A Contingency Perspective for Knowledge Management Solutions in Different Decision-Making Contexts

2021 ◽  
pp. 1242-1257
Author(s):  
Kursad Ozlen ◽  
Meliha Handzic
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Decision Makers ◽  
Superior Performance ◽  
Partial Support ◽  
Contingency Perspective ◽  
And Performance ◽  
Contingency View ◽  
The Impact ◽  
Best Fit

A contingency perspective of knowledge management, as one of the popular ways of promoting decision making capabilities, recognizes the need for a fit between knowledge management solutions (KMS) and decision-making contexts which they support. In order to determine the best fit, a field survey was carried out to investigate the impact of two different types of KMS (technical and social) on decision makers' behavior and performance in different decision contexts (simple and complex). According to the results, there is a partial support for the contingency view. As expected, social KMS appears as the best fit for complex contexts, based on subjects' superior performance from comparable adoption of both KMS. In contrast, the results suggest that both KMS were an equally good fit for simple contexts, based on similar levels of subjects' performance, but social KMS was preferred in terms of adoption. These findings contribute to much necessary empirical evidence for research and provide useful guidance for practice. However, their limitations necessitate further study.

A Contingency Perspective for Knowledge Management Solutions in Different Decision-Making Contexts

2019 ◽  
pp. 62-77
Author(s):  
Kursad Ozlen ◽  
Meliha Handzic
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Decision Makers ◽  
Superior Performance ◽  
Partial Support ◽  
Contingency Perspective ◽  
And Performance ◽  
Contingency View ◽  
The Impact ◽  
Best Fit

A contingency perspective of knowledge management, as one of the popular ways of promoting decision making capabilities, recognizes the need for a fit between knowledge management solutions (KMS) and decision-making contexts which they support. In order to determine the best fit, a field survey was carried out to investigate the impact of two different types of KMS (technical and social) on decision makers' behavior and performance in different decision contexts (simple and complex). According to the results, there is a partial support for the contingency view. As expected, social KMS appears as the best fit for complex contexts, based on subjects' superior performance from comparable adoption of both KMS. In contrast, the results suggest that both KMS were an equally good fit for simple contexts, based on similar levels of subjects' performance, but social KMS was preferred in terms of adoption. These findings contribute to much necessary empirical evidence for research and provide useful guidance for practice. However, their limitations necessitate further study.

A Contingency Approach to Knowledge Management

2016 ◽  
Vol 12 (1) ◽  
pp. 31-44 ◽  
Author(s):  
Meliha Handzic ◽  
Kursad Ozlen ◽  
Nermina Durmic
Keyword(s):  
Knowledge Management ◽  
Field Survey ◽  
Decision Makers ◽  
Superior Performance ◽  
Different Types ◽  
And Performance ◽  
Contingency View ◽  
The Impact ◽  
Best Fit ◽  
Contingency Approach

A contingency perspective of knowledge management recognises the need for a fit between knowledge management solutions (KMS) and decision making contexts which they support. In order to determine the best fit, a field survey was carried out to investigate the impact of two different types of KMS (technical and social) on decision makers' behaviour and performance in different decision contexts (simple and complex). The results provide partial support for the contingency view. As expected, the study identified social KMS as the best fit for complex contexts, based on subjects' superior performance from comparable adoption of both KMS. In contrast, the study identified that both KMS were an equally good fit for simple contexts, based on similar levels of subjects' performance, but social KMS was preferred in terms of adoption. These findings contribute to much needed empirical evidence for research and provide useful guidance for practice. However, their limitations warrant further study.

scholarly journals Elite Exploitation: A Combination of Mathematical Concept and EMO Approach for Multi-Objective Decision Making

Symmetry ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 136
Author(s):  
Wenxiao Li ◽  
Yushui Geng ◽  
Jing Zhao ◽  
Kang Zhang ◽  
Jianxin Liu
Keyword(s):  
Decision Making ◽  
Optimization Problems ◽  
Hybrid Genetic Algorithm ◽  
Decision Makers ◽  
Superior Performance ◽  
Test Problems ◽  
Mathematical Function ◽  
Hyperbolic Tangent ◽  
Nsga Ii ◽  
Multi Objective

