S. Sathiyanarayanan, C. Marikkannu, P. Bala Srinivasan and V. Muthupandi
Compares the corrosion behaviour of Ti6Al4V titanium alloy, a conventional duplex stainless steel (UNS 31803) and AISI 304 austenitic stainless steel in synthetic biofluids using…
Abstract
Compares the corrosion behaviour of Ti6Al4V titanium alloy, a conventional duplex stainless steel (UNS 31803) and AISI 304 austenitic stainless steel in synthetic biofluids using electrochemical techniques and comments on the suitability of DSS for use in biomedical applications. Finds that the general corrosion resistance of duplex stainless steels is slightly inferior to that of austenitic stainless steel and titanium alloy; duplex stainless steel does not show any sign of pitting when exposed to synthetic biofluids and exhibits excellent resistance to localised corrosion on par with that of titanium alloy. Concludes that duplex stainless steels are one of the best alternates to titanium alloys.
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Jiansan Li, Yali Li, Yanqin Chen, Jiawei Sun, Chunxiao Wang, Yingcai Zheng and Huiting Zhong
This paper aims to report the influence of hexamethylenetetramine (HMTA) on phosphate coatings formed on AZ31 magnesium alloys.
Abstract
Purpose
This paper aims to report the influence of hexamethylenetetramine (HMTA) on phosphate coatings formed on AZ31 magnesium alloys.
Design/methodology/approach
These phosphate coatings were obtained by immersing magnesium alloys in phosphate baths with HMTA. The morphology and composition of the phosphate coatings were investigated via scanning electron microscopy, energy dispersive spectrometry and X-ray diffraction.
Findings
The phosphate coatings were mainly composed of CaHPO4·2H2O. The HMTA concentration in the phosphate bath influenced the crystallization and corrosion resistance of the phosphate coating.
Originality/value
The polarization curve shows that the anti-corrosion qualities of the phosphate coating were optimal when the HMTA concentration was 1.0 g/L in the phosphate bath. Electrochemical impedance spectroscopy (EIS) shows that the electrochemical impedances increased gradually when the HMTA concentration varied from 1.0 to 3.0 g/L.
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Deepak Mehra, Manas Mohan Mahapatra and Suraj Prakash Harsha
The purpose of this study is to increase the wear resistance of Mg alloy by adding hard ceramic particles to it. The inclusion of hard ceramic particles further strengthen the Mg…
Abstract
Purpose
The purpose of this study is to increase the wear resistance of Mg alloy by adding hard ceramic particles to it. The inclusion of hard ceramic particles further strengthen the Mg alloy, resulting in higher wear resistance. Mg alloys containing Zn, rare earth and Zr exhibit high specific strength and excellent creep resistance, making them suitable for aerospace components such as aircraft gearboxes and generator housings.
Design/methodology/approach
In the present study, composites have been produced in situ by using RZ5 mg alloy as matrix and TiC as reinforcement by self-propagating high-temperature synthesis technique. The abrasive wear behavior of RZ5 Mg alloy matrix reinforced with TiC particulates has also been examined. The pin-on-disc apparatus has been used for the tests. The abrasive paper is used as a counter body, and the results are obtained by changing sliding distance and applied load.
Findings
A notable enhancement in the wear resistance and mechanical properties of tested composite has been observed as compared to the RZ5 Mg alloy as a matrix. There is a uniform increment in the change in weight loss of RZ5-TiC composite with increasing sliding distance and applied load, but it decreases with increasing TiC content. The coefficient of friction (µ) also decreases uniformly with an increase in the reinforcement of TiC, but it decreases with an increase in applied load and sliding distance. The investigation of the worn composite, which determines dominant wear mechanisms as abrasion and plowing grooves on tested samples, has been done using field emission scanning electron microscopy.
