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The purpose of this study is to investigate the intergranular corrosion (IGC) susceptibility of a nitrogen-containing austenitic stainless steel QN2109. The intergranular corrosion (IGC) susceptibility of a nitrogen-containing austenitic stainless steel QN2109 was investigated.

The double-loop electrochemical potentiodynamic reactivation (DL-EPR) tests were carried out. Scanning electron microscopy and atomic force microscopy were used to characterize the microstructure.

The optimized test condition for QN2109 was 1 M H₂SO₄ + 0.01 M NH₄SCN at 40°C. The nose temperature of the temperature–time–sensitization (TTS) curve of QN2109 plot was approximately 750°C. Moreover, the IGC susceptibility started to appear at approximately 120 min. The Cr-depletion zone of QN2109 was generated by the formation of M23C6 rather than by the addition of nitrogen. The depth–width ratio of the grain boundaries after the DL-EPR tests decreased as the aging temperature increased. The degree of Cr depletion and size of the Cr-depletion zone at the grain boundary were reflected by the degree of sensitization and depth–width ratio, respectively.

The optimized test condition for DL-EPR tests of a nitrogen-containing austenitic stainless steel QN2109 was investigated. The TTS curve of QN2109 was first plotted to avoid IGC failure. The morphology of the Cr-depletion zone was reflected by the depth–width ratio.

This study aims to study the effect of Sn on the corrosion behavior of weathering steel (WS) in a simulated tropical marine atmosphere.

Indoor alternate immersion tests, electrochemical measurements and real-time current-monitoring technology based on the galvanic corrosion principle were used and the scanning electron microscope, X-ray diffraction, X-ray photoelectron spectroscopy and electron probe microanalyzer were used to analyze the morphology and component of the rust layer.

The results indicated that Sn has a positive influence on the corrosion process. Sn participated in the composition of the rust layer in the form of SnO₂ and is enriched in the inner rust layer. SnO₂ participated in the coprecipitation process with iron oxides and oxyhydroxides, which promoted further transformation of γ-FeOOH to α-FeOOH. As a result, the rust layer of Sn-containing steel was continuous, compact and effectively blocked the invasion of aggressive Cl⁻. Therefore, the additive of Sn enhanced the corrosion resistance of WS in a simulated tropical marine atmosphere.

The corrosion behaviors of WS were researched by the real-time current-monitoring technology which was rarely used.

This paper aims to examine the effect of differential leadership on organizational corruption by developing a measure of organizational corruption and proposing a moderated mediation model. The model focuses on the mediating role of moral disengagement underpinning the relationship between differential leadership and organizational corruption, and the moderating role of organizational justice in influencing the mediation.

The authors collected 210 responses from online participants with full time work experience and 57 MBA students answered the survey offline.

Results showed that differential leadership was positively associated with organizational corruption. Furthermore, moral disengagement fully mediated the relationship between differential leadership and organizational corruption. Besides, distributive justice negatively but procedural justice positively moderated the indirect effect of moral disengagement.

Testing the moderated mediation model helps to advance the theoretical understanding of the mechanisms that underlie the effect of differential leadership on organizational corrupt behavior.

This empirical study provides preliminary evidence of the mediating role of moral disengagement in the positive relationship between differential leadership and organizational corruption. The mediated moderation also extends the finding by adding organizational justice as the moderator to explain how the effect of differential leadership on organizational corruption. Finally, this study provides initial evidence for organizational corruption measure.

According to the fact that the single function transformation which can both reduce the class ratio dispersion and keep the relative error no enlargement after the inverse transformation does not exist, this paper provides the separable binary function transformation F(x(k),k)=f(x(k))⋅g(k). The authors select the appropriate f(x(k)) and g(k) to get F(x(k),k)=f(x(k))⋅g(k). The sequence {F(x(k),k)}k=1n can not only improve the modeling accuracy but also ensure that the inverse transformation relative error has no enlargement.

First of all, to meet that the sequence reduces the class ratio dispersion after binary function transformation, the sufficient and necessary condition of binary function transformation with reduced class ratio dispersion is obtained. Secondly, to meet the condition that the inverse transformation relative error is not enlarged, the necessary condition of separable binary function transformation is obtained respectively for monotonically increasing and monotonically decreasing function f(x). Finally, the feasibility and correctness of this method are illustrated by example analysis and application.

The sufficient and necessary condition of binary function transformation with reduced class ratio dispersion and the necessary condition of separable binary function transformation with the inverse transformation relative error no enlargement.

According to the properties of separable binary function transformation provided in this paper, the grey prediction function model is established, which can improve the modeling accuracy.

This paper provides a binary function transformation, and researches the sufficient and necessary condition of binary function transformation with reduced class ratio dispersion and the necessary condition of separable binary function transformation with the inverse transformation relative error no enlargement. It is easy for scholars to carry out the pretest before selecting the separable binary function transformation. The binary function transformation is the further extension of single function transformation, which broadens and enriches the choice of function transformation.

This research helps firms pursue an open innovation strategy but want to minimize competitive pressure from other external entities. A theoretical framework is constructed to analyze the impact of openness on innovation performance, exploring different effect of firms' external search channels.

This paper employs a stepwise hierarchical regression approach to assess the effect of openness on technological innovation considering the role of information technology adoption and political ties. The effect is conducted using a large-scale sample of 1,073 Chinese manufacturing firms over the period 2011–2013 as empirical research objects.