This paper explores the combination of a classic mathematical function named “hyperbolic tangent” with a metaheuristic algorithm, and proposes a novel hybrid genetic algorithm called NSGA-II-BnF for multi-objective decision making. Recently, many metaheuristic evolutionary algorithms have been proposed for tackling multi-objective optimization problems (MOPs). These algorithms demonstrate excellent capabilities and offer available solutions to decision makers. However, their convergence performance may be challenged by some MOPs with elaborate Pareto fronts such as CFs, WFGs, and UFs, primarily due to the neglect of diversity. We solve this problem by proposing an algorithm with elite exploitation strategy, which contains two parts: first, we design a biased elite allocation strategy, which allocates computation resources appropriately to elites of the population by crowding distance-based roulette. Second, we propose a self-guided fast individual exploitation approach, which guides elites to generate neighbors by a symmetry exploitation operator, which is based on mathematical hyperbolic tangent function. Furthermore, we designed a mechanism to emphasize the algorithm’s applicability, which allows decision makers to adjust the exploitation intensity with their preferences. We compare our proposed NSGA-II-BnF with four other improved versions of NSGA-II (NSGA-IIconflict, rNSGA-II, RPDNSGA-II, and NSGA-II-SDR) and four competitive and widely-used algorithms (MOEA/D-DE, dMOPSO, SPEA-II, and SMPSO) on 36 test problems (DTLZ1–DTLZ7, WGF1–WFG9, UF1–UF10, and CF1–CF10), and measured using two widely used indicators—inverted generational distance (IGD) and hypervolume (HV). Experiment results demonstrate that NSGA-II-BnF exhibits superior performance to most of the algorithms on all test problems.

CAN BAYESIAN METHODS MAKE DATA AND ANALYSES MORE RELEVANT TO DECISION MAKERS?

2001 ◽  
Vol 17 (1) ◽  
pp. 114-122 ◽  
Author(s):  
Steven H. Sheingold
Keyword(s):  
Decision Making ◽  
Bayesian Methods ◽  
Paradigm Shift ◽  
Relevant Information ◽  
Decision Makers ◽  
Evidence Based ◽  
Critical Importance ◽  
Bayesian Approaches ◽  
Bayesian Analyses ◽  
And Performance

Decision making in health care has become increasingly reliant on information technology, evidence-based processes, and performance measurement. It is therefore a time at which it is of critical importance to make data and analyses more relevant to decision makers. Those who support Bayesian approaches contend that their analyses provide more relevant information for decision making than do classical or “frequentist” methods, and that a paradigm shift to the former is long overdue. While formal Bayesian analyses may eventually play an important role in decision making, there are several obstacles to overcome if these methods are to gain acceptance in an environment dominated by frequentist approaches. Supporters of Bayesian statistics must find more accommodating approaches to making their case, especially in finding ways to make these methods more transparent and accessible. Moreover, they must better understand the decision-making environment they hope to influence. This paper discusses these issues and provides some suggestions for overcoming some of these barriers to greater acceptance.

Integration between knowledge management and business process management and its impact on the decision making process in the construction sector: a case study of Jordan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sami Wasef Abuezhayeh ◽  
Les Ruddock ◽  
Issa Shehabat
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
Decision Makers ◽  
Decision Making Process ◽  
Construction Sector ◽  
Content Type

Purpose The purpose of this paper is to investigate and explain how organizations in the construction sector can enhance their decision-making process (DMP) by practising knowledge management (KM) and business process management (BPM) activities. A conceptual framework is developed that recognises the elements that impact DMP in terms of KM and BPM. The development of this framework goes beyond current empirical work on KM in addition to BPM as it investigates a wider variety of variables that impact DMP. Design/methodology/approach A case study is undertaken in the context of the construction industry in Jordan. A theoretical framework is developed and assessment of the proposed framework was undertaken through a questionnaire survey of decision-makers in the construction sector and expert interviews. Findings The outcomes of this research provide several contributions to aid decision-makers in construction organizations. Growth in the usage of KM and BPM, in addition to the integration between them, can provide employees with task-related knowledge in the organization’s operative business processes, improve process performance, promote core competence and maximise and optimise business performance. Originality/value Through the production of a framework, this study provides a tool to enable improved decision-making. The framework generates a strong operational as well as theoretical approach to the organizational utilization of knowledge and business processes.

