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Lots of successful space missions require that the maneuvering spacecraft can reach the target spacecraft. Therefore, research on relative reachable domain (RRD) in target orbit for maneuvering spacecraft is particularly important and is currently a hot-debated topic in the field of aerospace. This paper aims at analyzing and simulating the RRD in target orbit for maneuvering spacecrafts with a single fixed-magnitude impulse and continuous thrust, respectively, to provide a basis for analyzing the feasibility of spacecraft maneuvering missions and improving the design efficiency of spacecraft maneuvering missions.

Based on the kinematics model of relative motion, RRD in target orbit for maneuvering spacecraft with a single fixed-magnitude impulse can be calculated via analyzing the relationship between orbital elements, position vector and velocity vector of spacecrafts, and relevant studies are introduced to compare simulation results for the same case and validate the method proposed in the paper. With analysis of the dynamic model of relative motion, the calculation of RRD in target orbit for maneuvering spacecraft with continuous thrust can be transformed as the solution of the optimal control problem, and example emulations are carried out to validate the method.

For the case with a single fixed-magnitude impulse, simulation results show preliminarily that the method is in agreement with the method in Ref. (Wen et al., 2016), which treats the same case and thus is plausibly correct and feasible. For the case with continuous thrust, analysis and simulation results confirm the validity of the proposed method. The methods based on relative motion in this paper can efficiently determining the RRD in target orbit for maneuvering spacecraft.

Both theoretical analyses and simulation results indicate that the method proposed in this paper is comparatively simple but efficient for determine the RRD in target orbit for maneuvering spacecraft swiftly and precisely.

Our understanding of what we call “normal” in organizations has been shaken multiple times in recent years. As change is perceived as an inherent feature of routine dynamics, it is relevant to understand how change becomes established as a new normal. Therefore, the purpose of this study is to explore how change in routines takes hold as normality forms. To answer this question, the author studies the change in routines in an in-depth process case study of a higher education organization during the COVID-19 pandemic transforming its teaching model. The author’s findings show that normality formation is a dynamic process. While normality can be described as a snapshot of the current state of what is considered normal at one point in time, normality transforms in sequential waves making the overall process of normality formation pulsate. In drawing out six patterning mechanisms, the author introduces a pulsating normality as the transformative evolution of what is considered normal. This study speaks to routine dynamics literature, contributing to a better understanding of how a variation in performance becomes patterned as a sustained part of a routine.

Social media marketing has become a powerful strategic tool for many brands, but scholarly research in this domain is still in its infancy. This study aims to examine the effects of social media marketing activities on consumer online impulse buying intentions via brand resonance and emotional responses by incorporating the direct and moderating effects of social network proneness toward fashion retail brands.

By using snowball sampling, this study recruited 441 netizens (who were using fashion retail brands) and obtained their responses through an online survey. Structural equation modeling was applied to 394 responses for analysis.

The findings discovered that social media marketing activities significantly influenced brand resonance, consumer emotional responses and online impulse buying intentions. Likewise, brand resonance and emotional responses were positively associated with online impulse buying intentions and acted as decisive mediators. Social network proneness’s direct and moderating effects significantly increased consumer online impulse-buying intentions toward fashion retail brands.

This study provides recommendations to retail managers for creating and executing brand positioning, segmenting and targeting strategies to enhance consumers’ intentions for engaging in online impulsive purchases for fashion brands.

This original research contributes to the branding literature and stimulus–organism–response theory by focusing on social media marketing activities, brand resonance, emotional responses, social network proneness and consumer online impulse buying intentions toward fashion retail brands.

This study differentiates pure impulse buying behaviour from suggestive impulse buying behaviour in using mobile shopping applications (apps). This study aims to assess the moderating effects of instant discount and cashback promotional offers along with the mediating effects of impulse buying intention (IBI) and user satisfaction (US), using the app stimuli (performance expectancy, effort expectancy, layout, atmosphere, privacy and security).

The study was done in three stages: analysis of variance, followed by structural equation modelling (SEM) and paired t-tests.

The results showed that instant discounts and cashback offers are different from each other for the mediating variable IBI. The SEM results for pure impulse buying showed that, except for layout, the remaining variables have a positive relationship with IBI. For suggestive impulse buying, effort expectancy and layout were significantly related to both the mediating variables. Finally, pure and suggestive impulse buying behaviour showed significant differences.

Previous studies have looked into impulse buying in its generic sense and not through the “types” of impulse buying they were measuring. As impulse buying behaviour is a predominant theme for discussion today, marketing professionals and researchers must comprehend the impact of app stimuli in the context of select types of impulse buying behaviour.

This study examines the effects and driving mechanisms of relational bonds (i.e. financial, social, and structural bonds), live-streaming shopping atmosphere factors (i.e. suspense, entertainment, perceived crowdedness, and vicarious experience), consumer empowerment and customer commitment on consumers’ impulse consumption behavior. Additionally, the study examines the moderating influence of product involvement and collectivism.

An online survey was conducted with 665 valid respondents. The authors empirically validated the collected data through the partial least squares structural equation modeling (PLS-SEM) technique, complemented by the artificial neural network (ANN) analysis.

The results suggest that financial bonds, structural bonds, suspense, entertainment, and vicarious experience promote consumer empowerment, which in turn leads to customer commitment and impulse consumption behavior. Second, collectivism moderates the relationship between customer commitment and impulse consumption behavior.

