Enhancing decision-making with data quality metadata

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
G. Shankaranarayanan ◽  
Bin Zhu
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Data Quality ◽  
Sample Size ◽  
Task Complexity ◽  
Decision Makers ◽  
Cognitive Capacity ◽  
Content Type ◽  
Decision Performance ◽  
Cognitive Overload

Purpose Data quality metadata (DQM) is a set of quality measurements associated with the data. Prior research in data quality has shown that DQM improves decision performance. The same research has also shown that DQM overloads the cognitive capacity of decision-makers. Visualization is a proven technique to reduce cognitive overload in decision-making. This paper aims to describe a prototype decision support system with a visual interface and examine its efficacy in reducing cognitive overload in the context of decision-making with DQM. Design/methodology/approach The authors describe the salient features of the prototype and following the design science paradigm, this paper evaluates its usefulness using an experimental setting. Findings The authors find that the interface not only reduced perceived mental demand but also improved decision performance despite added task complexity due to the presence of DQM. Research limitations/implications A drawback of this study is the sample size. With a sample size of 51, the power of the model to draw conclusions is weakened. Practical implications In today’s decision environments, decision-makers deal with extraordinary volumes of data the quality of which is unknown or not determinable with any certainty. The interface and its evaluation offer insights into the design of decision support systems that reduce the complexity of the data and facilitate the integration of DQM into the decision tasks. Originality/value To the best of my knowledge, this is the only research to build and evaluate a decision-support prototype for structured decision-making with DQM.

Virtual reality-based decision support model for interior design and decoration of an office building

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Kai Juan ◽  
Hao-Yun Chi ◽  
Hsing-Hung Chen
Keyword(s):  
Decision Making ◽  
Virtual Reality ◽  
Decision Support ◽  
Decision Support System ◽  
Interior Design ◽  
Support System ◽  
Decision Makers ◽  
Office Building ◽  
Design Decision ◽  
Content Type

Purpose The purpose of this paper is to develop a virtual reality (VR)-based and user-oriented decision support system for interior design and decoration. The four-phase decision-making process of the system is verified through a case study of an office building. Design/methodology/approach Different “spatial layouts” are presented by VR for users to decide their preference (Phase 1). According to the selected spatial layout, a “spatial scene” is constructed by VR and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to determine the spatial scene preference (Phase 2). Based on the binary integer programming method, the system provides the optimal preliminary solution under a limited decoration budget (Phase 3). Finally, the consistency between the overall color scheme and pattern is fine-tuned by VR in order to obtain the final solution (Phase 4). Findings The questionnaire survey results show that decision makers generally affirm the operation and application of VR, and especially recognize the advantages in the improvement of VR-based interior design feasibility, communication efficiency and design decision-making speed. The optimization of the costs and benefits enables decision makers to effectively evaluate the impact of design decisions on subsequent project implementation during the preliminary design process. Originality/value The VR-based decision support system for interior design retains the original immersive experience of VR, and offers a systematic multiple criteria decision- making and operations research optimization method, thus, providing more complete decision-making assistance. Compared with traditional design communication, it can significantly reduce cognitive differences and improve decision-making quality and speed.

Shifting the burden archetype: developing a system dynamics game

2015 ◽  
Vol 10 (3) ◽  
pp. 380-395 ◽  
Author(s):  
Virupaxi Bagodi ◽  
Biswajit Mahanty
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
System Dynamics ◽  
Fundamental Solutions ◽  
Decision Makers ◽  
Strategic Decisions ◽  
Content Type ◽  
Complex Decision Making ◽  
Two Wheeler

Purpose – The purpose of the paper is to demonstrate the short comings in decision-making in a complex system. An approach to coping with a complex decision-making task is to identify generic structures known as systems archetypes in a given decision situation. In the “shifting the burden” archetype, decision-makers fail to identify the fundamental solution early and are subjected to accumulated side effects as they resort to quick remedial solutions. Design/methodology/approach – A system dynamics-based game has been built to highlight the pitfalls of “shifting the burden” systems archetype for a decision-making situation in the Indian two-wheeler industry. Participants of the game make strategic decisions for a company and receive feedback of their decisions and corresponding actions after every plan period. Findings – The decision-makers who adopt short-term measures to alleviate the company’s problems, invariably fail in their endeavour. Success comes to those who realize the importance of having a long-term perspective in the form of pursuing fundamental solutions. Practical implications – What could be a possible way of avoiding the pitfalls? The decision-makers should be aware of the pitfalls beforehand and identify the same – a decision support system possibly can aid them in this regard. Originality/value – The complexity of the system increases as the business grows. The managers need to adopt systems thinking and embrace a long-term perspective. Decision support systems integrating models of systems archetypes provide an environment to simulate various decision situations and see the effects beforehand.

