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This paper, based on the 2022 Master Class delivered at the 50th National Economic Meeting organized by ANPEC, discusses how post-Keynesian macroeconomics and New Developmentalism complement each other to understand middle-income economies' development in financial globalization. It summarizes my academic reflection about the advance in post-Keynesian thinking to develop macroeconomics for peripheral middle-income economies.

As part of this reflection, I first bring up the idea of a developmental convention and, next, how peripheral financialization impacts the elaboration of this convention. Given the asymmetric configuration of the international financial system and the context of hierarchical currencies, I discuss the challenge of overcoming underdevelopment in peripheral economies. The post-Keynesian macroeconomics and advances in the structuralist debate provide the analytical tools to understand how peripheral economies develop virtuous or vicious growth cycles. At the end of the paper, I present some comments on the stagnation of the Brazilian economy.

The growth strategy with foreign savings does not provide the conditions for middle-income economies to operate with sufficient economic policy autonomy to promote productive transformation. To this end, a developmental convention should replace the neoliberal convention that has dominated since the 1970s.

The dynamics of peripheral, middle-income economies, often influenced by international liquidity flows, are a crucial area of study. This research underscores the importance of understanding these dynamics, as it forms the basis for economic policy recommendations. The paper also highlights the inadequacy of the growth strategy with foreign savings in the current configuration of the international financial system, emphasizing the need for middle-income economies to operate with greater economic policy autonomy to foster productive transformation.

In this article, the research objective is to empirically investigate the effect of the adoption of the Brazilian instant payment system, Pix, on the local credit market structure and the diversification of the banking system in Brazilian municipalities.

By analyzing the data, in this study, we compile and align data from supervisory and public sources, covering the period from 2019 to 2022 in Brazil. As of 2014, Brazil was comprised of 5568 municipalities distributed across five regions: North (450 municipalities), Northeast (1792), Midwest (467), Southeast (1668) and South (1191), according to the Brazilian Institute of Geography and Statistics (IBGE). Our analysis relies on the volume and quantity of Pix to the outstanding credit operations in Brazil.

This article provides evidence that the widespread adoption of Pix has impacted the financial structure of municipalities. This analysis of banking concentration in the country and municipalities, based on banking relationships, helped us assess whether the adoption of Pix had any correlation with the increase in credit lines. Overall, the results from the statistical tables suggest that the adoption of Pix may be having a positive impact on the local credit market structure.

The originality contribution of the study is to initiate an investigation into the impact of this instant payment system, Pix, on the Brazilian reality. Pix was launched in 2020, amid the COVID-19 pandemic, and had significant numbers, such as over 61% of the adult population having at least one Pix key registered in a little over a year; about 100 million people made at least one payment with Pix; and more than 1.4 billion transactions per month, with 72% between individuals, as presented by the REB 2021.

This study combines the TAM and UGT frameworks to investigate how Vietnamese students' views of ChatGPT and intrinsic needs affect their intentions to use it for education (via variables including perceived ease of use, perceived usefulness, novelty, information seeking and academic content creation). We will employ TAM theory (Davis, 1989) and UGT theory to elucidate university students' motivations for utilising ChatGPT in Vietnam. Simultaneously, we aim to address the limitation stemming from data uniformity. Our research will make a substantial contribution to the understanding of researchers regarding the use of ChatGPT and its varied consequences as it grows and develops.

This study was conducted at a private university in Vietnam with an estimated population of 15,000 students. One of Vietnam’s top private information technology institutions requires its students to use a variety of information and communication technologies (ICTs) on a regular basis to facilitate and enjoy their academic pursuits (Ngo, 2024; Nguyen). Students who are familiar with ChatGPT and have access to it for educational purposes are the ones that were chosen. This research is a quantitative study that utilises primary data through a survey method. Participants answered a questionnaire online through the Google Form platform sharing via social media platforms from October to December 2023. The questionnaire was divided into two sections: the first contained screening questions and demographic information and the second had five-point Likert-scale questions that measured the study’s components. Two screening questions are used to separate out the intended responders. (i.e. “I have heard the name ChatGPT” and “I know about ChatGPT”) were set to find whether the participants had any knowledge of ChatGPT. If participants were unaware of ChatGPT, their responses were not included in the study. A total of 283 responses were received. The participant’s demographic information is shown in Table 1. It is believed that a sample size of more than 200 provides adequate statistical power for data analysis in structural equation modelling. It is evident that the 283-sample size in this study is adequate to evaluate the research hypothesis and the fitting model. 42.9% of the 283 research samples were made up of men, while 57.1% were women. Business administration accounted for 40.1% of survey respondents, followed by information technology (25.2%) and English language (14.5%). The average ChatGPT usage time of respondents was 56 min in a single use. The study sample’s average age is 20–72 years old.

