (age, household size and composition), resources (income, wealth, information and experience), tastes and priorities. Collecting information about consumer attitudes, preferences and perceptions is important for the real estate market in order to better understand housing demand and to ensure that this is met by appropriate supply. The aim of this paper is to identify consumer preferences for housing in Saudi Arabia. A quantitative closed-ended questionnaire was conducted with housing consumers in Saudi Arabia in order to gain insight into consumer needs, current household situation, preferences for a number of investigated housing attributes and consumers’ perceptions around the current housing problem. 752 survey responses were obtained and analysed in order to describe preferences for housing attributes and make comparisons between groups. Factor analysis was also conducted to identify and reduce the attributes. The results indicate a difference in preference according to the gender of the respondents and depending on their region of residence.

Keywords: housing attributes, Saudi Arabia, consumer preferences, housing preferences

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Authors: Periklis Brakatsoulas

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Recent empirical research shows a growing interest in investment decision-making under market anomalies that contradict the rational paradigm. Momentum is undoubtedly one of the most robust anomalies in the empirical asset pricing research and remains surprisingly lucrative ever since first documented. Although predominantly phenomena identified across equities, momentum premia are now evident across various asset classes. Yet few many attempts are made so far to provide traders a diversified portfolio of strategies across different assets and markets. Moreover, literature focuses on patterns from past returns rather than mechanisms to signal future price directions prior to momentum runs. The aim of this paper is to develop a diversified portfolio approach to price distortion signals using daily position data on stocks, credit derivatives, and bonds. An algorithm allocates assets periodically, and new investment tactics take over upon price momentum signals and across different ranking groups. We focus on momentum life cycles, trend reversals, and price acceleration signals. The main effort here concentrates on the density, time span and maturity of momentum phenomena to identify consistent patterns over time and measure the predictive power of buy-sell signals generated by these anomalies. To tackle this, we propose a two-stage modelling process. First, we generate forecasts on core macroeconomic drivers. Secondly, satellite models generate market risk forecasts using the core driver projections generated at the first stage as input. Moreover, using a combination of the ARFIMA and FIGARCH models, we examine the dependence of consecutive observations across time and portfolio assets since long memory behavior in volatilities of one market appears to trigger persistent volatility patterns across other markets. We believe that this is the first work that employs evidence of volatility transmissions among derivatives, equities, and bonds to identify momentum life cycle patterns.

Keywords: forecasting, long memory, momentum, returns

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Authors: Wisdom Robert Duruji

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Local farmers and fruit processors in developing countries of West Africa use different ripening agents to accelerate the ripening process of plantain and banana. This study reports on the influence of different ripening agents on the shelf-life and microbial load of organic and inorganic plantain (Musa paradisiaca) and banana (Musa sapientum) during ripening process and the health implication for food security in Nigeria. The experiment consisted of four treatments, namely: Calcium carbide, Irvingia gabonensis fruits, Newbouldia laevis leaves and a control, where no ripening agent was applied to the fingers of plantain and banana. The unripe and ripened plantain and banana were subjected to microbial analysis by isolating their micro flora (Bacteria, Yeast and Mould) using pour plate method. Microbes present in the samples were enumerated, characterized and classified to genera and species. The result indicated that the microbial load of inorganic plantain from (Urban day) open market in Ile-Ife increased from 8.00 for unripe to 12.11 cfu/g for ripened; and the microbial load of organic plantain from Obafemi Awolowo University Teaching and Research Farm (OAUTRF) increased from 6.00 for unripe to 11.60 cfu/g for ripened. Also, the microbial load of inorganic banana from (Urban day) open market in Ile-Ife increased from 8.00 for unripe to 11.50 cfu/g for ripened; while the microbial load of organic banana from OAUTRF increased from 6.50 for unripe to 9.40 cfu/g for ripened. The microbial effects of the ripening agents increased from 10.00 for control to 16.00 cfu/g for treated (ripened) organic and inorganic plantain; while that of organic and inorganic banana increased from 7.50 for control to 14.50 cfu/g for ripened. Visual observation for the presence of fungal colonies and deterioration rates were monitored till seven days after the plantain and banana fingers have fully ripened. Inorganic plantain and banana from (Urban day) open market in Ile-Ife are more contaminated than organic plantain and banana fingers from OAUTRF. The ripening accelerators reduced the shelf life, increased senescence, and microbial load of plantain and banana. This study concluded that organic Agriculture is better and microbial friendlier than inorganic farming.

