Application of multiple discriminant analysis (MDA) as a credit scoring and risk assessment model

2011 ◽  
Vol 6 (2) ◽  
pp. 132-147 ◽  
Author(s):  
Marcellina Mvula Chijoriga
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Credit Risk ◽  
Credit Scoring ◽  
Assessment Model ◽  
Management Decision ◽  
Multiple Discriminant Analysis ◽  
Content Type ◽  
Management Decision Making ◽  
Customer Classification

PurposeThe purpose of this research is to investigate whether inclusion of risk assessment variables in the multiple discriminant analysis (MDA) model improved the banks ability in making correct customer classification, predict firm's performance and credit risk assessment.Design/methodology/approachThe paper reviews literature on the application of financial distress and credit scoring methods, and the use of risk assessment variables in classification models. The study used a sample of 56 performing and non‐performing assets (NPA) of a privatized commercial bank in Tanzania. Financial ratios were used as independent variables for building the MDA model with a variation of five MDA models. Different statistical tests for normality, equality of covariance, goodness of fit and multi‐colinearity were performed. Using the estimation and validation samples, test results showed that the MDA base model had a higher level of predictability hence classifying correctly the performing and NPA with a correctness of 92.9 and 96.4 percent, respectively. Lagging the classification two years, the results showed that the model could predict correctly two years in advance. When MDA was used as a risk assessment model, it showed improved correct customer classification and credit risk assessment.FindingsThe findings confirmed financial ratios as good classification and predictor variables of firm's performance. If the bank had used the MDA for classifying and evaluating its customers, the probability of failure could have been known two years before actual failure, and the misclassification costs could have been calculated objectively. In this way, the bank could have reduced its non‐performing loans and its credit risk exposure.Research limitations/implicationsThe valiadation sample used in the study was smaller compared to the estimation sample. MDA works better as a credit scoring method in the banking environment two years before and after failure. The study was done on the current financial crisis of 2009.Practical implicationsUse of MDA helps banks to determine objectively the misclassification costs and its expected misclassification errors plus determining the provisions for bad debts. Banks could have reduced the non‐performing loans and their credit risks exposure if they had used the MDA method in the loan‐evaluation and classification process. The study has proved that quantitative credit scoring models improve management decision making as compared to subjective assessment methods. For improved credit and risk assessment, a combination of both qualitative and quantitave methods should be considered.Originality/valueThe findings have shown that using the MDA, commercial banks could have improved their objective decision making by correctly classifying the credit worthiness of a customer, predicting firm's future performance as well as assessing their credit risk. It has also shown that other than financial variables, inclusion of stability measures improves management decision making and objective provisioning of bad debts. The recent financial crisis emphasizes the need for developing objective credit scoring methods and instituting prudent risk assessment culture to limit the extent and potential of failure.

scholarly journals Manager perceptions of big data reliability in hotel revenue management decision making

2019 ◽  
Vol 36 (1) ◽  
pp. 25-39 ◽  
Author(s):  
David Egan ◽  
Natalie Claire Haynes
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Revenue Management ◽  
Management Decision ◽  
Local Market ◽  
Data Systems ◽  
Local Data ◽  
Content Type ◽  
User Input ◽  
Management Decision Making

PurposeThe purpose of this paper is to investigate the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing decisions.Design/methodology/approachA three-stage iterative thematic analysis technique based on the approaches of Braun and Clarke (2006) and Nowell et al. (2017) and using different research instruments to collect and analyse qualitative data at each stage was used to develop an explanatory framework.FindingsWhilst big data-driven automated revenue systems are technically capable of making pricing and inventory decisions without user input, the findings here show that the reality is that managers still interact with every stage of the revenue and pricing process from data collection to the implementation of price changes. They believe that their personal insights are as valid as big data in increasing the reliability of the decision-making process. This is driven primarily by a lack of trust on the behalf of managers in the ability of the big data systems to understand and interpret local market and customer dynamics.Practical implicationsThe less a manager believes in the ability of those systems to interpret these data, the more they perceive gut instinct to increase the reliability of their decision making and the less they conduct an analysis of the statistical data provided by the systems. This provides a clear message that there appears to be a need for automated revenue systems to be flexible enough for managers to import the local data, information and knowledge that they believe leads to revenue growth.Originality/valueThere is currently little research explicitly investigating the role of big data in decision making within hotel revenue management and certainly even less focussing on decision making at property level and the perceptions of managers of the value of big data in increasing the reliability of revenue and pricing decision making.

