scholarly journals Modeling Cross Category Purchase Decision Making with Consumers’ Mental Budgeting Control Habit

2020 ◽  
Vol 11 (4(I)) ◽  
pp. 33-42
Author(s):  
Zhiguo Yang
Keyword(s):  
Decision Making ◽  
Model Fit ◽  
Grocery Shopping ◽  
Purchase Decisions ◽  
Business Analytics ◽  
Ongoing Research ◽  
Cross Model ◽  
Price Effects ◽  
Mental Budgeting ◽  
Category Decision

Cross-category decision making is an ongoing research in decision science. Cross-category modeling is a powerful tool for big data and business analytics. Cross-category decision making involves evaluating multiple categories for complementary/substitutional utilities. This paper examines consumers’ mental budgeting control habit for its impact on cross purchase decisions. This factor has not been examined in existing cross modeling literature. This paper fits a base cross category model and a budgeting control habit cross model using a consumer grocery shopping dataset. The results show that by incorporating this variable in the cross model, model fit score and prediction accuracy are significantly improved. The budgeting control habit factor has significant moderating effects on price effects and cross price effects. In addition to providing the modeling technique, this paper also finds that consumers classify basket items into root and add-on categories. The common sense that price drop boosts sales is only true for the root category items. Price drop of add-on items may trigger consumers reconfiguring their basket items but not necessarily increase sales of the add-on items themselves.

Analisa Pengaruh Motivasi Konsumen, Persepsi Kualitas, Dan Sikap Konsumen Terhadap Keputusan Pembelian Sepeda Motor PT. Yamaha Indonesia MFG

CICES ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. 188-203
Author(s):  
Ria Wulandari ◽  
M. Ifran Sanni ◽  
Dani Ramadhan
Keyword(s):  
Decision Making ◽  
Regression Analysis ◽  
Qualitative Analysis ◽  
Purchase Decisions ◽  
Analysis Method ◽  
Purchasing Decisions ◽  
Processing Data ◽  
Customer Purchases ◽  
Customer Attitudes ◽  
Quantitative And Qualitative Methods

This research is motivated by a decline in motorcycle sales produced by PT. Yamaha Indonesia MFG in the 2014-2018 period. In this research there was a decrease in the decision on the power of interest in customer purchases on PT. Yamaha Indonesia MFG so that later can be analyzed in the formulation of this paper, that how customer take motorcycle purchase decisions amid the phenomenon of competition and increasingly crowded sales rivalries. The purpose of this research was to analyze the influence of motivation, perceived quality, and customer attitudes toward decisions in purchasing Yamaha motorbikes. This research uses quantitative and qualitative methods. The respondents in this research were 100 people who could meet one to five criteria consisting of; initiator (initiator), influencer (influencer), decision making (decider), purchase (buyer), user (user) motorcycle production PT. Yamaha Indonesia MFG. There are 3 hypotheses formulated and tested using the Regression Analysis method. In qualitative analysis it is obtained from the interpretation of processing data by providing information and explanation. In the results of this research shows the results of Motivation, Quality Perception, and Customer Attitudes have a relationship that has a significant impact on Purchasing Decisions.

scholarly journals Towards enhanced risk management: planning, decision making and monitoring of US wildfire response

2017 ◽  
Vol 26 (7) ◽  
pp. 551 ◽  
Author(s):  
Christopher J. Dunn ◽  
David E. Calkin ◽  
Matthew P. Thompson
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Fire Management ◽  
The United States ◽  
Management Decision ◽  
Current Response ◽  
Ongoing Research ◽  
Response Strategies ◽  
Management Decision Making ◽  
Response Decisions