The present study contributes to the existing AI chatbot literature in the educational industry in several ways. First, this study addresses a gap in the literature by investigating the factors that influence students’ ITU ChatGPT for educational purposes in Vietnam. Using the extended model, we investigated factors influencing students’ intentions to use ChatGPT. It integrates three motive factors of the UGT (ACT, IS and N) with the core factors of TAM (PeoU and PU). The integrated framework’s findings indicate that in a Vietnamese educational setting, ChatGPT is a novel technology that should be considered in conjunction with PU and PEoU.

First, only Vietnamese students make up the research sample. To increase the relevance of the findings, it is advised that future research look at the study model in various geographic regions. Second, the present investigation’s constraints arise from the lack of clarity about the Chat GPT version utilised by the respondents, specifically whether it was the free or premium edition. Furthermore, the limited duration of the survey presents an obstacle to gathering thorough data. Due to their reliance on the particular features and functionalities of the Chat GPT version used, these restrictions may have an effect on the researcher’s objectivity. Furthermore, the limited survey time may curtail the coverage of the collected answers, particularly considering that our survey predominantly focuses on business administration students, thus limiting the diversity and richness of the gathered data. We recommend that future studies should conduct comparative research between different versions of GPT Chat, including free and paid variants that can provide valuable insights into potential differences in performance and results. Such analysis can provide a deeper understanding of the strengths and limitations of different GPT Chat versions. Third, because the study focused on behavioural intention, actual usage and post-usage behaviour may not be covered by the findings. To gain a deeper understanding of users' actual behaviour, we suggest doing research on their usage and post-usage behaviours.

The findings will assist service providers and legislators in determining critical variables and influencing students' incentives to use ChatGPT in educational settings that use constructivist teaching methods. As a result, the information will assist service providers in creating AI chatbots that are more user-friendly, visually appealing, efficient, safe and convenient for education. Governments, in conjunction with service providers, have the potential to significantly accelerate the adoption of AI-based chatbots by highlighting their ethical and sustainable use. The findings demonstrate that students' ITU towards ChatGPT is substantially impacted by PU and PEoU. It is recommended that service providers emphasize the advantages and ease of use of AI chatbots in order to draw new clients. Additionally, in order to promote ChatGPT or related technologies, marketers should concentrate on raising the technology’s perceived novelty value. This is because people are open to new technologies as long as they believe they are interesting and innovative.

ChatGPT is an advanced AI-powered chatbot that has the potential to advance and revolutionize the learning and teaching process. This study attempted to look at the elements that lead students to want to use ChatGPT from an academic standpoint by combining the UGT and TAM. For practitioners, academics and educators, the findings provide a solid knowledge of and encouragement for the sustainable use of such AI tools. Despite having important practical consequences, the study contains a number of limitations that indicate possible research gaps that should be filled by further investigation.

Carbon emissions commonly serve as an indicator for environmental friendliness, and so more and more carbon emission calculators (CECs) are offered that allow an estimation of the environmental footprint of freight transport operations. Unfortunately, their exact measurement is challenging due to the availability or poor quality of necessary input data and a multitude of possible calculation methods that may result in highly inaccurate to very misleading figures.

A structured online search was conducted to identify suitable online carbon emission calculators (OCECs) for further assessment in the form of a benchmark case that includes different modes of transport from road and rail to air and sea between China and Europe. Further comparison resulted in a ranking of OCECs along the categories of transparency (routing system, data sources and calculation method), completeness (input options) and accuracy (data output).

Different predefined inputs and calculation methods employed by the OCECs assessed inevitably result in a wide spread of more or less reliable carbon footprint measurement results.

All potential users of CECs, including policymakers, actors from the transport industry and other stakeholders, are well advised to question greenhouse gas (GHG) emission statements that are not backed by transparent procedures and internationally recognized calculation standards.

This study, including a benchmark case and a ranking, offers a guideline for potential users of CEC to avoid major pitfalls coming along with the present carbon footprint measurement of freight transport operations.

