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Commercial property development builds floor space in anticipation of potential, but unknown, future demand, making it particularly prone to risk and uncertainty. The research explores the degree to which property developer decision-making is objective and rational and the degree to which it relies on behavioural instincts and intuition. Decision-making theory, including heuristics, is considered and its prevalence in the field of commercial property development is examined.

A “dual-processing” decision-making model, comprising intuitive System 1 and objective System 2 processing, is proposed and tested. Inductive research using template analysis of interviews, with “high status” commercial property developers, explored whether the model offers an accurate representation of developers' behaviour and effective lens through which to examine decisions made under conditions of risk and uncertainty.

Participants believed they adopted objective and rational approaches to complex commercial property development decisions. Analysis of interviews reveals that System 1 heuristics and intuition play significant roles in decision-making behaviour, leading to potential bias and systematic error. The research concludes that the dual-processing model provides a useful lens through which to better understand the decision-making approach adopted by commercial property developers.

The research represents the rare application of behavioural theory to the realm of commercial property development and provides new and original insight as to how important investment decisions are made under conditions of risk and uncertainty, with implications for professional practice.

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

This paper describes how financial professionals' behavioral biases influence their financial forecast and decision-making process. Most of the earlier studies are focused on well-developed financial markets, and little is researched about financial professionals, such as institutional investors, portfolio managers, investment advisors, financial analysts, etc., in emerging markets.

An expert-validated questionnaire measure four prominent behavioral biases and Indian financial professionals' rational decision-making process. The final sample consists of 274 valid responses using the purposive sampling technique. IBM SPSS and AMOS structural equation modeling (SEM) software are used to build measurement and structural models, multivariate analysis including regression, factor analysis, etc.

The results provide empirical insights into the relationship between behavioral biases and the decision-making process. The results suggest that the structural path model closely fits the sample data. The presence of behavioral biases indicates that financial professionals' forecasting and decision-making is not always rational but bounded rational or irrational due to these factors. Furthermore, these biases (except overconfidence bias) have a markedly significant and positive relationship with irrational decision-making.

It is critical to eradicate these psychological errors, but awareness and attentiveness toward behavioral biases may help financial professionals to make informed decisions. Investors can improve their portfolio decisions and investments by recognizing their judgment errors and focusing on specific investment strategies to mitigate the impact of these biases. It is necessary to incorporate behavioral insights while developing training techniques for financial professionals. Rules of thumb, visual tools, financial coaching and implementing social-cultural elements in training programs enable financial professionals to develop simple, engaging, appealing and customized approaches for their clients.

This novel study is the first of this kind of research that examines the relationship between financial professionals' behavioral biases and rational decision-making process. This study significantly and remarkably provides insights into irrationality in financial professionals' decision-making.

Research on market information use in product innovation suggests that firms utilize two key strategic decision-making processes: incremental and comprehensive. Drawing from organizational information processing theory, literature implies that these processes operate differently. However, this assumption remains untested. Moreover, the degree to which a comprehensive process affects the innovation strategy outcomes depends on market information time sensitivity (MITS) and analyzability. To-date, no study has tested these assertions, either. Finally, it is suggested that meaningful market strategy is a key driver of new product success and it is important to understand how decision-making processes influence it under differing time sensitivity and analyzability.

Based on survey data from 250 Chinese firms, authors use structural equation modeling to test the hypotheses.

The results generally support authors’ contentions. More specifically, marketing strategy outcomes are influenced by marketing strategy incrementality (MSI) and marketing strategy comprehensiveness (MSC) differently. Further, time sensitivity moderates the effect of both MSI and MSC on outcomes, except for the effect of MSI on decision quality. Finally, analyzability moderates the relationships between decision making processes and certain strategy outcomes such as between MSI and meaningfulness.

Drawing from information processing theory, authors argue that incremental and comprehensive marketing strategy decision making for new product operate differentially under the same conditions. Further, the effects of these decision processes on outcomes depend on time sensitivity and analyzability of market information. Finally, auhtors argue that meaningful market strategy is a driver of success. The authors find support for most of our hypotheses and provide directions for future research.

This study will examine the school principals’ ethical decision-making processes and to explore gender-related differences.

This study employed a mixed-method research design, combining qualitative and quantitative approaches. Data were collected through semi-structured in-depth interviews with a sample of 10 male and 10 female principals, who were presented with ethical dilemma scenarios. The qualitative component utilized a phenomenological analysis, while additional quantitative analyses were performed on the same dataset to explore gender-related differences.

Our analysis of principals' ethical evaluations identified three key areas where gender-related differences were evident: decision-making approaches, leadership styles, and philosophy/value orientations. The analysis revealed that women more frequently employed personal approaches, while men favored institutional approaches in their ethical evaluations. Secondly, men tended to adopt a democratic style, while women leaned towards an autocratic style. Finally, men exhibited a relativist orientation, while women displayed an idealist orientation in their ethical decision-making processes.

