Search results

Due to the complexity and diversity of megaprojects, the architectural programming process often involves multiple stakeholders, making decision-making difficult and susceptible to subjective factors. This study aims to propose an architectural programming methodology system (APMS) for megaprojects based on group decision-making model to enhance the accuracy and transparency of decision-making, and to facilitate participation and integration among stakeholders. This method allows multiple interest groups to participate in decision-making, gathers various perspectives and opinions, thereby improving the quality and efficiency of architectural programming and promoting the smooth implementation of projects.

This study first clarifies the decision-making subjects, decision objects, and decision methods of APMS based on group decision-making theory and value-based architectural programming methods. Furthermore, the entropy weight method and fuzzy TOPSIS method are employed as calculation methods to comprehensively evaluate decision alternatives and derive optimal decision conclusions. The workflow of APMS consists of four stages: preparation, information, decision, and evaluation, ensuring the scientific and systematic of the decision-making process.

This study conducted field research and empirical analysis on a practical megaproject of a comprehensive transport hub to verify the effectiveness of APMS. The results show that, in terms of both short-distance and long-distance transportation modes, the decision-making results of APMS are largely consistent with the preliminary programming outcomes of the project. However, regarding transfer modes, the APMS decision-making results revealed certain discrepancies between the project's current status and the preliminary programming.

APMS addresses the shortcomings in decision accuracy and stakeholder participation and integration in the current field of architectural programming. It not only enhances stakeholder participation and interaction but also considers various opinions and interests comprehensively. Additionally, APMS has significant potential in optimizing project performance, accelerating project processes, and reducing resource waste.

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 sustainable development of contractor organizations depends highly on bidding decision-making of projects. This current study, leveraging the risk decision-making theory, attempts to elucidate the process of contractors’ bid/no-bid decision-making and reveal how the process is influenced by their perception of risk. In particular, this study aims to explore the multiple mediating effects of contractors’ trust in owners and risk perception in explaining the relationship between contractual governance outlined in owners’ bidding documents and the bid/no-bid decisions.

A questionnaire survey was used to obtain data from the Chinese construction industry. The PLS-SEM technique was employed to analyze a dataset of 557 available questionnaires.

The findings indicate that (1) the contractual governance provided by owners’ bidding documents positively impacts contractors’ bid/no-bid decisions; (2) both risk perception and trust serve as multiple mediators in this relationship and (3) trust mediates the relationship between contractual governance and contractors’ risk perception.

Drawing upon the risk decision-making theory, this study proposes a multiple mediation model for understanding contractors’ bid/no-bid decision-making processes. It contributes to a better understanding of contractors’ bidding decision-making mechanisms, thereby offering theoretical guidance for contractors to make reasonable and informed risk decisions.

In this study, we explored factors driving evidence-based management (EBM) decision-making in Poland which has experienced changes from state-controlled market environments to more competitive ones. Evidence-based management requires the critical use and adaptability to information to deal with complex problems.

In total, 422 Polish managers responded to a telephone survey measuring their perceptions about decision-making culture, styles, competence, and their use of specific sources to derive the evidence to enable them to make evidence-based decisions. Informed by theoretical principles, we used Hayes’ PROCESS macro (Model 4) to examine whether each factor produced direct effects on EBM decision-making and the mediating influence of competence and style in the relationship between culture and perceived evidence-based decision-making.

All three factors correlated positively with perceived evidence-based decision-making. Moreover, style was not predictive of EBM decision-making compared to competence and culture while culture had an imposing effect on decision-making both as a direct effect and indirectly through competence.

This study provides important insights into the perceptual state of EBM among Polish managers. It emphasizes the importance of embracing diverse cultures and improving critical thinking to help managers make more evidence-based decisions during significant changes in the business world.

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 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.

The purpose of this study is to address a critical gap in enterprise resource planning (ERP) implementation process for small and medium-sized enterprises (SMEs) by acknowledging and countering cognitive biases through a cognitive bias awareness matrix model. Cognitive biases such as temporal discounting and optimism bias often skew decision-making, leading SMEs to prioritize short-term benefits over long-term sustainability or underestimate the challenges involved in ERP implementation. These biases can result in costly missteps, underutilizing ERP systems and project failure. This study enhances decision-making processes in ERP adoption by introducing a matrix that allows SMEs to self-assess their level of awareness and proactivity when addressing cognitive biases in decision-making.