Framework for Identification and Collection of Data Useful for Risk Assessments of Microbial Foodborne or Waterborne Hazards: A Report from the International Life Sciences Institute Research Foundation Advisory Committee on Data Collection for Microbial Risk Assessment

2007 ◽  
Vol 70 (7) ◽  
pp. 1744-1751 ◽  
Author(s):  
ISABEL WALLS
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Risk Management ◽  
Data Collection ◽  
Dose Response ◽  
Management Decision ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Response Data ◽  
Management Decision Making

A microbial risk assessment (MRA) can provide the scientific basis for risk management decision making. Much data are needed to complete an MRA, including quantitative data for pathogens in foods. The purpose of this document was to provide information on data needs and data collection approaches for MRAs that will be useful for national governments, particularly in developing countries. A framework was developed, which included the following activities: (i) identify the purpose of data collection—this should include stating the specific question(s) to be addressed; (ii) identify and gather existing data—this should include a determination of whether the data are sufficient to answer questions to be addressed; (iii) develop and implement a data collection strategy; (iv) analyze data and draw conclusions; and (v) use data to answer questions identified at the start of the process. The key data needs identified for an MRA were as follows: (i) burden of foodborne or waterborne disease; (ii) microbial contamination of foods; and (iii) consumption patterns. In addition, dose-response data may be necessary, if existing dose-response data cannot be used to estimate dose response for the population of interest. Data should be collected with a view to its use in risk management decision making. Standard sampling and analysis methods should be used to ensure representative samples are tested, and care should be taken to avoid bias when selecting data sets. A number of barriers to data collection were identified, including a lack of clear understanding of the type of data needed to undertake an MRA, which is addressed in this document.

Loyalty card adoption in SME retailers: the impact upon marketing management

2015 ◽  
Vol 49 (3/4) ◽  
pp. 467-490 ◽  
Author(s):  
Karise Hutchinson ◽  
Lisa Victoria Donnell ◽  
Audrey Gilmore ◽  
Andrea Reid
Keyword(s):  
Decision Making ◽  
Current Knowledge ◽  
Marketing Management ◽  
Management Decision ◽  
Adoption Process ◽  
Longitudinal Case Study ◽  
Content Type ◽  
Management Decision Making ◽  
The Impact ◽  
Loyalty Card

Purpose – The purpose of this paper is to understand how small to medium-sized enterprise (SME) retailers adopt and implement a loyalty card programme as a marketing management decision-making tool. Design/methodology/approach – A qualitative and longitudinal case study research design is adopted. Data were collected from multiple sources, incorporating semi-structured interviews and analysis of company documents and observation within a retail SME. Findings – The findings presented focus on the loyalty card adoption process to reflect both the organisational issues and impact upon marketing management decision-making. Research limitations/implications – This research is restricted to one region within the UK, investigating loyalty card adoption within a specific industry sector. Practical implications – SME retailers operate in an industry environment whereby there is a competitive demand for loyalty card programmes. SME retailers need to carefully consider how to match the firm’s characteristics with customer relationship management (CRM) operational requirements as highlighted in this case. Originality/value – The evidence presented extends current knowledge of retail loyalty card programmes beyond the context of large organisations to encompass SMEs. The study also illustrates the value of a structured, formal CRM system to help SME retailers compete in a complex, competitive and omni-channel marketplace, adding new insights into the retail literature.

Three perspectives on evidence-based management: rank, fit, variety

2018 ◽  
Vol 56 (10) ◽  
pp. 2085-2100 ◽  
Author(s):  
Peter F. Martelli ◽  
Tuna Cem Hayirli
Keyword(s):  
Decision Making ◽  
Science And Technology Studies ◽  
Management Decision ◽  
Evidence Based ◽  
Managerial Decision ◽  
Content Type ◽  
Rigorous Research ◽  
Central Notion ◽  
Management Decision Making ◽  
Cybernetic Theory

