Search results

Takes the view that managerial decisions are made in a diversity of organizational settings which can best be explained and evaluated in the context of conceptual interdisciplinary decision‐making models, and that such models constitute an appropriate vehicle for explaining the eclectic aspects of managerial decision making in all types of formal organization. Presents a typology of conceptual decision‐making models and evaluates their similarities and differences along with their respective efficacies in various managerial decision‐making contexts. Advances the process model of managerial decision making as the ideal choice for decisions which have significant long‐term consequences for the whole organization.

This paper aims to investigate a team dynamics based approach to assess board effectiveness, namely the interplay between boardroom decision-making processes and the board members' cognitive mental models.

A socio-cognitive perspective is utilized for analyzing board processes and determining board effectiveness. Utilizing the concepts of team mental models and sensemaking, a theoretically grounded model of board effectiveness is developed, wherein the propositions predict the causality and effect of the socio-cognitive and sensemaking processes on board effectiveness.

The proposed model is able to analyze the relationship among the different decision-making processes and members' cognitive models as determinants of board effectiveness, wherein the board's decision making process mediates the board's cognitive model – effectiveness relationship, while the board's cognitive model moderates the decision process – effectiveness relationship.

The conceptual model advances a rationale that might explain the mixed or modest findings in literature on the relationship between board demographics, dynamics and effectiveness.

The model allows practitioners and policy makers an alternative mechanism to assess board effectiveness, that is able to not only integrate the demographic, diversity and dynamics related measures, but also enables a clear understanding of the cognitive influences on board decision making and effectiveness.

The conceptual model encompasses most of the relevant constructs and findings of previous studies and offers a parsimonious yet holistic understanding of the boardroom mechanisms that might determine board effectiveness.

Independent travelers are those vacationers who have booked only a minimum of their transportation and accommodation arrangements prior to departure on the vacation. Independent travel is an important and growing sector of worldwide tourism. Choice of vacation itinerary for the independent vacation represents a complex series of decisions regarding purchase of multiple leisure and tourism services. This chapter builds and tests a model of independent traveler decision-making for choice of vacation itinerary. The research undertaken employs a two-phase, inductive–deductive case study design. In the deductive phase, the researcher interviewed 20 travel parties vacationing in New Zealand for the first time. The researcher interviewed respondents at both the beginning and the end of their New Zealand vacations. The study compares pre-vacation research and plans, and actual vacation behaviors, on a case-by-case basis. The study examines case study narratives and quantitative measures of crucial variables. The study tests two competing models of independent traveler decision-making, using a pattern-matching procedure. This embedded research design results in high multi-source, multi-method validity for the supported model. The model of the Independent Vacation as Evolving Itinerary suggests that much of the vacation itinerary experienced in independent travel is indeed unplanned, and that a desire to experience the unplanned is a key hedonic motive for independent travel. Rather than following a fixed itinerary, the itinerary of an independent vacation evolves as the vacation proceeds. The independent traveler takes advantage of serendipitous opportunities to experience a number of locations, attractions and activities that they had neither actively researched nor planned.

Servitization of manufacturing is characterized by very complex decision processes within strongly unstable and uncertain decision contexts. Decision-makers are face situations of lack of internal and external information. The purpose of this paper is to develop a decision aid approach to support the management of servitization decision-making processes.

The scientific orientation of this research consists in working at improving the efficiency of the servitization decision-making process, by identifying factors of non-reliability, in order to propose remediation actions for the whole process. Improving the final decisions taken by the managers is considered as a consequence of the improvement of the decision-making process reliability. The method, based on modeling and evaluation, requires the specification of a decision process model for servitization, used as a basis to assess decision process reliability and diagnose the enterprise’s servitization decision system. Improving the final decisions made by the managers is considered as a consequence of the improvement of the decision-making process reliability.

Key added values: first, to formalize a servitization decision-making reference model; second, to specify a reliability assessment applied to the decision system; and third, to define a decision process reliability diagnosis procedure for servitization, illustrated in a case study.

