Decision-making Process Research Articles

IFRS 16 and firms’ risk in emerging markets: the impact of managerial overconfidence

PurposeThe purpose of this study is to (1) investigate how IFRS 16 affects firms’ risk in Egypt and (2) examine the moderating role of managerial overconfidence on this relation.Design/methodology/approachThis study uses data from the annual reports of 38 Egyptian firms from 2014 to 2022. This study employs the generalized method of moments (GMM) and the three-stage least squares (3SLS) as estimation techniques.FindingsThe results show that IFRS 16 positively affects Egyptian firm risk, while managerial overconfidence reduces this positive effect.Research limitations/implicationsThis study has some limitations. First, the sample size was relatively small. Second, our analysis did not incorporate other metrics of managerial overconfidence owing to the unavailability of relevant data in Egypt.Practical implicationsThis study assists stakeholders and regulators in realising the implications of IFRS 16 on a firm’s risk, especially in emerging markets. Also, it enables managers to identify and assess lease-related risks more accurately to assist in developing appropriate risk mitigation strategies and optimizing lease-related decision-making processes. Furthermore, it aids in enhancing comprehension and knowledge of the interplay between managerial behaviour and firm outcomes.Originality/valueGrounded in agency theory, this study reveals novel empirical insights into the impact of IFRS 16 on firm risk, especially in the context of emerging markets. Utilizing behavioural decision theory and upper echelons theory, it examines the previously unexplored influence of managerial overconfidence on this relationship.

Measuring Indonesian Intention to Use Islamic Mortgage: A Quantitative Approach

This study explores the factors that influence the intention to use Islamic mortgage products in Indonesia, specifically focusing on Brand Awareness, Risk Perception, Religiosity, and their impact on Intention to Use. Using quantitative methods, 200 respondents were surveyed to gauge their interest in using Islamic mortgage products. The analysis used Structural Equation Modeling (SEM) through SmartPLS to evaluate the relationship between the variables. The findings show that Brand Awareness plays the most important role in shaping consumers' intention to use Islamic mortgage products, with a path coefficient of 0.773, which indicates a strong and significant influence. Perceived Risk also significantly influences Brand Awareness (β = 0.689), highlighting that consumers' perception of risk can shape their awareness of Islamic mortgage options, although its direct impact on Intention to Use is relatively smaller (β = 0.118). In addition, Religiosity was found to have a meaningful yet moderate influence on Brand Awareness (β = 0.275) and Intention to Use (β = 0.085), underscoring the relevance of religious values in consumers' decision-making process. Overall, the results suggest that to increase the adoption of Islamic mortgage products in Indonesia, financial institutions should focus on increasing Brand Awareness, reducing Perceived Risk, and increasing the religiosity of their target audience. Marketing strategies that emphasize Shariah compliance, transparency, and ethical financial practices can encourage the intention to use Islamic mortgages, thereby contributing to the growth of the Islamic financial sector in Indonesia.

Understanding Consumer Behavior in Online Education: Factors Influencing Purchase Intention of Paid Online Course

The evolution of technology has significantly influenced educational methodologies, leading to a surge in the popularity of online learning platforms. This study aims to investigate the factors influencing the purchase intentions of paid online courses in Indonesia. Utilizing a quantitative research design, the study examines the impact of several variables: certificate, performance expectation, perceived lecturer expertise, testimonial, brand trust, perceived financial cost, and personal trial experience on the decision-making process of consumers considering paid online courses. Variables examined in this research was obtained from the previous research and preliminary research to confirm the importance of these variables. Sample used in this research are 237 respondent that fit the criteria of having experience in using Online Paid Course, since this resarch used judgmental sampling. Data are gathered using questionnaire and analyze using SPSS 27.0. The findings reveal that perceived lecturer expertise and personal trial experience significantly enhance purchase intentions, underscoring the importance of credible instructors and the opportunity for prospective students to experience courses before enrollment. Perceived financial cost also plays a critical role, indicating that cost-effective pricing strategies are essential for attracting and retaining learners. Some group with different motivation and type has different important variable for them. Future research are recommended to explore on more specific themes like career switchers or detailed evaluations of an OPC provider's brand, considering user experience and other key aspects that influence brand perception and purchase decisions in the evolving field of online education.

