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Open Access
Article
Publication date: 6 April 2021

Beichen Liang

The purpose of this study is to investigate whether, in the context of making a go/no-go decision regarding a failing new product, the use of a stopping rule and/or a new…

Abstract

Purpose

The purpose of this study is to investigate whether, in the context of making a go/no-go decision regarding a failing new product, the use of a stopping rule and/or a new decision-maker would reduce the escalation of commitment (EOC).

Design/methodology/approach

This study uses a classroom experiment design and uses logistic regression and a chi-square test to analyze its data.

Findings

The findings show that both responsible and non-responsible participants are more likely to perceive the negative performance of a new product as less negative and believe that the goal for the product can be reached when there is a stopping rule and proximal negative feedback indicates a level of performance below but very close to it than when there is no stopping rule. Therefore, they are more likely to continue the failing new product, whether they are responsible for the product or not. However, non-responsible decision-makers are more likely than their responsible counterparts to discontinue the failing new product in the absence of a stopping rule.

Research limitations/implications

This paper extends the theory of EOC by showing that the use of a stopping rule and/or a new decision-maker may not reduce EOC.

Practical implications

This paper provides useful guidelines for managers on how to reduce EOC.

Originality/value

The originality and value of this paper are found in the investigation of a situation in which the use of a stopping rule and/or a new decision-maker may not reduce the EOC.

Details

Innovation & Management Review, vol. 18 no. 3
Type: Research Article
ISSN: 2515-8961

Keywords

Open Access
Article
Publication date: 12 February 2019

Deybbi Cuéllar-Molina, Antonia Mercedes García-Cabrera and Ma de la Cruz Déniz-Déniz

The purpose of this paper is to examine the influence of the emotional intelligence (EI) of the person in charge of making human resource management (HRM) decisions on the…

15243

Abstract

Purpose

The purpose of this paper is to examine the influence of the emotional intelligence (EI) of the person in charge of making human resource management (HRM) decisions on the adoption of high-performance human resource (HR) practices in small- and medium-sized enterprises (SMEs).

Design/methodology/approach

This study takes evidences from 157 HR decision makers in SMEs who autonomously make the decisions in the HR area and were responsible for the HR practices in their firm. The authors used multiple linear regression analysis to test the hypotheses.

Findings

Results show that both the EI and the different EI competencies of which it is comprised affect the adoption of various HR practices. Thus, the main theoretical contribution of this work stems from the incorporation of a psychological variable (EI) as an antecedent of HRM. Managers of the SME will find guidance about which emotional competencies are the most important for them to be more successful in their roles and for improving HRM.

Research limitations/implications

First, the sample of firms the authors studied is limited to a specific geographic area in one country – Spain (Canary Islands) – that will necessarily limit generalisation of the results obtained to other populations of SMEs. Researchers should replicate the current model in other geographic areas. Second, and with regard the methodology, researchers could explore other tools to measure EI and emotional competencies. It would be interesting to measure this construct using qualitative analytical techniques, with 360 – or 180 – degree tools. Finally, the current study is cross-sectional in nature, which limits our ability to draw causal inferences from the data. This cross-sectional design prevents us, for example, from analysing EI’s influence on the continued development of high-performance HR practices over time. Future research using longitudinal methodologies to study these variables could provide additional advances in this area. This work makes important contributions to both the literature and the business world. With regard to the theoretical implications, results confirm that EI as a whole, as well as in terms of its specific emotional competencies, affects the decision making related to the adoption of high-performance HR practices, which is known to contribute to the organisational performance.

Practical implications

With regard its practical implications, SMEs’ owners-managers and HR practitioners may find our results and conclusions interesting. Indeed, recommendations in business management have often been accompanied by new approaches in HRM (Kent, 2005), as this study proposes. In particular, managers will find evidence of how a decision-maker’s higher EI propitiates the adoption of high-performance HR practices, thus being able to improve HRM in their SMEs. Moreover, managers will obtain guidance on which emotional competencies are the most important for adopting each HR practice, and so find greater success in their HRM roles. SMEs could organise programmes to develop the HR decision-maker’s emotional competencies, as large firms do for their executives.

Originality/value

Thus, the main theoretical contribution of this work stems from the incorporation of a psychological variable (EI) as an antecedent of HRM. Managers of the SME will find guidance about which emotional competencies are the most important for them to be more successful in their roles and for improving HRM.

