A Data Mining Approach to Formulating a Successful Purchasing Negotiation Strategy

2011 ◽  
pp. 109-124
Author(s):  
Hokey Min ◽  
Ahmed Emam
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Experiential Learning ◽  
Optimal Performance ◽  
Negotiation Strategy ◽  
Data Mining Approach ◽  
Bargaining Position ◽  
Business Negotiations ◽  
The Impact ◽  
Business To Business

A successful path to purchasing negotiation often hinges on the buyer’s ability to gain relative bargaining strength. The buyer’s bargaining strength, in turn, depends upon the extent of the buyer’s preparation and preplanning for the negotiation. We postulate that the buyer’s level of expertise and/or simulated negotiation experiences through the experiential learning process help him/her better prepare for the negotiation and, thereby, increase his/her bargaining strength. Under such a premise, this study empirically investigates the impact of expertise and experiential learning on the bargaining position of purchasing professionals and their subsequent negotiation outcomes. The main objective of this chapter is to use both statistical data analysis and data mining techniques and demonstrate their usefulness in the optimal performance of business-to-business negotiations.

A Data Mining Approach to Formulating a Successful Purchasing Negotiation Strategy

2008 ◽  
pp. 2900-2914
Author(s):  
Hokey Min ◽  
Ahmed Emam
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Experiential Learning ◽  
Optimal Performance ◽  
Negotiation Strategy ◽  
Data Mining Approach ◽  
Bargaining Position ◽  
Business Negotiations ◽  
The Impact ◽  
Business To Business

A successful path to purchasing negotiation often hinges on the buyer’s ability to gain relative bargaining strength. The buyer’s bargaining strength, in turn, depends upon the extent of the buyer’s preparation and preplanning for the negotiation. We postulate that the buyer’s level of expertise and/or simulated negotiation experiences through the experiential learning process help him/her better prepare for the negotiation and, thereby, increase his/her bargaining strength. Under such a premise, this study empirically investigates the impact of expertise and experiential learning on the bargaining position of purchasing professionals and their subsequent negotiation outcomes. The main objective of this chapter is to use both statistical data analysis and data mining techniques and demonstrate their usefulness in the optimal performance of business-to-business negotiations.

Evaluating the impact of soy compounds on breast cancer using the data mining approach

2020 ◽  
Vol 11 (5) ◽  
pp. 4561-4570
Author(s):  
Sheng-I Chen ◽  
Hsiao-Ting Tseng ◽  
Chia-Chien Hsieh
Keyword(s):  
Breast Cancer ◽  
Data Mining ◽  
Cancer Type ◽  
Data Mining Approach ◽  
The Impact

Accumulating evidence has shown that soy intake is associated with the prevention of cancers. However, the specific soy compound and cancer type should be considered before allocating a precise nutrient intervention.

scholarly journals Analysis of the Impact of Residential Property and Equipment on Building Energy Efficiency and Consumption—A Data Mining Approach

2020 ◽  
Vol 10 (10) ◽  
pp. 3589 ◽  
Author(s):  
Mahsa Nazeriye ◽  
Abdorrahman Haeri ◽  
Francisco Martínez-Álvarez
Keyword(s):  
Data Mining ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Large Scale ◽  
Building Energy Efficiency ◽  
Data Set ◽  
Residential Homes ◽  
Improve Energy Efficiency ◽  
Data Mining Approach ◽  
The Impact

Human living could become very difficult due to a lack of energy. The household sector plays a significant role in energy consumption. Trying to optimize and achieve efficient energy consumption can lead to large-scale energy savings. The aim of this paper is to identify the equipment and property affecting energy efficiency and consumption in residential homes. For this purpose, a hybrid data-mining approach based on K-means algorithms and decision trees is presented. To analyze the approach, data is modeled once using the approach and then without it. A data set of residential homes of England and Wales is arranged in low, medium and high consumption clusters. The C5.0 algorithm is run on each cluster to extract factors affecting energy efficiency. The comparison of the modeling results, and also their accuracy, prove that the approach employed has the ability to extract the findings with greater accuracy and detail than in other cases. The installation of boilers, using cavity walls, and installing insulation could improve energy efficiency. Old homes and the usage of economy 7 electricity have an unfavorable effect on energy efficiency, but the approach shows that each cluster behaved differently in these factors related to energy efficiency and has unique results.