Wildfire’s economic, ecological and social impacts are on the rise, fostering the realisation that business-as-usual fire management in the United States is not sustainable. Current response strategies may be inefficient and contributing to unnecessary responder exposure to hazardous conditions, but significant knowledge gaps constrain clear and comprehensive descriptions of how changes in response strategies and tactics may improve outcomes. As such, we convened a special session at an international wildfire conference to synthesise ongoing research focused on obtaining a better understanding of wildfire response decisions and actions. This special issue provides a collection of research that builds on those discussions. Four papers focus on strategic planning and decision making, three papers on use and effectiveness of suppression resources and two papers on allocation and movement of suppression resources. Here we summarise some of the key findings from these papers in the context of risk-informed decision making. This collection illustrates the value of a risk management framework for improving wildfire response safety and effectiveness, for enhancing fire management decision making and for ushering in a new fire management paradigm.

scholarly journals Idea Management Systems as a Tool for Goals’ Setting & Achieving and Decision Making: Global Research Results

2021 ◽  
Vol 129 ◽  
pp. 05008
Author(s):  
Elina Mikelsone ◽  
Tatjana Volkova ◽  
Aivars Spilbergs ◽  
Elita Liela
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Data Collection ◽  
Idea Generation ◽  
Value Added ◽  
Scientific Data ◽  
Web Based ◽  
Ongoing Research ◽  
Research Results ◽  
Idea Management

Research background: the authors have explored that there are different idea management system (IMS) application types that could be used both locally and globally for diverse reasons and expected outcomes. There is ongoing research on how IMS could be applied for manageable idea management process. But there is a question – how do these IMS types help to set and achieve goals, and improve decision making? Purpose of the article: The article aims to clarify how an external and mixed web-based IMS could be used during COVID19 time for distance idea generation sessions, as well as, to solve complex issues such as decision making, goals’ setting and reaching them based on different idea generation sources and critical reflection on those ideas of evaluators. Methods: Literature review (data collection: systematic data collection from scientific data bases; data analysis: content analysis). The survey of n>400 enterprises with web-based IMS experience globally (data collection: a survey; data analysis: statistics). Findings & Value added: this paper explores how different types of web-based IMS could be applied as a tool and support system for decision making processes in general, decisions towards goal setting and its outreach. The research results provide also a practical contribution - it could help to choose the most appropriate IMS application type to reach estimated goals and to empower decision making.

scholarly journals The optimization model of the logging machinery usage in forestry practice

2009 ◽  
Vol 57 (6) ◽  
pp. 105-112 ◽  
Author(s):  
Jitka Janová ◽  
M. Lindnerová
Keyword(s):  
Decision Making ◽  
Czech Republic ◽  
Decision Support ◽  
Decision Support Systems ◽  
Optimization Model ◽  
Support Systems ◽  
Decision Problems ◽  
Optimization Models ◽  
Ongoing Research ◽  
The Impact

The decision support systems commonly used in industry and economy managerial practice for optimizing the processes are based on algoritmization of the typical decision problems. In Czech forestry business, there is a lack of developed decision support systems, which could be easily used in daily practice. This stems from the fact, that the application of optimization methods is less successful in forestry decision making than in industry or economy due to inherent complexity of the forestry decision problems. There is worldwide ongoing research on optimization models applicable in forestry decision making, but the results are not globally applicable and moreover the cost of possibly arising software tools are indispensable. Especially small and medium forestry companies in Czech Republic can not afford such additional costs, although the results of optimization could positively in­fluen­ce not only the business itself but also the impact of forestry business on the environment. Hence there is a need for user friendly optimization models for forestry decision making in the area of Czech Republic, which could be easily solved in commonly available software, and whose results would be both, realistic and easily applicable in the daily decision making.The aim of this paper is to develop the optimization model for the machinery use planning in Czech logging firm in such a way, that the results can be obtained using MS EXCEL. The goal is to identify the integer number of particular machines which should be outsourced for the next period, when the total cost minimization is required. The linear programming model is designed covering the typical restrictions on available machinery and total volume of trees to be cut and transported. The model offers additional result in the form of optimal employment of particular machines. The solution procedure is described in detail and the results obtained are discussed with respect to its applicability in practical forestry decision making. The possibility of extension of suggested model by including additional requirements is mentioned and the example for the wood manipulation requirement is shown.