Is moving the solution? Evidence from a social housing demolition program in Santiago, Chile

ABSTRACT In 2013, a social housing demolition program was implemented in Santiago, Chile. The program was voluntary, and residents were required to apply collectively. This article employs mixed methods to explore the decision-making processes of residents who stayed and those who moved. Residents resisted the negative narratives of their areas, demonstrating alternative ways of thinking about the neighborhood, and expected to move close-by, although to different kinds of units. Other residents recognized the negative effects of high turnover, including insecurity and distrust, and were willing to leave. Their experiences provide insights to reflect on the reach of mobility programs.

Valuation and Volatility of Virtual Properties in Metaverse: Exploring New Market Opportunities and Speculative Dynamics Based on Decentraland

Existing reality has been repeatedly subjected to multifaceted and multidimensional analyses. However, alongside it, a virtual reality exists, populated with virtual art, objects in games, cyber-pets, and virtual properties, collectively worth billions of real dollars. This virtual reality is associated with the concept of the 'metaverse' (a term derived from 'meta' and 'universe'), signifying a space that facilitates life in a virtual world. This space has a quantifiable value and is traded on specially designed platforms. The study focuses on the largest of these platforms, Decentraland, where users can purchase virtual properties using a cryptocurrency called MANA. Based on an analysis of 207 property transactions, the study examines whether these properties can be appraised using typical approaches applicable to “real” properties. It explores the relationship between spatial attributes, property price, and price volatility over time, calculating correlation coefficients for this purpose. Additionally, the study investigates the number of property sales, including multiple sales, and the proportion of properties with ITEMs on them, determining the correlation coefficients between price and parcel attributes. This study is the first to accomplish what researchers in the real estate market have long been doing. The results distinctly show that the virtual real estate market is governed by different factors compared to the traditional market, with property price and location remaining as two crucial aspects in the decision-making process for purchasing a property.

The Economic Value of the Protective Functions of Mountain Forests: A Case Study in the Italian Alps

ABSTRACT Mountain forests perform an indirect protective function against natural events. The aim of this study is to develop a method of economic valuation of the role of mountain forests in reducing the risk of windthrow and soil erosion, taking as a case study the Cansiglio Orientale forest (Italian Alps). Protection against windthrow was investigated through the slenderness coefficient, while the soil erosion protection was analysed using a model that takes into account stand and site characteristics. The risk mitigation cost method has been applied for the economic estimation of the protective functions. The main results showed that more than 63% of trees are included in areas with high stand stability, while over 54% of the area is classified as low risk of soil erosion. Finally, an economic value of € 61.72 ha−1 yr−1 – € 20.36 ha−1 yr−1 to maintain the stand stability and of € 4.39 ha−1 yr−1 – € 1.31 ha−1 yr−1 to restore soil fertility after erosion were estimated. This study has provided an approach for the economic valuation of the protective function of mountain forests based on mitigation cost method. This contribution fits into the literature concerning the economic valuation of ecosystem services to improve decision-making process.