Keywords: organic agriculture, food security, Musaceae, calcium carbide, Irvingia gabonensis, Newbouldia laevis

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Authors: Edward Pol

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All companies are confronted with the need to innovate in order to meet market demands. In so doing they are challenged with the dilemma of whether to aim to be first into the market with a new innovative product or to deliberately wait and learn from a pioneers’ mistakes; potentially avoiding higher risks. It is therefore important to critically understand from a first-mover advantage and disadvantage perspective the decision-making implications of defence industry transformation onset by an innovative paradigm shift. This paper will argue that the type of industry characteristics matter, especially when considering what role the clients play in the innovation process and what is their level of influence. Through investigation of qualitative case study research, this inquiry will focus on first mover advantages and first mover disadvantages with a view to establish practical and value-added academic findings by focusing on specific industries where the clients play an active role in cooperation with the supplier innovation. The resulting findings will help managers to mitigate risk in innovative technology introduction. A selection from several defense industry innovations is specifically chosen because of the client-supplier relationship typically differing from traditional first-mover research. In this instance, case studies will be used referencing vertical-takeoff-and-landing defence equipment innovations.

Keywords: innovation, pioneer, first-mover advantage, first-mover disadvantage, risk

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Authors: Shalaka Kadam, Dinesh Apte, Sagar Mainkar

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The life cycle of products is becoming shorter and shorter due to increased competition in market, shorter product development time and increased product diversity. Short life cycles are normal in retail industry, style business, entertainment media, and telecom and semiconductor industry. The subject of accurate forecasting for demand of short lifecycle products is of special enthusiasm for many researchers and organizations. Due to short life cycle of products the amount of historical data that is available for forecasting is very minimal or even absent when new or modified products are launched in market. The companies dealing with such products want to increase the accuracy in demand forecasting so that they can utilize the full potential of the market at the same time do not oversupply. This provides the challenge to develop a forecasting model that can forecast accurately while handling large variations in data and consider the complex relationships between various parameters of data. Many statistical models have been proposed in literature for forecasting time series data. Traditional time series forecasting models do not work well for short life cycles due to lack of historical data. Also artificial neural networks (ANN) models are very time consuming to perform forecasting. We have studied the existing models that are used for forecasting and their limitations. This work proposes an effective and powerful forecasting approach for short life cycle time series forecasting. We have proposed an approach which takes into consideration different scenarios related to data availability for short lifecycle products. We then suggest a methodology which combines statistical analysis with structured judgement. Also the defined approach can be applied across domains. We then describe the method of creating a profile from analogous products. This profile can then be used for forecasting products with historical data of analogous products. We have designed an application which combines data, analytics and domain knowledge using point-and-click technology. The forecasting results generated are compared using MAPE, MSE and RMSE error scores. Conclusion: Based on the results it is observed that no one approach is sufficient for short life-cycle forecasting and we need to combine two or more approaches for achieving the desired accuracy.

Keywords: forecast, short life cycle product, structured judgement, time series

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Authors: Bilal Ahmad Malik

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With the fall of Soviet Union in 1991 the whole Central Asian region saw a dramatic rise in Muslim identity, a call back to Islamic legacy. Today, many Central Asian Muslims demand, what Islam has termed legal (Halal) and, avoid what Islam has termed illegal (Haram). The process of Islamic resurgence kicked off very quickly soon after the integration of Central Asian republics with other Muslim geographies through the membership of Organization of Islamic Conference (OIC) and other similar organizations. This interaction proved to be a vital push factor to the already existing indigenous reviving trends and sentiments. As a result, along with many other requirements, Muslim customer demand emerged as navel trend in the market in general and in banking and financial sector in particular. To get this demand fulfilled, the governments of CIS states like Kazakhstan, Uzbekistan, Azerbaijan, Turkmenistan, Kyrgyzstan and Tajikistan introduced Halal banking and financial products in the market. Firstly, the present paper would briefly discuss the core composition of Halal banking and financial products. Then, coming to its major theme, it would try to identify and analyze the causes that lead to the emergence of Islamic banking and finance industry in the Muslim majority Post-Soviet CIS States.