The design and methodology of this research involves a structured approach using the problem-intervention-comparison-outcome-context (PICOC) framework to systematically explore the influence of cognitive biases on ERP decision-making in SMEs. The study integrates a comprehensive literature review, empirical data analysis and case studies to develop the Cognitive Bias Awareness Matrix. This matrix enables SMEs to self-assess their susceptibility to biases like temporal discounting and optimism bias, promoting proactive strategies for more informed ERP decision-making. The approach is designed to enhance SMEs’ awareness and management of cognitive biases, aiming to improve ERP implementation success rates and operational efficiency.

The findings underscore the profound impact of cognitive biases and information asymmetry on ERP system selection and implementation in SMEs. Temporal discounting often leads decision-makers to favor immediate cost-saving solutions, potentially resulting in higher long-term expenses due to the lack of scalability. Optimism bias tends to cause underestimating risks and overestimating benefits, leading to insufficient planning and resource allocation. Furthermore, information asymmetry between ERP vendors and SME decision-makers exacerbates these biases, steering choices toward options that may not fully align with the SME’s long-term interests.

The study’s primary limitation is its concentrated focus on temporal discounting and optimism bias, potentially overlooking other cognitive biases that could impact ERP decision-making in SMEs. The PICOC framework, while structuring the research effectively, may restrict the exploration of broader organizational and technological factors influencing ERP success. Future research should expand the range of cognitive biases and explore additional variables within the ERP implementation process. Incorporating a broader array of behavioral economic principles and conducting longitudinal studies could provide a more comprehensive understanding of the challenges and dynamics in ERP adoption and utilization in SMEs.

The practical implications of this study are significant for SMEs implementing ERP systems. By adopting the Cognitive Bias Awareness Matrix, SMEs can identify and mitigate cognitive biases like temporal discounting and optimism bias, leading to more rational and effective decision-making. This tool enables SMEs to shift focus from short-term gains to long-term strategic benefits, improving ERP system selection, implementation and utilization. Regular use of the matrix can help prevent costly implementation errors and enhance operational efficiency. Additionally, training programs designed around the matrix can equip SME personnel with the skills to recognize and address biases, fostering a culture of informed decision-making.

The study underscores significant social implications by enhancing decision-making within SMEs through cognitive bias awareness. By mitigating biases like temporal discounting and optimism bias, SMEs can make more socially responsible decisions, aligning their business practices with long-term sustainability and ethical standards. This shift improves operational outcomes and promotes a culture of accountability and transparency. The widespread adoption of the Cognitive Bias Awareness Matrix can lead to a more ethical business environment, where decisions are made with a deeper understanding of their long-term impacts on employees, customers and the broader community, fostering trust and sustainability in the business ecosystem.

This research introduces the original concept of the Cognitive Bias Awareness Matrix, a novel tool designed specifically for SMEs to evaluate and mitigate cognitive biases in ERP decision-making. This matrix fills a critical gap in the existing literature by providing a structured, actionable framework that effectively empowers SMEs to recognize and address biases such as temporal discounting and optimism bias. Its practical application promises to enhance decision-making processes and increase the success rates of ERP implementations. This contribution is valuable to behavioral economics and information systems, offering a unique approach to integrating cognitive insights into business technology strategies.

Female smallholder farmers in low-income countries face barriers to accessing capital and commodity markets. While agricultural cooperatives provide services that contribute to the income and productivity of small-scale producers, evidence of cooperatives' social and economic empowerment of female smallholders remains limited. We apply Sen's capability approach to female entrepreneurs' socioeconomic empowerment to examine whether women's participation in a coffee and microfinance cooperative from rural western Uganda benefits their social and economic position within their household. First, we study the relationship between women's cooperative participation and their household coffee sales and savings. Second, we investigate the link between women's cooperative participation and their intra-household decision-making and whether the inclusion of the husband in his wife's cooperative strengthens or lowers women's decision-making power.