Exploring the Impact of E-Governance on Public Sector Efficiency and Accountability in Local Governments: A Case of Kinondoni and Ubungo Municipalities in Tanzania

This study explores the impact of e-governance in enhancing service delivery efficiency and transparency in decision-making within local governments, specifically in Kinondoni and Ubungo municipalities in Tanzania. The theoretical foundation of this study was built upon two key frameworks: Innovation Diffusion Theory (IDT) and Principal-Agent Theory. This study used a descriptive research design and a quantitative approach. A stratified random sample of 300 participants (government employees and citizens) completed structured questionnaires. Data were analyzed using descriptive statistics and multiple regression analysis with SPSS software. Secondary data from government reports and policy documents supplemented the primary data to provide additional context. The findings indicate that e-governance significantly improved service delivery and transparency by reducing paper-based processes, speeding up services, and minimizing errors. Regression coefficients of 0.762 for efficiency and 0.735 for transparency were statistically significant (p < .001), with baseline constants of 1.173 and 1.249, respectively, prior to e-governance implementation. The respondents also reported that digital platforms have enhanced citizen engagement and made government operations more accessible. The study concludes that e-governance is a key factor in improving the efficiency of public services and the transparency of decision-making processes in local governments. Recommendations include further expansion of digital platforms, increased digital literacy, and stronger data security measures to maximize the benefits of e-governance.

Digital and Social Determinants of Consumer Decision Making in OTC Pharmaceuticals

This paper outlines various factors that determine consumer choice of over-the-counter drugs, focused mainly on digital marketing and social group influence. The research work is based on quantifying the relationship between different factors and consumer decision processes. These results also suggest a fair relationship between digital marketing and consumer buying behaviour, showing that digital platforms are increasingly used as information sources for OTC medicines. On the other side, reference groups—like advice from pharmacists, doctors, family, and friends—are more important for purchase choices than online marketing, highlighting how vital trust between people is in health decisions. The study further shows that digital marketing and reference groups are complementary, with consumers mainly initiated into buying through digital means but seeking validation and advice from trusted people. These agree with earlier findings and amplify the evolving interplay of modern marketing strategies with social influences in the traditional sphere of pharmaceuticals. Practical implications for this research indicate that pharmaceutical companies must pursue integrated marketing strategies in which digital outreach is combined with efforts to reach reference groups. The pharmacist or health professional is another important agent that can bridge the gap between online and offline consumer involvement. This study thus helps marketers, healthcare professionals, and policymakers develop strategies for improving consumer awareness and confidence in OTC medicines.

Adapting Constrained Markov Decision Process for OCPC Bidding with Delayed Conversions

Nowadays, optimized cost-per-click (OCPC) has been widely adopted in online advertising. In OCPC, the advertiser sets an expected cost-per-conversion and pays per click, while the platform automatically adjusts the bid on each click to meet advertiser’s constraint. Existing bidding methods are based on feedback control, adjusting bids to keep the current cost-per-conversion close to the expected cost-per-conversion to avoid compensation. However, they overlook the conversion lag phenomenon: There always exists a time interval between the ad’s click time and conversion time. This interval makes existing methods overestimate the cost-per-conversion and results in over conservative bidding policies which finally hurts the revenue. To address the issue, this article proposes a novel bidding method, Bidding with Delayed Conversions (Bid-DC) which predicts the conversion probability of the clicked ads and used it to adjust the cost-per-conversion values. To ensure the bidding model can satisfy the advertiser’s constraint, constrained Markov decision process (CMDP) is adapted to automatically learn the optimal parameters from the log data. Both online and offline experiments demonstrate that Bid-DC outperforms the state-of-the-art baselines in terms of improving revenue. Empirical analysis also showed Bid-DC can accurately estimate the cost-per-conversion and make more stable bids.

The effect of a general practitioner's perception of a patient request for antibiotics on antibiotic prescribing for respiratory tract infections: secondary analysis of a point prevalence audit survey in 18 European countries.