Keywords: causes, Central Asia, interest-free banking, Islamic Revival

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Authors: Barkha Ramteke, Sonali Ridhorkar

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An election is an important event in all countries. Traditional voting has several drawbacks, including the expense of time and effort required for tallying and counting results, the cost of papers, arrangements, and everything else required to complete a voting process. Many countries are now considering online e-voting systems, but the traditional e-voting systems suffer a lack of trust. It is not known if a vote is counted correctly, tampered or not. A lack of transparency means that the voter has no assurance that his or her vote will be counted as they voted in elections. Electronic voting systems are increasingly using blockchain technology as an underlying storage mechanism to make the voting process more transparent and assure data immutability as blockchain technology grows in popularity. The transparent feature, on the other hand, may reveal critical information about applicants because all system users have the same entitlement to their data. Furthermore, because of blockchain's pseudo-anonymity, voters' privacy will be revealed, and third parties involved in the voting process, such as registration institutions, will be able to tamper with data. To overcome these difficulties, we apply Ethereum smart contracts into blockchain-based voting systems.

Keywords: blockchain, AMV chain, electronic voting, decentralized

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Authors: Su Yen Chen

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ChatGPT has shown both strengths and limitations in clinical, educational, and research settings, raising important concerns about accuracy, transparency, and ethical use. Despite an improved understanding of user acceptance and satisfaction, there is still a gap in how general AI perceptions translate into practical applications within healthcare. This study focuses on examining the perceptions of ChatGPT's impact among 266 healthcare majors in Taiwan, exploring its implications for their career development, as well as its utility in clinical practice, medical education, and research. By employing a structured survey with precisely defined subscales, this research aims to probe the breadth of ChatGPT's applications within healthcare, assessing both the perceived benefits and the challenges it presents. Additionally, to further enhance the comprehensiveness of our methodology, we have incorporated qualitative data collection methods, which provide complementary insights to the quantitative findings. The findings from the survey reveal that perceptions and usage of ChatGPT among healthcare majors vary significantly, influenced by factors such as its perceived utility, risk, novelty, and trustworthiness. Graduate students and those who perceive ChatGPT as more beneficial and less risky are particularly inclined to use it more frequently. This increased usage is closely linked to significant impacts on personal career development. Furthermore, ChatGPT's perceived usefulness and novelty contribute to its broader impact within the healthcare domain, suggesting that both innovation and practical utility are key drivers of acceptance and perceived effectiveness in professional healthcare settings. Trust emerges as an important factor, especially in clinical settings where the stakes are high. The trust that healthcare professionals place in ChatGPT significantly affects its integration into clinical practice and influences outcomes in medical education and research. The reliability and practical value of ChatGPT are thus critical for its successful adoption in these areas. However, an interesting paradox arises with regard to the ease of use. While making ChatGPT more user-friendly is generally seen as beneficial, it also raises concerns among users who have lower levels of trust and perceive higher risks associated with its use. This complex interplay between ease of use and safety concerns necessitates a careful balance, highlighting the need for robust security measures and clear, transparent communication about how AI systems work and their limitations. The study suggests several strategic approaches to enhance the adoption and integration of AI in healthcare. These include targeted training programs for healthcare professionals to increase familiarity with AI technologies, reduce perceived risks, and build trust. Ensuring transparency and conducting rigorous testing are also vital to foster trust and reliability. Moreover, comprehensive policy frameworks are needed to guide the implementation of AI technologies, ensuring high standards of patient safety, privacy, and ethical use. These measures are crucial for fostering broader acceptance of AI in healthcare, as the study contributes to enriching the discourse on AI's role by detailing how various factors affect its adoption and impact.

Keywords: ChatGPT, healthcare, survey study, IT adoption, behaviour, applcation, concerns

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