This study provides empirical evidence that relational bonds and live-streaming shopping atmosphere factors play predictive roles in enhancing consumer empowerment, which further promotes impulse consumption behavior through customer commitment. Also, collectivism is found as a moderator.

A novel method has been proposed to reduce the false alarm rate of arrhythmia patients regarding life-threatening conditions in the intensive care unit. In this purpose, the atrial blood pressure, photoplethysmogram (PLETH), electrocardiogram (ECG) and respiratory (RESP) signals are considered as input signals.

Three machine learning approaches feed-forward artificial neural network (ANN), ensemble learning method and k-nearest neighbors searching methods are used to detect the false alarm. The proposed method has been implemented using Arduino and MATLAB/SIMULINK for real-time ICU-arrhythmia patients' monitoring data.

The proposed method detects the false alarm with an accuracy of 99.4 per cent during asystole, 100 per cent during ventricular flutter, 98.5 per cent during ventricular tachycardia, 99.6 per cent during bradycardia and 100 per cent during tachycardia. The proposed framework is adaptive in many scenarios, easy to implement, computationally friendly and highly accurate and robust with overfitting issue.

As ECG signals consisting with PQRST wave, any deviation from the normal pattern may signify some alarming conditions. These deviations can be utilized as input to classifiers for the detection of false alarms; hence, there is no need for other feature extraction techniques. Feed-forward ANN with the Lavenberg–Marquardt algorithm has shown higher rate of convergence than other neural network algorithms which helps provide better accuracy with no overfitting.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

With the launch of the Feminist International Assistance Policy (FIAP), the Canadian government named solidarity as a shared value and a driving motivation behind the FIAP. This paper explores how development workers understand and apply solidarity to their work, uncovering the opportunities and constraints they face.

In-depth, semi-structured interviews were conducted with 42 development workers from Canada’s federal development agency between 2019 and 2020. Transcribed data were coded by the author to identify how workers made sense of solidarity within the development industry.

The majority of workers were unsure of how to define or operationalize solidarity, demonstrating confusion. Commonality was routinely mentioned as a facet of solidarity, but workers understood this term in diverse ways, with some considering commonality as a precondition that inhibited a sense of solidarity with development partners in the global South due to differences in living conditions. About a quarter identified power and privilege as necessary considerations in the process of building solidarity, showing potential for bonds across the inequalities that define development. About 40% of workers identified the institutional structure of the organization as an obstacle to solidarity.

This paper presents original data from Canadian development workers, providing the first study of their understanding of solidarity as a development ethic. It shows the gaps between rhetoric and practice while recommending ways for development organizations to meaningfully engage with solidarity in their work.

A popular convention in the political-economy literature is that causality runs from democracy to economic growth. That thinking has continued to evoke significant debates among scholars. This study aims to propose a new research experiment by investigating whether macroeconomic variables cause democratisation.

The study uses a panel data set of 48 carefully selected economies in Sub-Saharan Africa spanning 1991 to 2020 and uses the PVAR system generalised method of moment (GMM) approach.

With the application of three macroeconomic indicators: economic growth, full employment and balance of payment equilibrium, the study suggests that economic growth has a negative implication on the democratisation process and that the incentives that increase national income provide in the global South enable autocratic rulers to impede democratic growth. The Granger causality test demonstrates a unidirectional effect from economic growth to democracy. The eigenvalue stability condition, impulse response function and forecast-error variance decomposition all confirmed the validity of the findings with the PVAR system GMM. Finally, the study proposed policy and theoretical implications for the political stakeholders.

Robust development of economic institutions (particularly the anti-corruption and rule of law) in the global South is required to tame the potential for the state actors to turn public resources into personal use to further their parochial political interest in the form of perpetuating themselves in office which negates the ideals of democracy and social norms. Strong institutions could prevent the misuse of national income and enhance a good quality of life for the citizenry, making them grow confidence in the democratisation process.

The research paper makes an insightful contributions from the methodological perspective and the sampling perspective. The author uses a new research method, the PVAR system GMM becoming the first attempt of such a method to be applied in determining the causal effects of macroeconomic variables on democracy in the literature. Another relevant contribution of the study relates to the sample technique of selecting economies from the Sub-Saharan Africa with notable weak or slow democratisation process.

This study aims to elucidate the dynamics of monetary and fiscal policy interactions in Brazil, focusing on the impacts of positive shocks in government consumption and interest rates. By comparing rational and behavioral agent responses, it clarifies how these frameworks influence gross domestic product (GDP), inflation, private and government consumption and nominal interest rates.

The study employs a new Keynesian dynamic stochastic general equilibrium (DSGE) model with Bayesian estimation from 2000Q1 to 2022Q4, capturing rational and behavioral behaviors with adjustments for Brazilian economic idiosyncrasies. Impulse response functions (IRF) assess the dynamic effects of policy shocks, providing a comparative analysis of the two frameworks.

Behavioral agents show greater initial sensitivity to policy shocks, causing more pronounced fluctuations in GDP, inflation and private consumption compared to rational agents. Over time, the behavioral approach leads to a more robust recovery, while the rational approach results in a quicker return to equilibrium but less pronounced long-term recovery. The study also finds fiscal policy can partially offset the negative impacts of monetary tightening, with a more delayed effect in the behavioral model.

This paper provides insights into the interplay between monetary and fiscal policies under different agent expectations, emphasizing the importance of incorporating behavioral elements into macroeconomic models to better capture policy dynamics in emerging markets.