A direct perspective is to complete the focus on procedural reliability, by taking into consideration the subjective rationality of decision-makers in the reliability assessment procedure. Additionally, this reliability assessment method and diagnosis could become the basis of a larger risk management approach for servitization.

The diagnosis procedure proposed in the paper is dedicated to generating practical results for enterprise decision-makers, consisting in recommendations for decision process improvements, in the context of servitization. The approach is illustrated through an industrial SME case study. The practical implications are highly contextualized.

The key originality of this research is to tackle servitization complexity with a decision system modeling and diagnosis orientation, including the formalization of the notion of “decision process reliability,” and the specification and implementation of a quantitative assessment procedure.

The paper proposes an innovative systemic method helping decision-makers to control servitization transition process, through decision process risk diagnosis.

The proposed method is based on the modeling of decision processes and risk identification and analysis. This method was based on an action-research approach, in close relationship with two companies (SMEs). The paper develops the feasibility experiment at Automelec company.

The method was successfully implemented and delivered concrete diagnosis results.

The generalization of the applicability of the method needs to be tested on several different cases.

The first practical implication is related to the efficiency of the method to help decision-makers in a servitization context to limit uncertainty and get a global view of the weaknesses of their decision-making process, it raises their awareness about servitization transition for their companies. Furthermore, the method also helps to explain the strategy of a servitization transition. It enhances the level of maturity of the decision process of the company, and can be used as a training/learning tool for managers.

The results brought by the research contribute to give the decision-making boards for organization living a servitization transition and especially SMEs a better control over the servitization decision process and related risks, which will increase the economic stability of the company and its vision over long, medium and short horizons. This will bring positive impact on the overall economic and social environment and networks of the servitized SME, and enhance the confidence of coworkers, subcontractors and clients.

The first originality of the paper is related to the new way of considering risk, not only as an analysis criterion but as the central driver in steering a strategic transition for the company, such as servitization. The second originality of the study is about assessing risk occurrence over a decision-making process through decision reliability and decision confidence.

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.

This study investigates the role of an augmented reality (AR)-based tool in customers' shopping processes.

Using the stimulus-organism-response (SOR) and consumer decision-making models, this study builds a comprehensive theoretical model that investigates the mechanism sequentially connected AR-enabled shopping tool and customer responses. Décor Matters was chosen as the AR-enabled mobile application for this study. Qualtrics, which conducted the survey, collected 150 responses in the USA. The authors used structural equation model to test the hypotheses.

This study enriches the retail-related AR theory by offering a holistic and structural view of the factors that connect customers' cognitive and affective internal processes with customers' shopping task. However, having used only one type of AR-enabled app in the study, the findings remain limited.

This research advances the understanding of AR's role in the customer shopping process by validating the positive effect of immersion on purchase intention, as well as revealing the mediating effect of decision-making quality and the moderating effect of privacy concerns. However, as only one type of AR-enabled app was used in the study, the findings are still limited.

The findings can help retailers to understand why and how firms can benefit from investing in AR-enabled apps (i.e. by focussing on customer perceived immersion and decision-making quality with AR).

This study's originality lies in the SOR model's extension, which integrates the customer decision-making model, allowing for connecting customers' cognitive and affective internal experiences with their shopping task. The findings can help retail managers to understand more clearly and in-depth why and how AR works in customers' shopping process.

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.

The purpose of this paper is to examine Chester Barnard's decisional model utilizing the lens of image theory. The main claim is that the individual decision‐making model proposed by Barnard in his Notes on the Significance of Decisive Behavior can be evaluated within the framework of image theory.

The paper performed a comparative analysis of Barnard's and image theory's models of decision making to outline congruence and incongruence between Barnard's early conceptualization of individual decision making and the contemporary understanding of image theory.

The findings provide support to the claim that image theory is an appropriate framework to describe Barnard's model.

The unique contribution of this study is that it provides the first theoretical analysis of Barnard's model of individual decision making. Barnard's model of individual decision making is little known because it was posthumously published in his Notes on the Significance of Decisive Behavior 35 years after Barnard's death.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.