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Although high-order smooth reproducing kernel mesh-free approximation enables the analysis of structural vibrations in an efficient collocation formulation, there is still a lack of systematic theoretical accuracy assessment for such approach. The purpose of this paper is to present a detailed accuracy analysis for the reproducing kernel mesh-free collocation method regarding structural vibrations.

Both second-order problems such as one-dimensional (1D) rod and two-dimensional (2D) membrane and fourth-order problems such as Euler–Bernoulli beam and Kirchhoff plate are considered. Staring from a generic equation of motion deduced from the reproducing kernel mesh-free collocation method, a frequency error measure is rationally attained through properly introducing the consistency conditions of reproducing kernel mesh-free shape functions.

This paper reveals that for the second-order structural vibration problems, the frequency accuracy orders are p and (p − 1) for even and odd degree basis functions; for the fourth-order structural vibration problems, the frequency accuracy orders are (p − 2) and (p − 3) for even and odd degree basis functions, respectively, where p denotes the degree of the basis function used in mesh-free approximation.

A frequency accuracy estimation is achieved for the reproducing kernel mesh-free collocation analysis of structural vibrations, which can effectively underpin the practical applications of this method.

The integration of e-commerce platforms and artificial intelligence (AI) into the marketing channel ecosystem is challenging the explanatory capacity of traditional channel power theories, indicating a significant yet unaddressed research gap concerning the impact of these digital entities and AI on channel power exercise dynamics. This study adopts a contingency perspective to critically revisit how e-commerce platforms exercise channel power and the ensuing effects on channel conflicts. The purpose of this study is to extend the boundaries of traditional channel power theories, enhancing their relevance in today’s digital marketplace.

Building on channel power theories, the authors developed a framework tested with survey data collected from 262 sellers. This framework incorporates three key contingent variables: inter-platform competition, AI capabilities and platform value co-creation. Regression analysis was used to perform the analyses.

This study finds that intense inter-platform competition mitigates the (positive) negative relationship between platform channel power and the exercise of (non-) coercive power. Moreover, a platform’s AI capabilities and value co-creation activities diminish the potential for channel conflicts induced by the exercise of coercive power. AI capabilities can also strengthen the negative relationship between the exercise of non-coercive power and channel conflicts.

This study contributes to the advancement of traditional channel power theories by integrating contemporary digital elements like AI and platform dynamics. This study provides theoretical and practical insights on navigating channel power in modern marketing environments, offering strategic guidelines for optimizing channel relationships.

This article presents a comprehensive analysis of innovation in micro, small and medium enterprises (MSMEs) in India, focusing on the barriers and facilitators within their internal and external ecosystems.

A self-administered questionnaire was used to collect data from 1430 MSMEs across India, employing Structural Equation Modeling (SEM) to analyze the relationships between internal and external factors and innovation adaptation.

The findings indicate that factors such as top management and organization structure, communication, technological capability and adaptation and organizational culture have a positive impact on innovation adaptation within the internal environment. Conversely, employee and market orientation, as well as financial factors, have a negative influence. Regarding the external environment, industry and competitive analysis, internationalization and partner alliances were found to positively affect innovation adaptation, whereas the country's infrastructure and policies had a negative impact.

The study emphasizes that MSMEs have the potential to leverage their internal and external environments to foster innovation within their organizations.

The topic of parent migration and its effects on the family environment has become a focus of moral dilemmas in East Europe for the last three decades. Children have been portrayed as social orphans and parents working abroad as neglectful parents. Today, with more evidence from research and experience, the impact of parental migration is much more comprehensive and nuanced, recognising its noxious or even harmful but also possibly empowering effects. This chapter reflects on the involvement of left-behind adolescents as co-researchers in a study of transnational families. It acknowledges the agentic role of children (often automatically labelled as victims of neglect), amplifies their voices to inform existing data on the impact of parents' departure to work abroad and identifies directions for intervention that might strengthen families.

The research is an integral part of CASTLE – Children Left Behind by Labour Migration, an ongoing project (June 2021–December 2023).¹ This chapter presents the research collaboration experience with 12 co-researcher adolescents with previous left-behind experiences, originating from Moldova and currently residing in Romania. The co-researchers participated in all stages of the research process: training, design of data collection, recruitment of research participants, data analysis and dissemination of results. Taking co-researcher roles had an empowering effect on adolescents, who learnt how to express their views on the topic, voiced their experiences about the emotional costs of being left behind by their parents and reflected on sensitive issues like separation of family members and violence in the family.

In recent years, author and document citation and co-citation analyses have often been applied to map the “intellectual structure” of different scientific fields, including management and international business. However, the technique of bibliographic coupling between scientific documents, which seeks to identify active research fronts in a scientific field or discipline, has been less commonly used. This study utilized this technique to identify and visualize the research fronts in the context of papers on emerging markets multinational enterprises (EM-MNEs) recently published in a wide variety of journals. The aim is not only to complement and expand the results obtained in prior studies that have used other types of systematization, such as qualitative content analysis methodology but also to propose avenues for future research.

The primary databases utilized to carry out the present research work – both comprised in the Web of Science™ (WoS) Core Collection – were: the Social Sciences Citation Index® (SCI) developed by the Institute for Scientific Information (ISI) and the Emerging Sources Citation Index. A total of 496 “peer-reviewed journal articles” published between 2014 and December 30, 2019 were retrieved. With regards to the methodology, bibliometric methods were utilized, as well as social network analysis (SNA).