Illness severity, comorbidity, fever, age and symptom duration influence antibiotic prescribing for respiratory tract infections (RTI). Non-medical determinants, such as patient expectations, also impact prescribing. To quantify the effect of general practitioners' (GPs') perception of a patient request for antibiotics on antibiotic prescribing for RTI and investigate effect modification by medical determinants and country. Prospective audit in 18 European countries. Consultation data were registered of 4982 patients presenting with acute cough and/or sore throat. A mixed-effect logistic regression model analysed the effect of GPs' perception of a patient request for antibiotics. Two-way interaction terms assessed effect modification. Relevant clinical findings were added to subgroups of lower RTI (LRTI), throat infection, and influenza-like-illness (ILI). GPs who perceived a patient request for antibiotics were four times more likely to prescribe antibiotics (OR: 4.4, 95%CI: 3.4-5.5). This effect varied by country: lower in Spain (OR: 0.06), Ukraine (OR: 0.15), and Greece (OR: 0.22) compared to the lowest prescribing country. The effect was higher for ILI (OR: 13.86, 95%CI: 5.5-35) and throat infection (OR: 5.1, 95%CI: 3.1-8.4) than for LRTI (OR: 2.9, 95%CI: 1.9-4.3). For ILI and LRTI, GPs were more likely to prescribe antibiotics with abnormal lung auscultation and/or increased/purulent sputum and for throat infection, with tonsillar exudate and/or swollen tonsils. GPs' perception of an antibiotic request and specific clinical findings influence antibiotic prescribing. Incorporating exploration of patient expectations, point-of-care testing and discussing watchful waiting into the decision-making process will benefit appropriate prescribing of antibiotics.

How Do UK Political Elites Reconcile With a Low Trust Environment?

Evidence indicates that citizens widely regard politicians as untrustworthy. But do low levels of trust affect politicians’ behaviour? In this article, we draw on interviews conducted with UK political elites to understand: (a) whether they recognise a lack of public trust; (b) what they perceive as its causes and present as solutions; (c) how it affects the decision-making process; and (d) whether they feel it undermines their sense of legitimacy. While we find that UK political elites do acknowledge low levels of trust, they reveal that this has only modest effects on their activities, and the legitimacy to take major decisions is undented. Low trust offers political opportunities as well as threats. Low trust places few constraints on politicians’ ability to wield power. As a result, leading politicians may lack the motivation to take meaningful action to arrest low levels of citizens’ trust.

How does live streaming affect tourists’ intention — a psychology theory perspective

As a novel experiential approach, live streaming at tourist destinations has garnered significant attention and profoundly impacts tourists’ travel decisions. This study aims to validate the effects of usefulness, authenticity, and interactivity of destination live streams on the decision-making process of tourists. Grounded in stimulus–organism–response (S-O-R) theory, this research identifies the usefulness, authenticity, and interactivity of destination live streams as the “stimulus,” while telepresence and trust as the “organism,” with tourists’ travel decisions as the “response.” Utilizing survey questionnaires, 274 valid data were collected and analyzed through structural equation modeling in SPSS 26.0 and Amos 28.0 software to assess the impact of destination live streams on tourists’ travel decisions. The findings reveal that both interactivity and authenticity positively influence tourists’ telepresence. Additionally, the usefulness, interactivity, and authenticity of these live streams also positively affect perceived trust among viewers, which subsequently enhances their travel decisions. This study highlights the usefulness, authenticity, and interactivity as external stimuli in destination live streams, elucidating their influence on tourists’ travel decisions and contributing to the understanding of the live streaming phenomenon within the tourism sector.

Factors Influencing the Choice Between Multi-Target Stool DNA and Colonoscopy for Colorectal Cancer Screening Among Alaska Native Peoples