Fuzzy multi-attribute group decision making to identify the order of establishing temporary logistics hubs during disaster response

2019 ◽  
Vol 9 (1) ◽  
pp. 2-21 ◽  
Author(s):  
Rajali Maharjan ◽  
Shinya Hanaoka
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Disaster Response ◽  
Group Decision ◽  
Decision Makers ◽  
Numerical Illustration ◽  
Content Type ◽  
Using Data ◽  
The Impact ◽  
Post Disaster

Purpose The purpose of this paper is to reveal the importance of the order of establishment of temporary logistics hubs (TLHs) when resources (mobile storage units used as TLHs) are limited and to present the development and implementation of a methodology that determines the order of establishment of TLHs to support post-disaster decision making. Design/methodology/approach It employed a decision support system that considers multiple decision makers and subjective attributes, while also addressing the impreciseness inherent in post-disaster decision making for ordering the establishment of TLHs. To do so, an optimization model was combined with a fuzzy multi-attribute group decision making approach. A numerical illustration was performed using data from the April 2015 Nepal Earthquake. Findings The results showed the location and order of establishment of TLHs, and demonstrated the impact of decision makers’ opinions on the overall ordering. Research limitations/implications The study does not discuss the uncertain nature of the location problem and the potential need for relocation of TLHs. Practical implications This methodology offers managerial insights for post-disaster decision making when resources are limited and their effective utilization is vital. The results highlight the importance of considering the opinions of multiple actors/decision makers to enable coordination and avoid complication between the growing numbers of humanitarian responders during disaster response. Originality/value This study introduces the concept of the order of establishment of TLHs and demonstrates its importance when resources are limited. It develops and implements a methodology determining the order of establishment of TLHs to support post-disaster decision making.

scholarly journals Policy impacts of ecosystem services knowledge

2016 ◽  
Vol 113 (7) ◽  
pp. 1760-1765 ◽  
Author(s):  
Stephen M. Posner ◽  
Emily McKenzie ◽  
Taylor H. Ricketts
Keyword(s):  
Decision Making ◽  
Quantitative Analysis ◽  
Ecosystem Services ◽  
Human Development ◽  
Policy Process ◽  
Decision Makers ◽  
Policy Impact ◽  
Predictor Variables ◽  
Policy Impacts ◽  
The Impact

Research about ecosystem services (ES) often aims to generate knowledge that influences policies and institutions for conservation and human development. However, we have limited understanding of how decision-makers use ES knowledge or what factors facilitate use. Here we address this gap and report on, to our knowledge, the first quantitative analysis of the factors and conditions that explain the policy impact of ES knowledge. We analyze a global sample of cases where similar ES knowledge was generated and applied to decision-making. We first test whether attributes of ES knowledge themselves predict different measures of impact on decisions. We find that legitimacy of knowledge is more often associated with impact than either the credibility or salience of the knowledge. We also examine whether predictor variables related to the science-to-policy process and the contextual conditions of a case are significant in predicting impact. Our findings indicate that, although many factors are important, attributes of the knowledge and aspects of the science-to-policy process that enhance legitimacy best explain the impact of ES science on decision-making. Our results are consistent with both theory and previous qualitative assessments in suggesting that the attributes and perceptions of scientific knowledge and process within which knowledge is coproduced are important determinants of whether that knowledge leads to action.