The a priori identification and development of army personnel competencies are necessary to enable effective and efficient responses to rapidly changing climate conditions. Accordingly, this study aims to identify the performance requirements of a military flood responder and the competencies (knowledge, skills and abilities) required to perform it.

Using an abductive approach, the authors conducted both secondary and primary research to generate a validated framework of performance criteria and competencies for army personnel responding to floods. This literature review integrated both the peer-reviewed academic literature and public sector grey literature. Using the critical incident technique, the authors then conducted semi-structured interviews with 15 members of the Canadian Armed Forces (CAF) who had previously been tasked with flood response operations. Participants were asked about the tasks required while conducting flood response operations. Interview transcripts were then content analysed to identify themes regarding those tasks, and the competencies needed to perform those tasks were then extracted and contrasted with the literature review findings. Inter-rater reliability for the analysis was established via iterative discussion between the two co-authors.

The primary data reinforced and expanded the list of performance expectations that the authors deductively identified from the integrated literature review, adding granularity to each. It also identified competencies (including both hard and soft skills) and highlighted previously neglected contextual antecedents of military flood response effectiveness.

though knowledge saturation was achieved from the 15 interviews conducted, further research with larger samples could more deeply ground the evidence discovered in this study. Nevertheless, the competencies identified in this paper could serve as a starting guide to staffing and/or training interventions targeted at improving these competencies for personnel responding to flood scenarios.

The theoretical findings also have immediate practical relevance to training for flood response operations. In particular, the subtle challenges in competency crossover from military operations to flood response operations may facilitate not only more efficient, targeted training (that could improve the effectiveness of army personnel involved in humanitarian roles), but could be applied to the selection of army personnel as well. This study may also help provincial/municipal operators and emergency planners by better communicating the strengths and limitations of army personnel in addressing civilian military cooperation for humanitarian operations. Thus, the findings of this research study represent an important first step in prompting attention to the strategic human resource planning studies required to make all responders more efficient and effective in their respective division of labour within the humanitarian domain.

Peering a little beyond these research findings, human-induced climate change is expected to continue increasing the frequency of such events (IPCC, 2021), and a timely, national force is likely to be increasingly required for Canadians impacted by major disasters stemming from natural hazards when local resources become overwhelmed. Yet, there is some concern from the CAF that increasing responsiveness to disaster operations will affect their military readiness (Leuprecht and Kasurak, 2020). One can indeed envision a paradox whereby the CAF is both a “force of last resort” while increasingly becoming a “first choice for domestic disaster and emergency assistance”. The practical implications from this research also suggest that military personnel, while fully capable of successfully conducting flood response operations, may become overburdened and less able to adopt yet greater capacity and training for other additional humanitarian work. Nevertheless, the competencies highlighted by participants can help inform the next flood response operation in Canada.

Most literature in the field of emergency response focuses on cooperation between civilian and military resources and other strategic-level themes. The findings address critical granularity missing at the operational and tactical levels of humanitarian assistance and disaster relief research. The authors also draw implications beyond the military context, including for local/regional governmental players (operators and emergency planners) as well as for volunteers in flood response roles.

This exploratory research aims to unravel how Chinese international students form their decisions regarding the school-to-work transition (sometimes also referred to as the university-to-work transition) when studying abroad.

The authors use the concepts of school-to-work transition and cultural approaches to investigate how Chinese graduate students make career decisions to navigate the school-to-work transition in the context of international mobility. The authors' empirical study is based on 30 semi-structured interviews conducted with Chinese graduate students studying in the Netherlands.

The authors discovered four patterns with two major subgroups among Chinese students studying in the universities in the Netherlands based on their initial intentions: return-return, open-return, open-stay and stay-stay. These patterns made sense when navigating the school-to-work transition: participants experienced varied international experiences, cultural perceptions and acknowledgment influences when enhancing employability and shaping their career decisions. Participants in the return-return and stay-stay groups indicated strong resilience and consistency in achieving their goals and strongly focused on long-term objectives. However, participants' open-return decision demonstrated a thoughtful alignment of personal goals and knowledge of the possible beneficial influence they may have in their home country. Open-stay participants utilized the overseas study opportunity to finalize their decisions and increase their employability in the local labor market, thereby creating a transition from university to work in the host country.

The authors highlight the way Chinese graduate students manage their international experience and provide novel insights into the role played by the cultural characteristics of their home country and host country.