Purpose The debate on evidence-based management (EBMgt) has reached an impasse. The persistence of meaningful critiques highlights challenges embedded in the current frameworks. The field needs to consider new conceptual paths that appreciate these critiques, but move beyond them. The paper aims to discuss this issue. Design/methodology/approach This paper unpacks the concept of finding the “best available evidence,” which remains a central notion across definitions of EBMgt. For each element, it considers relevant theory and offers recommendations, concluding with a discussion of “bestness” as interpreted across three key dynamics – rank, fit, and variety. Findings The paper reinforces that EBMgt is a social technology, and draws on cybernetic theory to argue that the “best” evidence is produced not by rank or fit, but by variety. Through variety, EBMgt more readily captures the contextual, political, and relational aspects embedded in management decision making. Research limitations/implications While systematic reviews and empirical barriers remain important, more rigorous research evidence and larger catalogues of contingency factors are themselves insufficient to solve underlying sociopolitical concerns. Likewise, current critiques could benefit from theoretical bridges that not only reinforce learning and sensemaking in real organizations, but also build on the spirit of the project and progress made towards better managerial decision making. Originality/value The distinctive contribution of this paper is to offer a new lens on EBMgt drawing from cybernetic theory and science and technology studies. By proposing the theoretical frame of variety, it offers potential to resolve the impasse between those for and against EBMgt.

Decision‐making training in local government emergency management

2012 ◽  
Vol 1 (2) ◽  
pp. 159-174 ◽  
Author(s):  
Helen Sinclair ◽  
Emma E.H. Doyle ◽  
David M. Johnston ◽  
Douglas Paton
Keyword(s):  
Decision Making ◽  
Local Government ◽  
Emergency Management ◽  
Management Decision ◽  
Content Type ◽  
Emergency Operations ◽  
Emergency Managers ◽  
Decision Making Styles ◽  
Management Decision Making ◽  
Survey Approach

PurposeThe purpose of this paper is to contribute information and recommendations that could better equip emergency managers to prepare for and respond to emergencies and disasters, with a focus on improving their decision‐making capabilities during response.Design/methodology/approachA questionnaire‐based survey approach was used in this research and 48 different local government organisations participated. These results were examined in conjunction with contemporary emergency management decision‐making literature. A combination of closed and open ended questions was used, enabling qualitative and quantitative analysis.FindingsResults suggest that while there is information available about decision making, not all emergency managers are aware of the existence of this information or understand its relevance to emergency management. It is likely that those who did have a comprehensive understanding of decision making had gained this knowledge through non‐emergency management‐related courses. In total, 71 percent of participants said they would be interested in receiving more support regarding training and practice for decision making in Emergency Operations Centres.Originality/valueA wide body of research has investigated decision‐making styles. However, this paper shows that in the local government emergency management sector there is little awareness of the understanding of the different decision‐making approaches. In addition, for those organisations surveyed, there is a great desire for further training and practice in decision making. It is thus vital that this need is addressed, to further improve the future response of these organisations to emergencies.

Adoption of renewable energy technologies (RETs) using a mixed-method approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nicholas Morgan Geddes
Keyword(s):  
Decision Making ◽  
Diffusion Of Innovations ◽  
Mixed Methodology ◽  
Management Decision ◽  
Content Type ◽  
Study Approach ◽  
Energy Technologies ◽  
Water Pumping ◽  
Management Decision Making

Purpose This paper aims to propose that the socio-technical perspective is under-represented when appraising the adoption potential of renewable energy technologies (RETs) in late-industrialising countries and that this results in under-adoption. It also aims to identify a methodological approach that allows the socio-technical perspective to be integrated into management decision-making, alongside the more typical economic appraisal methodology. Design/methodology/approach A case study and novel mixed-methodology approach is used, which applies the diffusion of innovations framework, innovation system (IS) framework and system dynamics modelling (SDM) alongside traditional economic modelling and appraisal techniques. This approach is used to assess the adoption potential of solar photovoltaic (PV) and diesel water pumping systems in the wildlife conservation sector and surrounding rural communities in Kenya. The case study approach tests the merits of the mixed-methodology approach. Findings The life-cycle costs of solar PV water pumping systems are lower in nearly all financing and utilisation scenarios; offer additional social, technical and environmental benefits; and the conditions exist for greater adoption. The use of an integrated diffusion of innovations and IS framework generates significant qualitative data that can support management decision-making. The use of SDM techniques aid conceptualisation of the community economic, water and institutional systems into which water pumps may be diffused and provide a starting point for formal SDM simulation. The results suggest that these techniques capture the socio-technical perspective well and, when used alongside traditional project appraisal approaches, produce more complete information with which to support management decision-making. Originality/value This mixed-methodology approach could be used by practitioners to increase the diffusion and adoption of RETs in more complex contexts in late-industrialising countries. The emergent theory built through the case-study approach should be tested further to assess the merits of applying these techniques to support RET management decision-making in other contexts and more broadly.