Details

European Journal of Management and Business Economics, vol. 28 no. 1
Type: Research Article
ISSN: 2444-8494

Keywords

Content available
Article
Publication date: 7 November 2018

Nathan Parker, Jonathan Alt, Samuel Buttrey and Jeffrey House

This research develops a data-driven statistical model capable of predicting a US Army Reserve (USAR) unit staffing levels based on unit location demographics. This model provides…

Abstract

Purpose

This research develops a data-driven statistical model capable of predicting a US Army Reserve (USAR) unit staffing levels based on unit location demographics. This model provides decision makers an assessment of a proposed station location’s ability to support a unit’s personnel requirements from the local population.

Design/methodology/approach

This research first develops an allocation method to overcome challenges caused by overlapping unit boundaries to prevent over-counting the population. Once populations are accurately allocated to each location, we then then develop and compare the performance of statistical models to estimate a location’s likelihood of meeting staffing requirements.

Findings

This research finds that local demographic factors prove essential to a location’s ability to meet staffing requirements. We recommend that the USAR and US Army Recruiting Command (USAREC) use the logistic regression model developed here to support USAR unit stationing decisions; this should improve the ability of units to achieve required staffing levels.

Originality/value

This research meets a direct request from the USAREC, in conjunction with the USAR, for assistance in developing models to aid decision makers during the unit stationing process.

Details

Journal of Defense Analytics and Logistics, vol. 2 no. 2
Type: Research Article
ISSN: 2399-6439

Keywords

Open Access
Article
Publication date: 28 October 2022

Diqian Ren, Jun-Ki Choi and Kellie Schneider

Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the…

1474

Abstract

Purpose

Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.

Design/methodology/approach

The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.

Findings

To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.

Originality/value

This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

Details

Rapid Prototyping Journal, vol. 28 no. 11
Type: Research Article
ISSN: 1355-2546

Keywords

Open Access
Article
Publication date: 9 September 2022

Mirella Bezerra Garcia, Renata Magalhaes Oliveira, Mariusa Momenti Pitelli and Jose Vieira

This paper aims to propose a methodology for managerial decision-making based on scenario planning and a multi-criteria approach.

Abstract

Purpose

This paper aims to propose a methodology for managerial decision-making based on scenario planning and a multi-criteria approach.

Design/methodology/approach

The methodology consists of two stages, one referring to scenario planning and the other to multi-criteria decision-making. The methodology was applied to a company in the Brazilian agribusiness sector, aiming to help managers face the current situation of the COVID-19 pandemic.

Findings

The proposal addresses a set of simple methods for developing a scenario analysis based on different approaches. Although the methodology may allow the future addition of new, perhaps more robust strategies, the purpose of the analysis is not only to tell the decision maker which strategy should be adopted, but also to provide greater knowledge about the problem and possible scenarios.

Originality/value

The contribution of this research is to propose a structured and easily applicable methodology that can help managers in the future planning of their companies, especially when faced with complex decisions and high level of uncertainty.

Details

Revista de Gestão, vol. 30 no. 3
Type: Research Article
ISSN: 1809-2276

Keywords

Open Access
Article
Publication date: 23 February 2024

Sarah Mueller-Saegebrecht

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…

477

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Practical implications

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.

Originality/value

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.

Details

Management Decision, vol. 62 no. 13
Type: Research Article
ISSN: 0025-1747

Keywords

Open Access
Article
Publication date: 27 May 2021

Ilaria Galavotti, Andrea Lippi and Daniele Cerrato

This paper aims to develop a conceptual framework on how the representativeness heuristic operates in the decision-making process. Specifically, the authors unbundle…

4393

Abstract

Purpose

This paper aims to develop a conceptual framework on how the representativeness heuristic operates in the decision-making process. Specifically, the authors unbundle representativeness into its building blocks: search rule, stopping rule and decision rule. Furthermore, the focus is placed on how individual-level cognitive and behavioral factors, namely experience, intuition and overconfidence, affect the functioning of this heuristic.

Design/methodology/approach

From a theoretical standpoint, the authors build on dual-process theories and on the adaptive toolbox view from the “fast and frugal heuristics” perspective to develop an integrative conceptual framework that uncovers the mechanisms underlying the representativeness heuristic.

Findings

The authors’ conceptualization suggests that the search rule used in representativeness is based on analogical mapping from previous experience, the stopping rule is the representational stability of the analogs and the decision rule is the choice of the alternative upon which there is a convergence of representations and that exceeds the decision maker's aspiration level. In this framework, intuition may help the decision maker to cross-map potentially competing analogies, while overconfidence affects the search time and costs and alters both the stopping and the decision rule.