The Alaska Tribal Health System is increasing colorectal cancer (CRC) screening among Alaska Native (AN) peoples, who experience the highest CRC rate in the world. Through a clinical trial (NCT04336397), AN people living in rural/remote Alaska were offered either the previously unavailable multi-target stool DNA test (mt-sDNA; Cologuard®) or colonoscopy. From April 2022 to August 2024, 113 (59%) people who completed mt-sDNA testing and 51 (39%) who completed a colonoscopy procedure participated in a survey on factors influencing their screening test choice. The majority of mt-sDNA participants (79%) were aware of the colonoscopy option, while most colonoscopy participants (72%) reported being unaware of the mt-sDNA option. Key mt-sDNA preference themes included not having to travel, less time commitment, childcare and work responsibilities, physical limitations, greater convenience, and the test being less invasive and dangerous than a colonoscopy. In contrast, colonoscopy preference themes included wanting to adhere to screening recommendations, be proactive about preventative health, family history of cancer, awareness of the higher CRC risk among AN peoples, as well as the belief that colonoscopy is more reliable and accurate since it is performed by medical providers. These findings underscore the complex factors influencing CRC screening preferences among rural and remote AN people. Limited access to medical facilities, financial burdens, and personal commitments, along with personal factors, have a substantial bearing on the screening decision-making process. Recognizing and addressing these multifaceted influences can help CRC screening programs better meet community member needs and preferences, ultimately improving screening rates and colorectal health outcomes.

Towards Personalized Radiotherapy in Pelvic Cancer: Patient-Related Risk Factors for Late Radiation Toxicity

Normal tissue reactions vary significantly among patients receiving the same radiation treatment regimen, reflecting the multifactorial etiology of late radiation toxicity. Predicting late radiation toxicity is crucial, as it aids in the initial decision-making process regarding the treatment modalities. For patients undergoing radiotherapy, anticipating late toxicity allows for planning adjustments to optimize individualized care. Various dosimetric parameters have been shown to influence the incidence of late toxicity, and the literature available on this topic is extensive. This narrative review examines patient-related determinants of late toxicity following external beam radiotherapy for pelvic tumors, with a focus on prostate and cervical cancer patients. In Part I, we address various methods for quantifying radiation toxicity, providing context for interpreting toxicity data. Part II examines the current insights into the clinical risk factors for late toxicity. While certain factors—such as previous abdominal surgery, smoking behavior, and severe acute toxicity—have consistently been reported, most of the others show inconsistent associations. In Part III, we explore the influence of genetic factors and discuss promising predictive assays. Single-nucleotide polymorphisms (SNPs) likely elevate the risk in specific combinations. Advances in artificial intelligence now allow for the identification of SNP patterns from large datasets, supporting the development of polygenic risk scores. These innovations hold promise for improving personalized treatment strategies and reducing the burden of late toxicity in cancer survivors.

Ethical AI in HR: A Case Study of Tech Hiring

ABSTRACT The job applicant hiring process is inherently complex, encompassing various dimensions such as cultural fit, team dynamics, and individual qualifications. This paper explores the potential of machine learning techniques as analytical tools to examine the nuances of the hiring process rather than automating it. In this study, we use machine learning models to evaluate whether gender or age bias exists in hiring decisions by examining an extensive IT industry dataset comprising over 70,000 applicants. We provide practical guidelines for data preparation, bias evaluation, and assessment of AI-driven hiring outcomes, focusing on the influence of key factors on hiring probability. Our findings reveal that female applicants tend to receive lower hiring probabilities than male applicants, suggesting a gender-related bias. Additionally, we identify that proficiency in “Computer Skills,” the number of programming languages known, and familiarity with the language “TypeScript”—introduced in 2012—are among the top skills influencing hiring decisions. This study offers HR practitioners actionable insights into the AI decision-making process, highlighting how skills valued by AI models may differ from those prioritized in traditional recruitment. Through our empirical study, we demonstrate how multiple machine learning methods can be used for bias detection and the validation of critical decision factors in hiring decisions, equipping HR professionals with tools to enhance understanding and fairness in AI-driven hiring.

Strategies for introducing and implementing vaccines for adults into national immunization programs in Europe: Good practices and key insights of the adult immunization board meeting.