The Impact of Culture and Context on Knowledge Management

2011 ◽  
pp. 6-11 ◽  
Author(s):  
Murray E. Jennex
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Home Office ◽  
Consensus Definition ◽  
Main Work ◽  
Study Support ◽  
Editorial Review ◽  
Definition Of ◽  
Year 2000 ◽  
The Impact

Jennex (2005) used an expert panel to generate the definition of knowledge management as the practice of selectively applying knowledge from previous experiences of decision-making to current and future decision making activities with the express purpose of improving the organization’s effectiveness. This was a consensus definition from the editorial review board that tells us what we are trying to do with knowledge management. However, knowledge management is being applied in multinational, multicultural organizations and we are seeing issues in effectively implementing knowledge management and transferring knowledge in global and/or multicultural environments. Chan and Chau (2005) discuss a failure of knowledge management that was in part caused by organizational culture differences between the home office (Hong Kong) and the main work location (Shanghai). Jennex (2006) discusses Year 2000, Y2K, knowledge sharing projects that were not as successful as expected due to cultural and context issues. These projects involved organizations that performed the same functions just in different nations, however, problems caused by culture and context were not expected. Other research in review with the International Journal of Knowledge Management explores issues of culture with respect to social capital and implementing knowledge management. None of these are far reaching studies that we can generalize issues from, but they do provide anecdotal and case study support that culture and context are issues we need to address.

scholarly journals The Risk of Failure: Trial and Error Learning and Long-Run Performance

2019 ◽  
Vol 11 (1) ◽  
pp. 44-78 ◽  
Author(s):  
Steven Callander ◽  
Niko Matouschek
Keyword(s):  
Sufficient Conditions ◽  
Decision Makers ◽  
Risk Averse ◽  
Trial And Error ◽  
Improve Performance ◽  
Risk Of Failure ◽  
Long Run ◽  
Error Learning ◽  
And Performance ◽  
The Impact

Innovation is often the key to sustained progress, yet innovation itself is difficult and highly risky. Success is not guaranteed as breakthroughs are mixed with setbacks and the path of learning is typically far from smooth. How decision makers learn by trial and error and the efficacy of the process are inextricably linked to the incentives of the decision makers themselves and, in particular, to their tolerance for risk. In this paper, we develop a model of trial and error learning with risk averse agents who learn by observing the choices of earlier agents and the outcomes that are realized. We identify sufficient conditions for the existence of optimal actions. We show that behavior within each period varies in risk and performance and that a performance trap develops, such that low performing agents opt to not experiment and thus fail to gain the knowledge necessary to improve performance. We also show that the impact of risk reverberates across periods, leading, on average, to divergence in long-run performance across agents. (JEL D81, D83, O31, O38)

scholarly journals Leveraging Logistics Competence in New Product Sourcing: The Role of Strategic Intent and Impact on Performance

Logistics ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 24
Author(s):  
Myung Kyo Kim ◽  
Ram Narasimhan ◽  
Tobias Schoenherr
Keyword(s):  
Superior Performance ◽  
Strategic Intent ◽  
South Korean ◽  
Selection Decisions ◽  
Path Modelling ◽  
Construct Measurement ◽  
And Performance ◽  
The Impact ◽  
Moderating Role

The purpose of the present research is to examine and compare product and logistics competencies in supplier selection decisions, which can serve as a crucial building block for competitive differentiation, in the context of the unique private label (PL) supply chain. This study also hypothesizes about the impact of product and logistics competence on the retailer’s financial performance. Lastly, the moderating role of the product type in the proposed research model is explored. Partial least squares path modelling is used to analyze the dataset drawn from major South Korean retailers, due to the exploratory nature of the research and the use of both reflective and formative construct measurement items. Overall, the results of this study demonstrate that relationships between the desire for a particular strategic intent and performance are more complex than previous studies have implied. The findings of this research offer possible explanations on an important but understudied aspect of PL success: why not all PLs (even of the same retailer) are thriving even in a rapidly growing PL industry. We further elicit strategic recommendations for retailers in selecting PL suppliers and for PL manufacturers to differentiate themselves and achieve a superior performance.

Sign in / Sign up

Export Citation Format

Share Document