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Live-streaming e-commerce (LSE) allows anchors to bring offline promotion skills to interact with consumers and persuade them to buy. However, how consumers respond to these communications remains unknown. This study examines the persuasive effect of different scarcity marketing messages on impulsive buying in the LSE context.

This study adopts scenario-based experimental methods and conducts two 2 quantity-based scarcity (supply-framed vs demand-framed)*2 time-based scarcity appeals (high vs low) between-subjects experiments to test the hypotheses.

The results indicate that supply-framed appeals are more effective in provoking consumers’ arousal and impulsive buying, but are moderated by time scarcity. Furthermore, emotional arousal only mediates the effects of quantity-based scarcity appeals on impulsive buying under high-level time scarcity conditions.

This study contributes to the e-commerce literature by comparing the persuasive effect of different scarcity messages in the LSE context. We broaden the scarcity marketing literature by testing the combined effect of quantity-based and time-based scarcity appeals. Finally, this study extends the application of the competitive arousal model.

The topic of artificial intelligence (AI) has been expanding rapidly in recent years, gaining the attention of academics and practitioners. This study provides a structured literature review (SLR) on AI and management decisions (MDs) by analysing the scientific output and defining new research topics.

The study uses a rigorous methodological approach to summarise the state of the art of the past literature. The authors used Scopus as the database for data collection and utilised the Bibliometrix R package. In total, 204 peer-reviewed English articles were collected and analysed.

The results showed that literature in this field is emerging. Studies are focused on using AI as forecasting and classification for management decision-making, AI as a tool to improve knowledge management in organisations and extract information. The cluster analysis revealed the presence of five thematic clusters of studies on the topic.

The study’s originality lies in providing a new perspective on AI for MDs. In particular, the analysis reveals a new classification of research streams and provides fruitful research questions to continue research on the topic.

The aim of this paper is to review the literature on the prediction of cutting tool life. Tool life is typically estimated by predicting the time to reach the threshold flank wear width. The cutting tool is a crucial component in any machining process, and its failure affects the manufacturing process adversely. The prediction of cutting tool life by considering several factors that affect tool life is crucial to managing quality, cost, availability and waste in machining processes.

This study has undertaken the critical analysis and summarisation of various techniques used in the literature for predicting the life or remaining useful life (RUL) of the cutting tool through monitoring the tool wear, primarily flank wear. The experimental setups that comprise diversified machining processes, including turning, milling, drilling, boring and slotting, are covered in this review.

Cutting tool life is a stochastic variable. Tool failure depends on various factors, including the type and material of the cutting tool, work material, cutting conditions and machine tool. Thus, the life of the cutting tool for a particular experimental setup must be modelled by considering the cutting parameters.

This submission discusses tool life prediction comprehensively, from monitoring tool wear, primarily flank wear, to modelling tool life, and this type of comprehensive review on cutting tool life prediction has not been reported in the literature till now. The future suggestions provided in this review are expected to provide avenues to solve the unexplored challenges in this field.

The purpose of this study is to provide an optimal joint strategy of multi-period pricing and sales effort for a retailer with a logit choice demand in an integrated channel.

Customer demand is characterized by a logit choice model, it varies over time and is influenced by price and sales effort. The multi-period decision model for the retailer is constructed using a discrete-time dynamic programming method to determine the optimal price and sales effort in each period.

When the inventory level does not exceed a certain threshold, decreasing price and increasing sales effort over time or as inventory level increases are the optimal strategies. However, once the inventory level exceeds the threshold, the optimal strategy is to maintain both price and sales effort constant as the inventory level changes or to increase price and decrease sales effort over time. Additionally, the greater the influence of sales effort on demand or the higher the arrival rate of customers, the higher the optimal price and the greater the optimal sales effort level.

This study contributes to the existing research on dynamic pricing and sales effort in integrated channels by incorporating a logit choice model. Furthermore, it provides valuable management insights for retailers operating in an integrated channel to make pricing and sales effort decisions based on inventory level and time period.

The purpose of this study is developing a new buy-back coordination contract in the symbiotic supply chain. In this new contract, the goal of the supply chain members (profit maximization) is realized.

This paper encourages the manufacturer to order products optimally by presenting a new buy-back coordination contract, and in return, the supplier undertakes to buy the unsold products from the manufacturer at the buy-back price. By using data-driven decision-making and multiobjective decision-making and considering the existing conditions in the symbiosis industry, a contract has been presented that guarantees the profits of supply chain members.

In this paper, it was found out how the authors can determine the order quantity, buy-back price and wholesale price in a symbiotic supply chain in such a way that it makes a profit for both the supplier and the manufacturer. In other words, how to determine these variables to encourage the manufacturer to order more quantity to the supplier so that both will benefit.