In April 2024, the Adult Immunization Board convened a technical meeting to explore the latest strategies and identify exemplary approaches regarding the implementation of vaccines for adults into Europe's National Immunization Programs (NIPs). The meeting was built around three pillars: decision making for introducing a new vaccine, implementation, monitoring, and evaluation. The increasing number of new vaccines available in a context of competing health priorities warrants transparent and evidence-based decision-making processes for vaccine introduction. In Europe, burden of disease, vaccine efficacy or effectiveness, and safety are universally used decision-making criteria. While economic evaluations and the quality of evidence are being increasingly considered, public acceptance, equity, and operational criteria remain underutilized. Vaccine implementation requires planning and coordination. Implementation activities discussed during the meeting were vaccine program goals, target population identification, communication, training of healthcare professionals, and involvement of pharmacists. Once operational, NIPs are to be monitored in terms of safety, effectiveness, and impact. Implementation science as well as behavioral and cultural insights can be used to identify tangible interventions to improve uptake. Meeting discussions allowed to identify adult vaccine implementation barriers and possible strategies to overcome them. Enhanced cooperation and coordination throughout the Europe region were recognized as critical components of progress.

Understanding the Baltic Dry Index (BDI): an explainable decomposition approach

ABSTRACT The Baltic Dry Index (BDI) is a crucial indicator of the dry bulk freight market, offering insights into the shipping industry’s health and activity levels. In this study, we introduce an explainable decomposition framework to unveil the underlying mechanisms of BDI dynamics. Utilizing historical data from 1 November 1999, to 5 March 2024, we decompose BDI into trends, seasonal fluctuations, and externally derived influences. Our experiments have identified the magnitude of trend changes from major global events over the past two decades. Intriguingly, we find that advancements in industry and technology contribute significantly to upward trends in BDI. We also explore BDI’s seasonality, identifying distinct cyclical patterns within a year, including the Christmas and Chinese New Year effects, and more interestingly, a trough in late June due to the receding in shipping demand for the three major bulk. Our findings further offer valuable insights into understanding BDI fluctuations, aiding decision-making processes in the maritime freight market. We find that Natural Gas and the Dollar Index are potent signals for BDI one week to one month ahead, while the NASDAQ 100 Index emerges as a leading indicator for longer forecasting horizons.

Using the knife to build the trust? The role of trust in the decision-making process of aesthetic surgeons and women patients/clients

Using the knife to build the trust? The role of trust in the decision-making process of aesthetic surgeons and women patients/clients

The impact of neuromarketing and influencer marketing on the decision process of generation Z consumers on the purchase of halal cosmetics

This study aims to help business actors understand Generation Z's purchase decision. In addition, it examines the behaviour of Generation Z mediated by neuromarketing and influencer marketing in the decision to purchase halal cosmetics so that business actors can determine strategies by optimising product information and advertising. The population of this study is residents of Cirebon City aged 19 to 24 years, with a population of 56,626. The sampling used the Slovin formula and obtained as many as 397 respondents. To test the hypothesis of this study, samples were taken randomly using SEM-PLS (Partial Least Squares—Modeling Structural Equation) analysis. The study results show that neuromarketing and influencer marketing influence the purchase decision of Generation Z halal cosmetics through consumer behaviour. The dominating influence is influencer marketing in the decision to purchase halal cosmetics through the behaviour of Generation Z. Thus, the results of this research can be used by halal cosmetics business actors in Cirebon City to implement their business strategies using influencer marketing so that business continuity is also expected to be maintained.

Effects of described demonstrator ability on brain and behavior when learning from others

Observational learning enables us to make decisions by watching others’ behaviors. The quality of such learning depends on the abilities of those we observe, but also on our beliefs about those abilities. We have previously demonstrated that observers learned better from demonstrators described as high vs. low in ability, regardless of their actual performance. The current study aimed to conceptually replicate these findings, and explore the neural mechanisms involved. Forty-five participants performed an observational learning task while undergoing functional magnetic resonance imaging (fMRI). We hypothesized that participants would perform better when demonstrators were described as having high vs. low ability. Unexpectedly, participants performed equally well regardless of described demonstrator ability. The behavioral effects of biased observational learning seem to be driven by mentalizing processes together with general learning and decision-making processes.