Particularly, the analytical techniques employed – adopting a “quantitative” method of a deductive character – allowed the identification of the most active research “fronts” in international research related to the topic under analysis: the phenomenon of EM-MNEs.

The present study has several limitations resulting from the utilization of bibliometric methods applied in the analyses performed.

The authors believe that this research is of value for future researchers since it allows the identification of research “fronts,” which shape the vanguard of knowledge and reveal current trends and future directions in the area under examination.

This paper aims to argue that markets need a foundation of morality to promote the long-run success of an economy.

Three types of ethical theories are discussed and compared with what the sacred scriptures of Islam and Christianity say and with what economic theory says. Examples from China are provided.

Markets need morality.

There are more religions in the world than just Islam and Christianity; however, space limitations force me to only consider those two religions. Furthermore, there are more countries in the world than just China. However, space limitations force me to only pull examples from China.

Economists should recognize that markets need morality, and they should start teaching that to their students.

If markets are built on a foundation of ethics, then society prospers. In the absence of that foundation, societies falter. When a government, business and religious institutions see each other as complementary forces, then ethics can evolve.

The author knows of no other studies that explain the three types of ethical theories, compares those theories to what the sacred scriptures of Islam and Christianity say and to what economic theory says, and then uses examples from China to illustrate the need for morality.

To what extent Mikhail Gorbachev′s Glasnost and Perestroika anticipate the paradigm of a socialist market economy, is investigated. Gorbachev, like China′s Deng Xiaoping, realises that socio‐economic theories which abstract themselves from the observations and needs of daily life have little relevance. That is, a meaningful paradigm has to pay attention to society′s values, especially to the interrelationship of personal initiative, morality, law, government and public policy. Hence, Gorbachev advocates the establishment of more favourable socio‐economic conditions to lay the foundation for a “functional socialist social market economy”, however defined, in the Soviet Union.

The purpose of this paper is to investigate the organizational readiness perspective of adopting artificial intelligence and big data analytics in the textile and garment industry in Bangladesh along with identifying the associated factors.

The research uses a qualitative method using semi-structured interviews with representatives of business organizations and stakeholders of Bangladesh’s textile and garment industry.

The research reveals that the textile and garment industry in Bangladesh currently has low organizational readiness to adopt artificial intelligence and big data analytics. This is due to moderate knowledge- and leadership-readiness along with low human-, finance- and engagement-readiness of most of the business organizations. The readiness aspects interplay with each other and need to be improved holistically.

Considering the significant global and national importance of Bangladesh’s textile and garment industry, gaining insights into the industry’s current state of readiness for adopting artificial intelligence and big data analytics would offer valuable assistance to both national and global economies and may enhance economic outcomes.

Since no exploratory study was conducted to understand the organizational readiness aspects of adopting artificial intelligence and big data analytics of the globally significant textile and garment industry in Bangladesh, the paper analyzes five key aspects of such readiness and offers a basis for conducting similar studies in other emerging economies.

Findings from a comparative qualitative study with parents in the USA and China increase the understanding of experiences of adults with autism in both countries.

Semi-Structured interviews were conducted with families in the USA and in China. In total, 18 families participated in the study – 7 in the USA, 11 in China.

Analysis of the comparative data led to the emergence of three overarching themes, expressing both similarities and differences in experiences: 1) transition to adult services plays out differently in the two nations, 2) parent advocacy and efforts in supporting and securing services for their children are strong in both countries but are also defined by the variability in access to services and 3) due to the scarcity of adult services in their country, Chinese parents express significantly more worries about their own aging and mortality as compared with USA parents.

Practical implications and directions for future research are discussed.

By examining the experiences of families of adults with autism in the USA and China, the research reveals themes that would not be visible in a single-nation study.

This study attempts to gain insight into what factors influence individual behavior towards the adoption of telemedicine application during coronavirus disease 2019 (COVID-19) pandemic. The research model incorporates two well-known theories namely the extended unified theory of acceptance and use of technology (UTAUT2) and DeLone and McLean information success model to examine individual behavior towards the adoption of telemedicine application.

The research design of this study is based on quantitative research approach. During research survey, 350 valid responses were received from Pakistani citizens and examined to understand citizen's behavior towards the adoption of telemedicine applications. The research model was empirically tested with the latest statistical approach namely variance-based structural equation modeling (VB-SEM).

The results of the structural equation modeling have revealed that altogether performance expectancy, social influence, effort expectancy, facilitating condition, habit, hedonic motivation, price values, information quality, system quality and service quality explained 77.9% variance in determining user behavior towards adoption of telemedicine application. The predictive relevance of the research model was found substantial in measuring user behavior to adopt telemedicine applications. The research framework is further extended with moderating role of perceived severity between the relationship of user intention and actual usage behavior. Results confirmed that the positive relationship between intention to adopt telemedicine health application and usage behavior will be stronger when perceived severity is higher.

Theoretically, this study integrates extended UTAUT2 and DeLone and McLean information success model and contributes to e-health literature. Practically, this research suggests that by improving user performance expectancy and effort expectancy, managers and healthcare professionals can boost user confidence towards the adoption of telemedicine applications.

This study is unique as it integrates the extended UTAUT2 with DeLone and McLean information success model and perceived severity to investigate user behavior towards adoption of telemedicine application during COVID-19 pandemic. Additionally, the integration of theories contributes to information system literature in the context of the adoption of telemedicine applications.