A growing interest in digitalisation provides continuous support for corporate governance in addressing strategic decision-making under uncertain environments. Although an increasing number of studies provide valuable insights and practical implications, limited research examines specific CEO...

We investigate and axiomatize preferences that display indifference between deterministic states, but exhibit strict orderings over lotteries over these states. Such preferences might be due to the ability to adopt to states, or a (dis)taste for uncertainty. We derive a representation theorem...

This paper develops an axiomatic framework for decision making when preferences depend not only on the current alternative but also on the past frequency with which alternatives have been chosen. We identify key independence axioms that characterize frequency-dependent preferences. In addition,...

The increasing complexity and commercialization of the global space sector have elevated the strategic role of public-private partnerships (PPPs). However, the criteria for selecting suitable PPP models remain underexplored, particularly regarding the influence of national policy and market...

Information unraveling is an elegant theoretical argument suggesting that private information is voluntarily and fully revealed in many circumstances. However, the experimental literature has documented many cases of incomplete unraveling and has suggested limited depth of reasoning on the part...

Career decisions are among the most consequential choices individuals make, profoundly shaping their long-term stability and overall life satisfaction. The literature suggests that behavioral biases, specifically overconfidence, herd mentality, social comparison, status quo bias, and optimism...

Multi-objective optimization problems (MOPs) are common in real-world applications, including scheduling, vehicle routing, and engineering design. A key challenge in solving MOPs is balancing convergence and diversity, as these problems often involve conflicting objectives and complex...

Named Entity Recognition (NER) models have been used in various contexts to automate the analysis of textual data, supporting tasks such as text categorization and relationship extraction across entities. While these models are typically trained on large corpora, their efficacy should be...

This study examines how blockchain technology (BT) enhances sustainability and resilience in construction supply chains (CSCs). Recognizing the sector's vulnerability to disruptions and inefficiencies, the research aims to identify key blockchain facilitators (BTFs) that enhance environmental,...

Multi-Criteria Decision-Making (MCDM) methods, particularly TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) (Multicriteria Optimization and Compromise Solution), are extensively used in logistics for...

Civil Helicopter Emergency Medical Services (CHEMS) are vital for improving emergency healthcare access, particularly in remote or congested areas. While widely implemented in high-income countries, CHEMS remain underutilized in low- and middle-income countries (LMICs) due to financial,...

Seaweed is a globally significant aquaculture commodity with increasing economic and environmental importance. However, inconsistent quality standards and subjective procurement practices continue to hinder efficiency in its value chain, particularly for dried Eucheuma seaweed. This study...

Many countries are prioritizing renewable energy sources in response to fossil fuel depletion, environmental concerns, and the need for energy resilience. This study evaluates five renewable energy alternatives: Biomass, Wind, Solar, Geothermal, and Hydro, with the aim of reducing foreign energy...

Natural disasters like hurricanes, earthquakes, and floods devastate food supply chains and can threaten food security and public health. These disruptions, from production to consumption, lead to shortages, increased waste, and heightened vulnerability among food-insecure populations. This...

Suitable facility location selection for customer-required capacity localization is an emerging topic in semiconductor supply chain management. However, this topic has not been thoroughly investigated. For this reason, an explainable artificial intelligence (XAI)-interpreted fuzzy group...

(1) Background: This study aimed to develop and validate a new instrument to measure relational reflexivity in management settings. Relational reflexivity-defined as the integration of self-awareness, perspective-taking, and interpersonal responsibility-has been discussed conceptually, but it...

The transition to a sustainable bioeconomy represents a crucial strategy for mitigating climate change and reducing dependence on fossil resources. Central to this strategy is the development of bio-based alternatives through innovative technologies, such as biorefineries. The success of this...

The association between emotions and decision-making is evident. Our article aims to demonstrate, for individual investors, the development of negative emotional charges on stock markets in a perceived negative trend. The research question concerns how negative emotions may be associated with...

In the rapidly evolving landscape of data analytics, effective decision-making is paramount. Multi-attribute decision-making (MADM) techniques are widely applied to handle uncertainty and vagueness in diverse fields such as medical diagnosis, social selection, networking, and environmental...

We develop a micro-founded framework to account for individuals' effort and cognitive noise which confound estimates of preferences based on observed behavior. Using a large-scale experimental dataset we find that observed decision noise responds to the costs and benefits of exerting effort on...

Several behavioral models assume that choice over multi-attribute goods is systematically affected by the ranges of attribute values. Two recurring principles in this literature are contrast, whereby attributes with larger ranges attract attention and are therefore overweighted, and...

Understanding generational differences in herding behavior is crucial for policymakers, financial educators, and market regulators, particularly in emerging markets where retail investor participation is rapidly growing. This study investigates the influence of herding behavior on investment...