scholarly journals A data mining approach to study the impact of the methodology followed in chemistry lab classes on the weight attributed by the students to the lab work on learning and motivation

2016 ◽  
Vol 17 (1) ◽  
pp. 156-171 ◽  
Author(s):  
M. Figueiredo ◽  
L. Esteves ◽  
J. Neves ◽  
H. Vicente
Keyword(s):  
Data Mining ◽  
Methodological Approach ◽  
Teaching Methodology ◽  
Unit Of Analysis ◽  
Use Of Data ◽  
Data Mining Approach ◽  
The Individual ◽  
School Careers ◽  
The Impact ◽  
11Th Grade

This study reports the use of data mining tools in order to examine the influence of the methodology used in chemistry lab classes, on the weight attributed by the students to the lab work on learning and own motivation. The answer frequency analysis was unable to discriminate the opinions expressed by the respondents according to the type of the teaching methodology used in the lab classes. Conversely, the data mining approach usingk-means clustering models, allowed a deeper analysis of the results,i.e., enabled one to identify the methodology to teach chemistry that, in students' opinion, is important for learning chemistry and increasing their motivation. The sample comprised 3447 students of Portuguese Secondary Schools (1736 in the 10th grade; 1711 in the 11th grade). Thek-means Clustering Method was used, withkvalues ranging between 2 and 4. The main strengths of this study are the methodological approach for data analysis and the fact that the sample was formed by students with different school careers that enables the use of the individual as the unit of analysis.

scholarly journals Understanding the impact of coal blending decisions on the prediction of coke quality: a data mining approach

2018 ◽  
Vol 6 (2) ◽  
pp. 207-217
Author(s):  
Lauren A. North ◽  
Karen L. Blackmore ◽  
Keith V. Nesbitt ◽  
Kim Hockings ◽  
Merrick R. Mahoney
Keyword(s):  
Data Mining ◽  
Coke Quality ◽  
Data Mining Approach ◽  
Coal Blending ◽  
The Impact

Assessing the impact of students’ activities in e-courses on learning outcomes: a data mining approach

2019 ◽  
Vol 16 (2) ◽  
pp. 117-129 ◽  
Author(s):  
Damijana Keržič ◽  
Aleksander Aristovnik ◽  
Nina Tomaževič ◽  
Lan Umek
Keyword(s):  
Data Mining ◽  
Learning Outcomes ◽  
Undergraduate Students ◽  
Research Question ◽  
Final Exam ◽  
Content Type ◽  
Data Mining Approach ◽  
Student’S Performance ◽  
The Impact ◽  
The Relationship

Purpose This paper aims to study the relationship between students’ activities in the e-classroom and grades for the final exam. The study was conducted at the Faculty of Administration, University of Ljubljana among first-year undergraduate students. In the e-classroom, students learn new content for individual self-study, and their knowledge is checked with quizzes. Design/methodology/approach In the empirical study, the relationship between performance in quizzes and at the final exam was studied from two perspectives. First, successful and unsuccessful students (in terms of quizzes) were compared. Second, the Orange data mining software was used for two predictive modelling tasks. The research question was based on a student’s quiz performances, is it possible to predict whether the student will pass an exam and will the student’s grade for the exam be good. Findings The empirical results indicate a very strong connection between a student’s performance in quizzes and their score for the final exam in the course. Significant differences in performance were found between students who had completed most quizzes and those who had not. Moreover, the results highlighted which quizzes, in other words topics, are most important for passing an exam or obtaining a better grade. Therefore, the quality of individual study in the e-classroom positively influences a student’s performance. Originality/value The paper is the first to assess the impact of students’ activities on learning outcomes in undergraduate public administration programmes by applying a data mining approach.

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