A decision support system for technician routing with time windows

2019 ◽  
Vol 32 (2) ◽  
pp. 138-158
Author(s):  
Elyn Lizeth Solano Charris ◽  
Jairo Rafael Montoya-Torres ◽  
William Guerrero-Rueda
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Time Windows ◽  
Real Life ◽  
Route Planning ◽  
Decision Makers ◽  
Two Stage ◽  
Content Type

Purpose The purpose of this paper is to present a decision support system (DSS) for a Colombian public utility company in order to aid decision-making at the operational level regarding route planning and travel time. The aim is to provide a tool to assist technicians that perform interruption and reconnection of domiciliary services for about 2,000 customers a day. Design/methodology/approach The real-life problem is modeled as a Single Depot Vehicle Routing Problem with Time Windows (SDVRP-TW), which is a well-known optimization problem in Operations Research/Management Science. A two-stage approach integrated into decision-making software is provided. The first stage considers the clustering of customers generated by a combination of the sweep and the k-means algorithms, while the second phase plans the routing of technicians using the nearest-neighbor and the Or-opt heuristics. The proposed approach is tested using real data sets. Findings In comparison with the current route planning approach, the proposed method is able to obtain savings in total travel times, improving operational productivity by 22.2 percent. Research limitations/implications Since the analysis is carried out based on mathematical modeling, assumptions about the relationships between variables and elements of the actual complex problem might be simplified. Although the proposed approach aids the route planning, decision makers make the final decisions. Practical implications The proposed DSS has a critical impact on actual operational practices at the company. Productivity and service level are improved, while reducing operational costs. The decision-making process itself will be improved so technicians and higher decision makers can focus on performing other tasks. Originality/value The real-life problem is modeled using mathematical programming and efficiently solved through a two-stage approach based on simple, quite intuitive, solution procedures that have not been implemented for such services. In addition, as actual data from the company is employed for experimental purposes, the solution approach is tested and its efficiency and efficacy are both validated in a realistic setting, hence providing realistic behavior for decision makers at the company.

scholarly journals A Multi-Criteria Decision Support Concept for Selecting the Optimal Contractor

2021 ◽  
Vol 11 (4) ◽  
pp. 1660 ◽  
Author(s):  
Ivan Marović ◽  
Monika Perić ◽  
Tomaš Hanak
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Project Performance ◽  
Decision Makers ◽  
Construction Project Management ◽  
Analytic Hierarchy ◽  
Conflicting Demands ◽  
Decision Making Problem ◽  
Scientific Approach ◽  
Hierarchy Process

A way to minimize uncertainty and achieve the best possible project performance in construction project management can be achieved during the procurement process, which involves selecting an optimal contractor according to “the most economically advantageous tender.” As resources are limited, decision-makers are often pulled apart by conflicting demands coming from various stakeholders. The challenge of addressing them at the same time can be modelled as a multi-criteria decision-making problem. The aim of this paper is to show that the analytic hierarchy process (AHP) together with PROMETHEE could cope with such a problem. As a result of their synergy, a decision support concept for selecting the optimal contractor (DSC-CONT) is proposed that: (a) allows the incorporation of opposing stakeholders’ demands; (b) increases the transparency of decision-making and the consistency of the decision-making process; (c) enhances the legitimacy of the final outcome; and (d) is a scientific approach with great potential for application to similar decision-making problems where sustainable decisions are needed.