Gender-based analysis of school principals’ ethical decision-making process has remained an under-researched area. This study contributes to the understanding of gender-related differences in principals’ ethical decision-making processes.

This exploratory study aimed to investigate law enforcement officers’ decision-making processes in high-stress scenarios, exploring variations based on experience and how cognitive demands influence officer decision-making processes.

Employing a naturalistic decision-making approach and macrocognitive framework, the study utilizes scenario-based virtual reality simulations and qualitative interviews to examine the decision-making processes of law enforcement officers in high-stress policing contexts.

Thematic coding of interview data from twelve LEOs immediately following a high-stress virtual reality task revealed differences in decision-making processes and cognitive demands between novice and expert officers. Findings also revealed differences in the type of cognitive demands experienced by officers at key points in the simulated scenario.

The authors offer theoretical and practical contributions toward an increased understanding of officer decision-making, factors and conditions that impact LEO decisions and potential mitigation strategies that law enforcement organizations may leverage to improve officer decision-making in high-stress contexts.

This paper examines the relationship between marketing automation emergence and the marketers' use of heuristics in their decision-making processes. Heuristics play a role for the integration of human decision-making models and automation in augmentation processes, particularly in marketing where automation is widespread.

This study analyzes qualitative data about the impact of marketing automation on the scope of heuristics in decision-making models, and it is based on evidence collected from interviews with twenty-two experienced marketers.

Marketers make extensive use of heuristics to manage their tasks. While the adoption of new automatic marketing tools modify the task environment and field of use of traditional decision-making models, the adoption of heuristics rules with a different scope is essential to defining inputs, interpreting/evaluating outputs and control the marketing automation system.

The paper makes a contribution to research on the relationship between marketing automation and decision-making models. In particular, it proposes the results of in-depth interviews with senior decision makers to assess the impact of marketing automation on the scope of heuristics as decision-making models adopted by marketers.

Citizen engagement can promote value creation in urban development projects. This potential stems from the granting of decision-making authority to citizens, labeled citizen enfranchisement in this study. Citizens are focal stakeholders of urban development projects and enfranchisement grants them an explicit say on such projects. Despite this potential for enhanced value creation, there remains limited understanding about how project organizations enfranchise stakeholders in the front end of urban development projects.

In this research, we designed a multiple-case study to analyze two novel citizen engagement processes in Northern-European cities. In these processes, citizens were enfranchised in ideating, designing, and making selections on urban development projects. We followed a multimethod approach to data collection. The collected datasets include document data, interview data and observation data.

Our findings demonstrated a distribution and redistribution of decision-making authority throughout the phases of the citizen engagement processes. Citizens’ voices were amplified throughout the project front end, although episodes of decision-making authority held by the cities took place periodically as well. By granting explicit decision-making authority to citizens, citizen enfranchisement facilitated a more democratic urban development process, promoting value creation.

In contrast to the earlier research, the findings of our study illustrate citizen engagement taking place at so-called higher levels of stakeholder engagement. In particular, our study reveals a granting of de facto decision-making authority to citizens, also known as citizen enfranchisement. These findings contribute to the earlier research on stakeholder engagement in projects, where the influence of stakeholder engagement has often been considered symbolic or limited.

The Kingdom of Saudi Arabia’s dedicated pursuit of technological modernization positions it as a forefront leader in integrating advanced systems, aligning smoothly with the ambitious goals outlined in Vision 2030. The purpose of this study is to investigate the influence of integrating enterprise resource planning (ERP) and business intelligence (BI) systems on decision-making processes within the industrial sector of Saudi Arabia.

Using a quantitative research design, this study uses a bootstrapping approach and partial least squares structural equation modeling to meticulously analyze data collected from Saudi industrial firms.

The research reveals favorable relationships among infrastructure readiness, data quality, security and access control, user capabilities, user training and the integration of ERP and BI. These positive associations collectively affirm the overarching positive impact of ERP and BI integration on decision-making processes within the industrial sector.

The study underscores the strategic imperative of aligning organizational practices with the identified characteristics to fully unlock the potential benefits of ERP and BI integration in the Saudi Arabian industrial sector.

This study contributes significantly to the existing literature by delving into the integration of ERP and BI in the industrial sector and its nuanced impact on decision-making processes, specifically in the context of the Kingdom of Saudi Arabia – an area that has not been extensively studied.

The purpose of this research is to analyze the influence of heuristics on Brazilian investors' behavior in the decision-making process.

The authors apply the partial least squares structural equation modeling methodology. This sample is composed of 220 investors.

The heuristics of overconfidence and anchoring positively influence investors' decision-making, while loss aversion negatively influences it. The herd effect exhibits no influence. The results also support the idea that decision-making positively influences investors' performance. Investors feel secure in their attitudes regarding financial decision-making, even if their decisions are not always rational as they are affected by biases.

This article explains the influence of heuristics on investors' decision-making and performance in the Brazilian context during the COVID-19 pandemic.