Originality/value
The current manuscript provides a detailed abrasive wear analysis of RZ5-TiC composite by using different wear parameters. Specifically, extensive experimental data have been provided for RZ5-TiC composite. The effects of parameters such as applied load, sliding distance and Wt.% of TiC on the weight loss and coefficient of friction of the composites have been analyzed and discussed thoroughly.
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Kong Dejun and Li Jiahong
The purpose of this paper is to evaluate the salt spray corrosion (SSC) and electrochemical corrosion performances of CrNi, TiAlN/NiCr and CrNi–Al2O3–TiO2 coatings on H13 steel…
Abstract
Purpose
The purpose of this paper is to evaluate the salt spray corrosion (SSC) and electrochemical corrosion performances of CrNi, TiAlN/NiCr and CrNi–Al2O3–TiO2 coatings on H13 steel, which improved the corrosion resistance of H13 hot work mold.
Design/methodology/approach
CrNi, TiAlN/NiCr and CrNi–Al2O3–TiO2 coatings were fabricated on H13 hot work mold steel using a laser cladding and cathodic arc ion plating. The SSC and electrochemical performances of obtained coatings were investigated using a corrosion test chamber and electrochemical workstation, respectively. The corrosion morphologies, microstructure and phases were analyzed using an electron scanning microscope, optical microscope and X-ray diffraction, respectively, and the mechanisms of corrosion resistance were also discussed.
Findings
The CrNi coating is penetrated by corrosion media, producing the oxide of Fe3O4 on the coating surface; and the TiAlN coating is corroded to enter into the CrNi coating, forming the oxides of TiO and NiO, the mechanism is pitting corrosion, whereas the CrNi–Al2O3–TiO2 coating is not penetrated, with no oxides, showing the highest SSC resistance among the three kinds of coatings. The corrosion potential of CrNi coating, TiAlN/CrNi and CrNi–Al2O3–TiO2 coatings was –0.444, –0.481 and –0.334 V, respectively, and the corresponding polarization resistances were 3,074, 2,425 and 86,648 cm2, respectively. The electrochemical corrosion resistance of CrNi–Al2O3–TiO2 coating is the highest, which is enhanced by the additions of Al2O3 and TiO2.
Originality/value
The CrNi, TiAlN/CrNi and CrNi–Al2O3–TiO2 coatings on H13 hot work mold were firstly evaluated by the SSC and electrochemical performances.
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Md. Al Amin, Md. Abdul Ahad Mia, Tapas Bala, Mohammed Masum Iqbal and Md. Shariful Alam
The study aims to examine the green finance customers' post-usage continuance behavior based on an extended social support theory (SST). Remarkably, this study explores five…
Abstract
Purpose
The study aims to examine the green finance customers' post-usage continuance behavior based on an extended social support theory (SST). Remarkably, this study explores five indirect predictors of green finance continuance behavior (GFCB) (i.e. environmental consciousness (EC), green bank marketing initiatives (GBMI), informational supports, emotional supports (EST) and psychological reactance) and a mediator (i.e. customer satisfaction).
Design/methodology/approach
In this study data were collected from 362 respondents from Bangladesh using a purposive sampling method with a structured self-administrative questionnaire and analyzed by partial least square structural equation and modeling using SMART PLS 3.0 software.
Findings
The results depict that the five predictors, i.e. information supports (ß = 0.367, t-statistics = 2.463, p < 0.001), EST (ß = 0.206, t-statistics = 2.315, p < 0.000), EC (ß = 0.324, t-statistics = 3.484, p < 0.000), GBMI (ß = 0.288, t-statistics = 2.028, p < 0.000), psychological reactance (ß = 0.126, t-statistics = 0.969, p < 0.052) influence GFCB while satisfaction is predicted by four predictors except psychological reactance (ß = 0.126, t-statistics = 0.969, p < 0.052). In addition, customer satisfaction (ß = 0.638, t-statistics = 6.317, p < 0.005) also has an impact on continuance behavior. Besides, the study understood that four predictors indirectly influence GFCB through satisfaction except psychological reactance ((ß = 0.080, t-statistics = 964, z = 0.958p < 0.338). Finally, the coefficient of determinations (R2) indicates that the five predictors explained 65.3% of changes in satisfaction, whereas 72.8% of changes are described by the five predictors and customer satisfactions.