scholarly journals The prioritization and categorization method (PCM) process evaluation at Ericsson: a case study

2017 ◽  
Vol 23 (2) ◽  
pp. 377-398 ◽  
Author(s):  
Jens Ohlsson ◽  
Shengnan Han ◽  
Harry Bouwman
Keyword(s):  
Decision Making ◽  
Process Improvement ◽  
Process Management ◽  
Single Case ◽  
Management Decision ◽  
Organizational Setting ◽  
Content Type ◽  
Business Context ◽  
Management Decision Making

Purpose The purpose of this paper is to demonstrate and evaluate the prioritization and categorization method (PCM), which facilitates the active participation of process stakeholders (managers, owners, customers) in process assessments. Stakeholders evaluate processes in terms of effectiveness, efficiency and relevance against certain contextual business and industry factors. This collective evaluation serves as a foundation for the management decision-making process regarding process improvement and redesign. Design/methodology/approach The PCM is examined based on a case study at Ericsson. In total, 55 stakeholders, representing different organizational levels and functions, assessed eight core processes. Follow-up interviews and feedback after the evaluation sessions were collected for triangulation purpose. Findings The PCM helps Ericsson evaluate its processes within business context and industry environments. The results show that, to realize seamless end-to-end processes in the eight assessed processes, Ericsson has to make a greater effort to improve its process structures, governance and culture for fulfilling the needs of future business. Ericsson Steering Group is satisfied with the insights provided and has decided to train more stakeholders to use PCM. Research limitations/implications This research is based on a single case within a specific organizational setting. The results may not be necessary generalizable to other business and industry settings. Organizations need to configure PCM in consideration of their own processes and business contingencies to explore and fulfil their process improvement purposes. Originality/value This paper presents a new context-aware, easy-to-use and holistic method for business process management (BPM), the PCM. The method requires the active engagement of stakeholders, it focusses on developing dynamic BPM capabilities and fully embeds organizational contingencies and contextual factors in the decision-making regarding BPM. This paper contributes a novel method to explorative BPM.

Supply chain sustainability: evidence on conflict minerals

2014 ◽  
Vol 26 (1/2) ◽  
pp. 28-53 ◽  
Author(s):  
Paul A. Griffin ◽  
David H. Lont ◽  
Yuan Sun
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Control Sample ◽  
Management Decision ◽  
Negative Effects ◽  
Content Type ◽  
Positive Effects ◽  
Conflict Minerals ◽  
Social Concerns ◽  
Management Decision Making

Purpose – This study aims to examine the economic cost imposed by capital markets of section 1502 of the Dodd-Frank Act of 2010 on conflict minerals (CM). The authors analyse a sample of first-time CM disclosures made by US companies in 2010-2012. Design/methodology/approach – The authors measure the market response to these disclosures and compare it to the response of a matched control sample of non-disclosers. An overall negative response could arise from regulatory costs, changes in management decision making, or customers' social concerns about CM. An overall positive response could reflect the benefits of disclosure transparency. Findings – The authors find that the negative effects of the disclosures outweigh any positive effects. The authors also find more limited negative effects for the control sample, since they are likely to be future CM disclosers. Research limitations/implications – Because companies' balance sheets do not report these negative effects, the results imply that investors price supply chain activities related to CM as an off-balance sheet liability. Practical implications – The results agree with companies' assertions of a substantial cost to implement the CM provision. The authors estimate an aggregate loss of shareholder value for the sample of $6.5 to $13.1 billion. Social implications – These results show that regulators' and stakeholders' demands for increased transparency can be costly to shareholders when the disclosures induce changes in management decision making and raise customers' social concerns about supply chain sustainability. Originality/value – The study is the first to examine the economic effects of companies' initial disclosures about CM under the Dodd-Frank Act of 2010.

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