The hidden power of language

2020 ◽  
Vol 11 (1) ◽  
pp. 187-206
Author(s):  
Philipp Hummel ◽  
Jacob Hörisch
Keyword(s):  
Decision Making ◽  
Value Creation ◽  
Cost Reduction ◽  
Social Consequences ◽  
Decision Makers ◽  
Social Aspects ◽  
Social Aspect ◽  
Content Type ◽  
Current Accounting ◽  
Cost Reductions

Purpose Stakeholder theory research identifies changes in language as one possible mechanism to overcome the deficiencies of current accounting practices with regard to social aspects. This study aims to examine the effects of the terms used for specific accounts on company internal decision-making, drawing on the example of “value creation accounting”. Design/methodology/approach The study uses a survey based-experiment to analyze the effects of terms used for specific accounts on decision-making, with a focus on social aspects (in particular expenditures for staff) in cost reduction and expenditure decisions. Findings The findings indicate that wordings, which more closely relate to value creation than to costs, decrease cost reductions and increase the priority ascribed to the social aspect of reducing staff costs in times of financial shortage. The effects of terms used on cost reductions are stronger among female decision makers. Practical implications The analysis suggests that conventional accounting language best suits organizations that aim at incentivizing decision makers to primarily cut costs. By contrast, if an organization follows an approach that puts importance on social aspects in times of financial shortage and on not doing too sharp cost reductions, value creation-oriented language is the more effective approach. Social implications The study suggests that the specific terminology used for accounts should be chosen more carefully and with awareness for the possible effects on cost reduction decisions as well as on social consequences. Originality/value This study contributes to a better understanding of the relevance of language in accounting. It suggests that the terms used for accounts should be chosen purposefully because of their far-reaching potential consequences for stakeholders as well as for the organization.

The role of agency in project initiation decisions

2014 ◽  
Vol 7 (3) ◽  
pp. 518-535 ◽  
Author(s):  
Mark Mullaly
Keyword(s):  
Decision Making ◽  
Decision Rules ◽  
Personal Characteristics ◽  
Decision Makers ◽  
Organizational Dynamics ◽  
Substantive Theory ◽  
Content Type ◽  
The Subject ◽  
Board Level

Purpose – The purpose of this paper is to explore the role of decision rules and agency in supporting project initiation decisions, and the influences of agency on decision-making effectiveness. Design/methodology/approach – The study this paper is based upon used grounded theory methodology, and sought to understand the influences of individual decision makers on project initiation decisions within organizations. Data collection involved 28 participants who were involved in project initiation decisions within their organizations, who discussed the process of project initiation in their organization and their role within that process. Findings – The study demonstrates that the overall effectiveness of project initiation decisions is a product of agency, process effectiveness or rule effectiveness. The employment of agency can have a direct influence on decision-making effectiveness, it can compensate for organizational inadequacies of a process or political nature, and it can be constrained in the evidence of formal and effective organizational practices. Research limitations/implications – While agency was recognized by all participants, there are clearly circumstances where actors perceive the ability to exercise agency to be externally constrained. The study is exploratory, contributing to the development of substantive theory. Theory testing as well as a more in-depth investigation of the underlying drivers of agency would be valuable. Practical implications – The study provides executives and individuals supporting the initiation of projects with insights on how to effectively influence the effectiveness of project initiation decisions, and the degree to which personal characteristics influence organizational dynamics. Originality/value – Most discussions of agency has been framed the subject as an executive- or board-level phenomenon. The current study demonstrates that agency is in fact being perceived and operationalized at all levels. Those demonstrating agency in the majority of instances in this study do so in exercising stewardship behaviours. This has important implications for how agency is perceived by executives, and by how agency is exercised by actors at all levels of the organization.

ERP software selection using intuitionistic fuzzy and interval grey number-based MACBETH method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mustafa Said Yurtyapan ◽  
Erdal Aydemir
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Selection Process ◽  
Intuitionistic Fuzzy Set ◽  
Decision Makers ◽  
Software Selection ◽  
Content Type ◽  
Intuitionistic Fuzzy ◽  
Expert Opinions ◽  
Erp Software