Practical implications
Finally, this study highlights the social and managerial implications for the implementers of the green finance industry. It is recommended to emphasize green finance practice as it plays a crucial role in promoting environmental protection, ensuring social equity and driving economic growth. The green banking service providers, industry analysts, green consumers and respective government authorities can generalize green finance activities as an essential aspect of sustainable development to equalize the economic growth with a view to protecting environmental collapse and promoting renewable energy, energy efficiency, sustainable agriculture and other environmentally friendly activities.
Originality/value
The study will enormously contribute to the existing literature validating the proposed holistic framework applying SST along with EC, GBMI and psychological reactance in green finance continuance behavior.
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Birol Yıldız and Şafak Ağdeniz
Purpose: The main aim of the study is to provide a tool for non-financial information in decision-making. We analysed the non-financial data in the annual reports in order to show…
Abstract
Purpose: The main aim of the study is to provide a tool for non-financial information in decision-making. We analysed the non-financial data in the annual reports in order to show the usage of this information in financial decision processes.
Need for the Study: Main financial reports such as balance sheets and income statements can be analysed by statistical methods. However, an expanded financial reporting framework needs new analysing methods due to unstructured and big data. The study offers a solution to the analysis problem that comes with non-financial reporting, which is an essential communication tool in corporate reporting.
Methodology: Text mining analysis of annual reports is conducted using software named R. To simplify the problem, we try to predict the companies’ corporate governance qualifications using text mining. K Nearest Neighbor, Naive Bayes and Decision Tree machine learning algorithms were used.
Findings: Our analysis illustrates that K Nearest Neighbor has classified the highest number of correct classifications by 85%, compared to 50% for the random walk. The empirical evidence suggests that text mining can be used by all stakeholders as a financial analysis method.
Practical Implications: Combining financial statement analyses with financial reporting analyses will decrease the information asymmetry between the company and stakeholders. So stakeholders can make more accurate decisions. Analysis of non-financial data with text mining will provide a decisive competitive advantage, especially for investors to make the right decisions. This method will lead to allocating scarce resources more effectively. Another contribution of the study is that stakeholders can predict the corporate governance qualification of the company from the annual reports even if it does not include in the Corporate Governance Index (CGI).
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Desirée H. van Dun and Maneesh Kumar
Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech…
Abstract
Purpose
Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech initiatives is key to successful Industry 4.0 technology adoption, but few studies have examined the determinants of employee acceptance. This study, therefore, aims to explore how managers affect employees' acceptance of Industry 4.0 technology, and, in turn, Industry 4.0 technology adoption.
Design/methodology/approach
Rooted in the unified theory of acceptance and use of technology model and social exchange theory, this inductive research follows an in-depth comparative case study approach. The two studied Dutch manufacturing firms engaged in the adoption of Industry 4.0 technologies in their primary processes, including cyber-physical systems and augmented reality. A mix of qualitative methods was used, consisting of field visits and 14 semi-structured interviews with managers and frontline employees engaged in Industry 4.0 technology adoption.
Findings
The cross-case comparison introduces the manager's need to adopt a transformational leadership style for employees to accept Industry 4.0 technology adoption as an organisational-level factor that extends existing Industry 4.0 technology user acceptance theorising. Secondly, manager's and employee's recognition and serving of their own and others' emotions through emotional intelligence are proposed as an additional individual-level factor impacting employees' acceptance and use of Industry 4.0 technologies.
Originality/value
Synthesising these insights with those from the domain of Organisational Behaviour, propositions were derived from theorising the social aspects of effective Industry 4.0 technology adoption.