This study aims to extend the cognitive appraisal theory by developing and validating a conceptual framework to illustrate how travelers' behavioral intention is generated via a multi-stage evaluation of health-related variables.

SEM and moderator analysis were conducted to examine the theoretical framework (post-intervention event travel intention) and to investigate how the appraisal process differs across travelers with various attitudes toward vaccination.

This study found that cruise travel intention was positively influenced by the perceived hedonic value and perceived trustworthiness and negatively influenced by perceived infection risk. Furthermore, whereas perceived hedonic value, perceived trustworthiness and perceived risk of infection were all predicted by crisis management, the dimensions of crisis management operated differently. In addition, vaccination attitudes amplified the unfavorable effect of perceived risk on intention.

Drawing on the CAT, this study developed and validated a conceptual framework to integrate crisis management with customers' behavioral intentions. This study extends existing cruise travel intention theory by demonstrating how post-pandemic travelers' behavioral intention is generated via a multi-stage appraisal-reappraisal process based on the evaluations of infection risks and cruise line crisis management.

Generative artificial intelligence (GenAI) has progressed in its ability and has seen explosive growth in adoption. However, the consumer’s perspective on its use, particularly in specific scenarios such as financial advice, is unclear. This research develops a model of how to build trust in the advice given by GenAI when answering financial questions.

The model is tested with survey data using structural equation modelling (SEM) and multi-group analysis (MGA). The MGA compares two scenarios, one where the consumer makes a specific question and one where a vague question is made.

This research identifies that building trust for consumers is different when they ask a specific financial question in comparison to a vague one. Humanness has a different effect in the two scenarios. When a financial question is specific, human-like interaction does not strengthen trust, while (1) when a question is vague, humanness builds trust. The four ways to build trust in both scenarios are (2) human oversight and being in the loop, (3) transparency and control, (4) accuracy and usefulness and finally (5) ease of use and support.

This research contributes to a better understanding of the consumer’s perspective when using GenAI for financial questions and highlights the importance of understanding GenAI in specific contexts from specific stakeholders.

In the Fall of 2019, Marietta College and Marietta City Schools, in Marietta, Ohio, piloted a program to improve literacy knowledge and pedagogy through completing LETRS training, a two-year literacy professional development based on the science of reading, as peers.

This project was aligned to effective professional development research that states better trainings are content-specific, allow support and collaboration and are ongoing throughout the school year (Blank and de las Alas, 2009; Darling-Hammond, Hyler, and Gardener, 2017) and respect participants work/life schedules (Bigsby and Firestone, 2017).

Some benefits of this collaboration were that teachers, college faculty and teacher candidates were able to communicate more effectively about literacy because we all had shared background knowledge and spoke the same language when it came to literacy. We were also able to make more meaningful clinical experiences for our teacher candidates because we created a stronger connection between the knowledge and pedagogy taught in students’ literacy courses and the practices they saw in real classrooms. Inservice teachers saw the college faculty and teacher candidates as strong partners, which greatly strengthened our clinical preparation.

The paper includes implications for the development of stronger partnerships between teacher preparation program faculty and school partnership faculty and more authentic and meaningful clinical experiences for teacher candidates.

This project shows how meaningful partnerships and clinical experiences can be created when partnership faculty are seen as peers.

The purpose of this paper is to explore networked business models on a nascent market for a sustainable innovation.

The study takes a qualitative approach through a comparative case study of three solar photovoltaic (PV) parks in Sweden. Data was collected from 14 interviews with multiple supply chain and network actors as well as secondary data. Industrial marketing and purchasing is applied for theoretical framing.

The study demonstrates transactional, relational, environmental and social drivers for participating in the network. The study reveals the duplicity of the nascent market, which encourages supply chain actors to develop their individual business models to take a larger market share or become future competitors to current collaborators. On the nascent market with few developed regulations, the network enables actors to influence regulations on local and regional levels.

The study is limited to the nascent solar PV industry in Sweden, which is characterized by institutional turbulence, market uncertainties and few established supply networks.

Practitioners need to consider multifarious drivers for participating in networked business models, where the economic driver may be the least motivating.

This study provides several multiactor business models and classifies them into specific applications and general applications. The study provides unique insight into the complexity of interactions among supply chain actors in networked business models on a nascent market for sustainable innovation. Due to the scarcity of available partners on the nascent market, actors need to look beyond their on-going relationships and their network horizon, or actors’ roles evolve to include activities that was not part of their individual business models.