We carry out a case study of a hybrid coffee and microfinance cooperative that promotes social innovation through the integration and empowerment of female smallholders in rural Uganda. Using a cross-sectional survey of 411 married female cooperative members from 26 randomly selected self-help groups of Bukonzo Joint Cooperative and 196 female non-members from the identical area, employing propensity score matching, this paper investigates the benefits of women's participation in a coffee and microfinance cooperative in the Rwenzori Mountains of western Uganda. We present and discuss the results of our case study within an extensive literature on the role of institutions in collective action for women's empowerment.

Our findings provide new empirical evidence on female smallholders' participation in mixed cooperatives. Our results indicate that women's participation in microfinance-producer cooperatives appears to be a conditional blessing: even though membership is linked to increased women's intra-household decision-making and raised household savings and income from coffee sales, a wife with a husband in the same cooperative self-help group is associated with diminished women's household decision-making power.

The focus of this study is on female coffee smallholders in an agricultural cooperative in rural western Uganda. In particular, we focus on a case study of one major coffee cooperative. Our cross-sectional survey does not allow us to infer causal interpretations. Also, the survey does not include variables that allow us to measure other dimensions of women's empowerment beyond decision-making over household expenditures and women's financial performance related to savings and income from coffee cultivation.

Our empirical results indicate that female smallholders' cooperative membership is associated with higher incomes and coffee sales. However, husband co-participation in their wives' cooperative group diminishes wives' decision-making, which suggests that including husbands and other family members in the same cooperative group may not be perceived as an attractive route to empowerment for female smallholders. For these reasons, an intervention that encourages the cooperation of both spouses and that is sensitive to context-specific gender inequalities, may be more successful at stimulating social change toward household gender equality than interventions that focus on women's autonomous spheres only.

While the literature thus far has focused on microfinance's potential for women's empowerment, evidence on agricultural cooperatives' affecting women's social and economic position is limited. First, our findings provide novel empirical evidence on the empowering effects of women's participation in a self-help group-based coffee cooperative in rural Uganda. Second, our data allows us to explore the role of husbands' participation in their wives' cooperative and SGH. We embed our hypotheses and empirical results in a rich discussion of female entrepreneurship, microfinance and cooperative literature.

This paper aims to propose an accurate and efficient decision-making process adapted to the specific context of Claim Management situations, implying partners engaged in a high-involvement relationship.

We used a three-step approach: first, an inductive phase based on 12 past case studies. Second, a theory-building phase. Third, a theory-testing phase based on an ongoing case study to observe and test our propositions.

Proposal 1: Partner’s Strategic Value is an influential decision parameter that must be incorporated into Claim Management-related decision-making processes in high-involvement relationships. Proposal 2: The Fast-and-Frugal Heuristic is adapted to the intense, interactive and iterative nature of the Claim Management context. Our final proposal combines these two findings, i.e. a Fast-and-Frugal Heuristic incorporating the Partner’s Strategic Value and based on using decision criteria as a sequence, not simultaneously.

In the context of high-involvement business relationships and Claim Management, this study introduces the importance of selecting an appropriate decision methodology and integrating a strategic decision parameter (Partner’s Strategic Value) into an operational decision-making context. Furthermore, the principle of considering decision parameters in a specific sequence corresponds to the iterative and interactive nature of the Claim Management processes.

The authors study how cloud adoption decision making unfolds in organizations and present the dynamic process leading to a decision to adopt or reject cloud computing. The authors thus complement earlier literature on factors that influence cloud adoption.

The authors adopt an interpretive epistemology to understand the process of cloud adoption decision making. Following an empirical investigation drawing on interviews with senior managers who led the cloud adoption decision making in organizations from across Europe. The authors outline a framework that shows how cloud adoptions follow multiple cycles in three broad phases.

The study findings demonstrate that cloud adoption decision making is a recursive process of learning about cloud through three broad phases: building perception about cloud possibilities, contextualizing cloud possibilities in terms of current computing resources and exposing the cloud proposition to others involved in making the decision. Building on these findings, the authors construct a framework of this process which can inform practitioners in making decisions on cloud adoption.

This work contributes to authors understanding of how cloud adoption decisions unfold and provides a framework for cloud adoption decisions that has theoretical and practical value. The study further demonstrates the role of the decision-leader, typically the CIO, in this process and identifies how other internal and external stakeholders are involved. It sheds light on the relevance of the phases of the cloud adoption decision-making process to different cloud adoption factors identified in the extant literature.