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Beybala Timur, Yasin Emre Oğuz and Veysel Yilmaz
Mobile food ordering apps (MFOAs) became more popular, thanks to social distancing regulations during the COVID-19 outbreak. People started to order food using these apps more…
Abstract
Purpose
Mobile food ordering apps (MFOAs) became more popular, thanks to social distancing regulations during the COVID-19 outbreak. People started to order food using these apps more than usual. As customers seem happy to use these apps, there is always a risk of spreading infection. These facts inevitably shape customer intentions. Therefore, this study aims to empirically assess the MFOA user dining attitudes (DA), e-satisfaction (ES) and continuance intention (CI) regarding the perceived risk (PR) during the COVID-19 pandemic in Türkiye.
Design/methodology/approach
This study used structural equation modelling (SEM) in the expectation confirmation theory and technology acceptance model. Data collection instruments were derived from existing literature, and 625 questionnaires were collected via online surveys. The data collection instrument consisted of eight parts that aimed to gather information about participants’ demographics, expectation confirmation, perceived ease of use, perceived usefulness, ES, PR and CI.
Findings
Results showed significant relationships between ES, DA, PR and CI. The most remarkable finding is that while ES influences customers to reuse MFOAs, PR causes a decrease in CI.
Originality/value
This study model broadened the existing MFOA study models by adding risk factors. Also, it made a valuable contribution to emerging MFOA literature both in Türkiye and the world.
研究目的
由于 Covid-19 爆发期间的社交距离规定, 移动订餐应用程序 (MFOA) 变得更受欢迎。 人们开始比平时更多地使用这些应用程序点餐。由于客户似乎很乐意使用这些应用程序, 因此始终存在传播感染的风险。这些事实不可避免地会影响客户的使用意愿。因此, 本研究旨在实证评估 MFOA 用户在 Turkiye Covid-19 大流行期间对感知风险的用餐态度、电子满意度和持续意图。
研究设计/方法/途径
该研究在预期确认理论和技术接受模型中使用了 SEM。 数据收集工具来自现有文献, 通过在线调查收集了 625 份问卷。 数据收集工具由 8 个部分组成, 旨在收集有关参与者的人口统计信息、期望确认、感知易用性、感知有用性、电子满意度、感知风险和持续意图的信息。
研究发现
结果显示电子满意度、用餐态度、感知风险和持续意愿之间存在显着关系。 最显着的发现是, 虽然电子满意度会影响客户重复使用 MFOA, 但感知到的风险会导致持续意愿下降。
研究原创性/价值
该研究模型通过添加风险因素拓宽了现有的 MFOA 研究模型。 此外, 它还为土耳其和世界新兴的 MFOA 文献做出了宝贵贡献。
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Ryan Varghese, Abha Deshpande, Gargi Digholkar and Dileep Kumar
Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has…
Abstract
Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.
Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.
Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.
Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.
Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.
Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.
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Sara R. Jaeger, Duncan Hedderley and Halliday J.H. MacFie
To help further our understanding of how keymethodological issues in conjoint analysis influence outcomes, a choice‐based conjoint study measuring consumer preferences for…
Abstract
To help further our understanding of how keymethodological issues in conjoint analysis influence outcomes, a choice‐based conjoint study measuring consumer preferences for pre‐packed apple selection packs was conducted. The role of stimuli presentation format was considered by comparing the performance of physical prototype stimuli and realistic pictorial representations. This indicated no substantial differences in the choice decisions made using the two presentation formats and suggested that photographic images may be used instead of prototype stimuli. A second issue pertained to the need for training and warm‐up exercises prior to the actual conjoint choice task. While this indicated some differences in choice strategies, a significant improvement in internal validity of choice decisions made with and without training was not achieved. One possible explanation for this finding may be that respondents made choices between apple products, a product category for which decision strategies are likely to be stable and well‐developed.