There are two stages of the open technological innovation process while the information technology (IT) adoption and political ties are the key consideration in emerging markets. Openness is curvilinearly (taking an inverted U-shape) related to innovation performance. Both information technology adoption and political ties generally help firms to turn broadly sourced external knowledge into technological innovation performance. This will stimulate “one plus one is greater than two” effect not only in the process of achieving performance goals, but also in the process of technological innovation.

This quantitative research illustrates the importance relationship between firms' open behaviors and technological innovation performance in emerging markets. It helps us understand firms' current constrains of open strategy of technological innovation and helps domestic or foreign investors to make strategic collaboration choices in emerging economies according to the degree of openness, informatization level, political connections, which is equally important for research and practice.

Innovative modern technologies are utilised in the hospitality and tourist industry to attract prospective consumers. Travel vlogs have emerged as a type of visual travel blog which includes information regarding tourist destinations, accommodation, cuisine, touristic activities, mode of accessibility, etc. The current study aims to investigate the influence of vlogger credibility on triggering the tourist intention to visit an eco-tourism destination.

The present study is a quantitative study, and it was conducted by surveying 218 respondents. A structured, close-ended and self-administrated questionnaire was used to collect data from the respondents.

The findings indicated that vlogger trustworthiness, expertise and attractiveness significantly impact Bangladeshi tourists' intention towards visiting an eco-tourist destination.

The present study has several theoretical and practical contributions. Theoretically, the research framework illustrated how the vloggers' trustworthiness, expertise and attractiveness on Bangladeshi tourists' visit intention to eco-tourist destinations. Practically, tourism industry practitioners, particularly destination marketers, will get benefit from the present study.

The last few years have witnessed massive artificial intelligence (AI) and gaming adoption that has navigated the emerging markets. Moreover, according to the WOG summit (world government summit report, by Nielsen) 2020 reports, AI with gaming mechanisms are expected to enrich marketing services in the coming future in the emerging markets. Countries such as India, China and South Korea contribute significantly to this area, and recent forecasting allows the need to increase in emerging markets. Similarly, these countries have a maximum number of youth gamers and AI-driven technology adopters. The adoption of AI-driven technologies and amplification of gamification in marketing services are new phenomena. Moreover, gaming and AI dynamics are relatively new in emerging countries and need greater attention. Thus, this book chapter proposes a dyad model that would explain users' and companies' perspectives to understand the role of AI and gamification for the emerging markets. The chapter will explain how AI-driven gamification helps the users of emerging markets. The chapter will also illustrate how companies in emerging markets use AI for gamification. Therefore, the dyad model would also comprehend the gap, opportunities and challenges in this area and the subsequent strategies to help all the stakeholders.

This chapter provides an overview of the strategic implications of chatbot use and implementation, including potential applications in marketing, and factors affecting customer acceptance. After presenting a brief history and a classification of conversational artificial intelligence (AI) and chatbots, the authors provide an in-depth review at the crossroads between marketing, business, and human–computer interaction, to outline the main factors that drive users' perceptions and acceptance of chatbots. In particular, the authors describe technology-related factors and chatbot design characteristics, such as anthropomorphism, gender, identity, and emotional design; context-related factors, such as the product type, task orientation, and consumption contexts; and users-related factors such as sociodemographic and psychographic characteristics. Next, the authors detail the strategic importance of chatbots in the field of marketing and their impact on consumers' perceived service quality, satisfaction, trust, and loyalty. After discussing the ethical implications related to chatbots implementation, the authors conclude with an exploration of future opportunities and potential strategies related to new generative AI technologies, such as ChatGPT. Throughout the chapter, the authors offer theoretical insights and practical implications for incorporating conversational AI into marketing strategies.

Research on the effects of feedback frequency has reported mixed findings. To tackle this problem, the current study focuses on specific feedback signs (i.e. negative feedback). By integrating the face management theory and attribution theory, this study examined the mediating effect of trust in supervisors and the moderating effect of employee-attributed performance promotion motives for negative feedback.

A field study with 176 participants and two supplemental experiments with 143 and 100 participants, respectively, were conducted to test the theoretical model.

Results revealed that the frequency of supervisory negative feedback negatively influenced employees’ trust in supervisors, which in turn influenced employees’ perceptions of feedback utility and learning performance. These indirect effects can be alleviated when employees have high degrees of performance promotion attribution for supervisor motives.

This research extends feedback research by integrating feedback frequency with a specific sign of feedback and revealing a moderated mediation effect of the negative feedback frequency.

This chapter examines how Industrial Revolution 4.0 (IR 4.0) influences shape and reshapes the tourism industry. Tourism 4.0 technology enables user engagement with a system, improvement of the real tourist experience and the development of new approaches to influence behaviour change and even long-term user transformation.

Using an in-depth review of existing data, this chapter explains IR 4.0 and its integration into the tourism industry, especially on tourist behaviour.

Although technology integrates very slowly into the tourism industry, its phase of integration, especially Industry 4.0, is highly evident. Technology proved that it could enhance products and services in tourism and with its optimal use it can sustainably integrate into the tourism industry.

Service is still the keyword for tourism, and at a certain level, services are integrated into the tourism industry for standardisation and consistency. The recent global pandemic paves the way for several alternatives to integrate technology into the services.