PurposeEnterprise Resource Planning (ERP) software which is a knowledge-based design on the interconnective communication of business units and information share, ensures that business processes such as finance, production, purchasing, sales, logistics and human resources, are integrated and gathered under one roof. This integrated system allows the company to make fast and accurate decisions and increases its competitiveness. Therefore, for an enterprise, choosing the suitable ERP software is extremely important. The aim of this study is to present new research on the ERP software selection process by clarifying the uncertainties and find suitable software in a computational way.Design/methodology/approachERP selection problem design includes uncertainties on the expert opinions and the criteria values using intuitionistic fuzzy set theory and interval grey-numbers to MACBETH multi criteria decision making method. In this paper, a new interval grey MACBETH method approach is proposed, and the degree of greyness approach is used for clarifying the uncertainties. Using this new approach in which grey numbers are used, it is aimed to observe the changes in the importance of the alternatives. Moreover, the intuitionistic fuzzy set method is applied by considering the importance of expert opinions separately.FindingsThe proposed method is based on quantitative decision making derived from qualitative judgments. The results given under uncertain conditions are compared with the results obtained under crisp conditions of the same methods. With the qualitative levels of experts reflected in the decision process, it is clearly seen that ERP software selection problem area has more effective alternative decision solutions to the uncertain environment, and decision makers should not undervalue the unsteadiness of criteria during ERP software selection process.Originality/valueThis study contributes to the relevant literature by (1) utilizing the MACBETH method in the selection of the ERP software by optimization, and (2) validating the importance of expert opinions with uncertainties on a proper ERP software selection procedure. So, the findings of this study can help the decision-makers to evaluate the ERP selection in uncertain conditions.

Jumping to conclusions – an analysis of the NBA Draft Combine athleticism data and its influence on managerial decision-making

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tobias Berger ◽  
Frank Daumann
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Predictive Power ◽  
Principal Component ◽  
Decision Makers ◽  
Decision Quality ◽  
Managerial Behavior ◽  
Managerial Decision ◽  
Content Type ◽  
Selection Behavior

PurposeThe NBA Draft policy pursues the goal to provide the weakest teams with the most talented young players to close the gap to the superior competition. But it hinges on appropriate talent evaluation skills of the respective organizations. Research suggests the policy might be valid but to date unable to produce its intended results due to the “human judgement-factor”. This paper investigates specific managerial selection-behavior-influencing information to examine why decision-makers seem to fail to constantly seize the opportunities the draft presents them with.Design/methodology/approachAthleticism data produced within the NBA Draft Combine setting is strongly considered in the player evaluations and consequently informs the draft decisions of NBA managers. Curiously, research has failed to find much predictive power within the players pre-draft combine results for their post-draft performance. This paper investigates this clear disconnect, by examining the pre- and post-draft data from 2000 to 2019 using principal component and regression analysis.FindingsEvidence for an athletic-induced decision-quality-lowering bias within the NBA Draft process was found. The analysis proves that players with better NBA Draft Combine results tend to get drafted earlier. Controlling for position, age and pre-draft performance there seems to be no proper justification based on post-draft performance for this managerial behavior. This produces systematic errors within the structure of the NBA Draft process and leads to problematic outcomes for the entire league-policy.Originality/valueThe paper delivers first evidence for an athleticism-induced decision-making bias regarding the NBA Draft process. Informing future selection-behavior of managers this research could improve NBA Draft decision-making quality.

Regulatory focus and construal level theory on low-income consumer indebtedness: Evidence from an emerging market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Patrícia de Oliveira Campos ◽  
Marconi Freitas da Costa
Keyword(s):  
Decision Making ◽  
Low Income ◽  
Regulatory Focus ◽  
Task Complexity ◽  
Emerging Market ◽  
Psychological Distance ◽  
Construal Level Theory ◽  
Construal Level ◽  
Content Type ◽  
Low Income Consumers

PurposeThis study aims to further analyse the decision-making process of low-income consumer from an emerging market by verifying the influence of regulatory focus and construal level theory on indebtedness.Design/methodology/approachAn experimental study was carried out with a design 2 (regulatory focus: promotion vs prevention) × 2 (psychological distance: high vs low) between subjects, with 140 low-income consumers.FindingsOur study points out that the propensity towards indebtedness of low-income consumer is higher in a distal psychological distance. We found that promotion and prevention groups have the same propensity to indebtedness. Moreover, we highlight that low-income consumers are prone to propensity to indebtedness due to taking decisions focused on the present with an abstract mindset.Social implicationsFinancial awareness advertisements should focus on providing more concrete strategies in order to reduce decision-making complexity and provide ways to reduce competing situations that could deplete self-regulation resources. Also, public policy should organize educational programs to increase the low-income consumer's ability to deal with personal finances and reduce this task complexity. Finally, educational financial programs should also incorporate psychology professionals to teach mindfulness techniques applied to financial planning.Originality/valueThis study is the first to consider regulatory focus and construal level to explain low-income indebtedness. This paper provides a deeper analysis of the low-income consumers' decision process. Also, it supports and guides future academic and decision-making efforts.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

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