Originality/value

The authors develop a conceptual framework on representativeness, as one of the most common, though still poorly investigated, heuristics. The model offers a nuanced perspective that explores the cognitive and behavioral mechanisms that shape the use of representativeness in decision-making. The authors also discuss the theoretical implications of their model and outline future research avenues that may further contribute to enriching their understanding of decision-making processes.

Details

Management Decision, vol. 59 no. 7
Type: Research Article
ISSN: 0025-1747

Keywords

Content available
Article
Publication date: 14 March 2022

Aruna Apte, Scott Chirgwin, Ken Doerr and Davis Katakura

Vertical lift (VL) assets are vital and expensive resources in humanitarian missions. What and where supplies are needed evolves in short time following a disaster. The purpose of…

Abstract

Purpose

Vertical lift (VL) assets are vital and expensive resources in humanitarian missions. What and where supplies are needed evolves in short time following a disaster. The purpose of this paper is to offer analysis to understand the range of capabilities of these assets.

Design/methodology/approach

The authors use scenario analysis to investigate the tradeoff between two key capabilities of VL, agility and speed. The authors do this by generating loads and distances randomly, based on historical data. In post hoc analysis, based on different factors, the authors investigate the impact of configuration of Expeditionary Strike Force (ESG) on providing disaster relief.

Findings

The authors find the most effective deployment of VL in a HADR mission is in supplying essentials to victims in a focused region. Delivering sustainment requirements leads to substantial shortfall for survival needs. If the configuration of the ESGs were changed for HADR, it would better-meet the demand.

Research limitations/implications

Cargo capacity is modeled assuming every aircraft type was equal, in terms of mean and variance of cargo-capacity utilization. Detailed information on cargo-bay configurations was beyond the scope of our model and data. However, this means the benefit of standardizing cargo load-outs and the variability associated with randomized load-outs may be understated in the results.

Practical implications

The analysis presents decision-makers with projections of VL asset performance in the early stages of disaster relief, to assist in planning and contingency planning.

Originality/value

This research deals exclusively with the most critical but expensive capabilities for HADR: VL. The in-depth analysis illustrates the limitations and benefits of this capability.

Details

Journal of Defense Analytics and Logistics, vol. 6 no. 1
Type: Research Article
ISSN: 2399-6439

Keywords

Open Access
Article
Publication date: 13 February 2024

Felipa de Mello-Sampayo

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these…

Abstract

Purpose

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

Design/methodology/approach

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Findings

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

Practical implications

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Social implications

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

Originality/value

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

Details

Journal of Economic Studies, vol. 51 no. 9
Type: Research Article
ISSN: 0144-3585

Keywords

Open Access
Article
Publication date: 13 May 2021

Devin DePalmer, Steven Schuldt and Justin Delorit

Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with…

1077

Abstract

Purpose

Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with strategic objectives. Traditional facility prioritization methods using risk matrices can be improved to increase granularity in categorization and avoid mathematical error or human cognitive biases. These limitations restrict the utility of prioritizations and if erroneously used to select projects for funding, they can lead to wasted resources. This paper aims to propose a novel facility prioritization methodology that corrects these assessment design and implementation issues.

Design/methodology/approach

A Mamdani fuzzy logic inference system is coupled with a traditional, categorical risk assessment framework to understand a facilities’ consequence of failure and its effect on an organization’s strategic objectives. Model performance is evaluated using the US Air Force’s facility portfolio, which has been previously assessed, treating facility replicability and interruptability as minimization objectives. The fuzzy logic inference system is built to account for these objectives, but as proof of ease-of-adaptation, facility dependency is added as an additional risk assessment criterion.

Findings

Results of the fuzzy logic-based approach show a high degree of consistency with the traditional approach, though the value of the information provided by the framework developed here is considerably higher, as it creates a continuous set of facility prioritizations that are unbiased. The fuzzy logic framework is likely suitable for implementation by diverse, spatially distributed organizations in which decision-makers seek to balance risk assessment complexity with an output value.

Originality/value

This paper fills the identified need for portfolio management strategies that focus on prioritizing projects by risk to organizational operations or objectives.

Details

Journal of Facilities Management , vol. 19 no. 3
Type: Research Article
ISSN: 1472-5967

Keywords

1 – 10 of over 3000