To the best of the authors’ knowledge, this is the first paper that defines a new buy-back coordination contract in the symbiotic supply chain by considering uncertain demand and a multiobjective model. Due to the importance of environmental issues, the sharing of resources by companies and organizations with each other, and the necessity of their cooperation, industries are moving toward a symbiosis industry.

The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.

First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.

This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.

This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.

Since February 2022, the conflict between Ukraine and Russia has significantly influenced global financial markets, altering investor behavior and increasing market volatility. Western countries’ sanctions on Russia have influenced market uncertainty. Academic literature has deeply investigated the market’s reaction to the conflict and demonstrated a diverse range of impacts. Our study delves into how corporate decisions to remain in or exit Russia during the conflict influence analyst sentiment.

Leveraging data on analysts' revision scores (ARS) from Eikon, Refinitiv, our analysis underscores the importance of analysts during periods of uncertainty (Kacperczyk and Seru, 2007; Loh and Stulz, 2018). Using static and dynamic panel analysis, we examine the impact of Russia exposure on ARS while controlling for key variables.

Companies that retain a presence in Russia tend to enhance the overall ARS score, contributing to increased optimism among analysts regarding forecasts for the firms in question. Controlling for endogeneity and underlying dynamics in ARS does not alter the main findings. All in all, the results confirm the absence of an impact on the companies' returns post-announcement to continue or leave Russia after the start of the conflict (Balyuk and Fedyk, 2023).

This research sheds light on the complex relationship between geopolitical events, corporate decisions and investor sentiment, offering valuable insights for stakeholders, policymakers and regulators.

The performance of large-scale projects is often challenged due to major environmental changes that occur during their life. However, literature has paid little attention to the governance adaptations required to respond effectively to these changes. This paper aims to study changes in the project environment over time, the corresponding governance adaptations and their impact on project performance.

To ensure triangulation between two sources of evidence, we used both primary and secondary data sources and examined 14 projects through 2 studies, the first focused on seven documented, illustrative case projects and the second on interviews with senior and project managers involved in seven additional projects.

We found the key environmental changes that should trigger appropriate governance adaptations to be market evolutions, technological advancements and sociopolitical events. However, we also found that these necessary governance adaptations are not commonly implemented timely, sufficiently or effectively.

The paper distills the dynamics of large-scale projects in achieving project effectiveness and raises theoretical propositions on the combination of environmental changes and deficient governance adaptations that, over time, turns efficient projects into ineffective projects and discusses implications for theory and practice.

A variety of buffer allocation methods exist to distribute an aggregated time buffer among project activities. However, these methods do not pay simultaneous attention to two key attributes of disruptive events that may occur during the construction phase: probability and impact. This paper fills this research gap by developing a buffer allocation method that takes into account the synergistic impact of these two attributes on project activities.

This paper develops a three-step method, calculating the probability that project activities are disrupted in the first step, followed by measuring the potential impact of disruption on project activities, and then proposing a risk-informed buffer allocation index by simultaneously integrating probability and impact outputs from the first two steps.

The proposed method provides more accurate results by sidestepping the shortcomings of conventional fuzzy-based and simulation-based methods that are purely based on expert judgments or historical precedence. Further, the paper provides decision-makers with a buffer allocation method that helps in developing cost-effective buffering and backup strategies by prioritizing project activities and their required resources.

This paper develops a risk-informed buffer allocation method that differs from those already available. The simultaneous pursuit of the probability and impact of disruptions distinguishes our method from conventional buffer allocation methods. Further, this paper intertwines the research domains of complexity science and construction management by performing centrality analysis and incorporating a key attribute of project complexity (i.e. the interconnectedness between project activities) into the process for buffer allocation.

The goal of this study was to assess changes in eating self-efficacy after participating in a brief psychoeducational group intervention, grounded in the cognitive-behavioral model, delivered by dieticians in community-based health facilities.

The study was conducted using a quasi-experimental, pre-post design. A total of 110 program participants took part in the study. They were asked to complete the Eating Self-Efficacy Scale before the start of the intervention, at the end of the intervention, and three months after the intervention ended. Data were analyzed using the Linear Mixed Model.

Participants’ personal sense of control over their eating behaviors significantly increased after they completed the program and continued to increase up to the three-month follow-up. The effect of the intervention remained significant after controlling for differences in age and whether participants had access to other forms of individual support or completed the follow-up during the COVID-19 general lockdown.

By promoting participants’ sense of eating self-efficacy, this intervention could lead to positive dietary changes, which in turn could promote better health and healthy aging.

This community intervention is readily accessible and represents a cost-effective approach to promote healthy eating, reducing the risk of chronic disease and the need for medical care, thereby cutting costs for the healthcare system.

(1) This study addresses a gap in the scientific literature as there was limited published research to date that investigated this intervention. (2) The three-month follow-up made it possible to evaluate whether changes in eating self-efficacy were maintained over time. (3) Potential confounding variables, including age, having access to other forms of individual support and the COVID-19 general lockdown, were taken into account.