Designing a Business Analytics Culture in Organizations in India

2021 ◽  
pp. 670-678
Author(s):  
Tanushri Banerjee ◽  
Arindam Banerjee
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Data Organization ◽  
Business Analytics ◽  
Domain Specific ◽  
Consumer Lending ◽  
Effective Decision ◽  
Effective Decision Making

There are several challenges faced by decision makers while deploying Business Analytics in their organization. There may not be one resolution approach that is suitable for creating a Business Analytics culture in all organizations. However, it is easy to perceive that most India-based organizations may have similar issues of data organization that may be impeding their progression in the field of Analytics. Based on their research, the authors have proposed a framework for adoption of Analytics in Indian firms in their book “Weaving Analytics for Effective Decision Making” by SAGE. They propose to use that model for explaining certain domain specific adoption of Business Analytics in organizations in India. They have used a case study of a Global Bank which is in the process of establishing its consumer lending USA operations, an offshore captive operation, in India to describe the process of building an Analytics team in an organization in India. Data processed using R has been added as screenshots for supporting the findings.

The Role of Big Data and Business Analytics in Decision Making

2021 ◽  
pp. 226-257
Author(s):  
Pedro Caldeira Neves ◽  
Jorge Rodrigues Bernardino
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Open Source ◽  
Specific Area ◽  
Business Analytics ◽  
Business Decision ◽  
Business Sustainability ◽  
Open Source Systems ◽  
Fundamental Shift

The amount of data in our world has been exploding, and big data represents a fundamental shift in business decision-making. Analyzing such so-called big data is today a keystone of competition and the success of organizations depends on fast and well-founded decisions taken by relevant people in their specific area of responsibility. Business analytics (BA) represents a merger between data strategy and a collection of decision support technologies and mechanisms for enterprises aimed at enabling knowledge workers such as executives, managers, and analysts to make better and faster decisions. The authors review the concept of BA as an open innovation strategy and address the importance of BA in revolutionizing knowledge towards economics and business sustainability. Using big data with open source business analytics systems generates the greatest opportunities to increase competitiveness and differentiation in organizations. In this chapter, the authors describe and analyze business intelligence and analytics (BI&A) and four popular open source systems – BIRT, Jaspersoft, Pentaho, and SpagoBI.

scholarly journals Compensating Qualitative Rating Distortion of User Experience Evaluation Based on Prospect Theory

2019 ◽  
Vol 11 (23) ◽  
pp. 6815
Author(s):  
Min Chul Lee ◽  
Jaehyun Park
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Case Studies ◽  
User Experience ◽  
Cognitive Distortion ◽  
Model Fit ◽  
Online Questionnaire ◽  
Measurement Results ◽  
Preliminary Study ◽  
User Value

Psychophysical assessment may be affected by cognitive distortion. Although the theory was originally developed to revise decision making in uncertain situations, prospect theory can be applied to psychophysical measurements, which was verified in a previous preliminary study. Two case studies were used to validate the utilization of prospect theory in psychophysical measurements. Affective satisfaction dimensions were rated by participants for an experimental device using a 0–100 scale. Performance of affective satisfaction models increased with the application of prospect theory-based compensation. Hundreds of participants evaluated the user value of their own devices via an online questionnaire. Although model fit performance increased slightly with transformed data, more case studies are needed to investigate the utility of prospect theory on user value or on a range of target constructs. The application of prospect theory in various situations of psychophysical measurement can be expected to improve and compensate for measurement results.

Complicating or simplifying? Investigating the mixed impacts of online product information on consumers’ purchase decisions

2019 ◽  
Vol 30 (1) ◽  
pp. 263-287
Author(s):  
Yan Yu ◽  
Ben Qianqian Liu ◽  
Jin-Xing Hao ◽  
Chuanqi Wang
Keyword(s):  
Decision Making ◽  
Product Information ◽  
Purchase Decisions ◽  
Decision Strategy ◽  
Market Outcomes ◽  
Content Type ◽  
Decision Bias ◽  
Set Size ◽  
Product Presentation ◽  
Choice Set

Purpose Prior literature indicates conflicting effects of online product information, which may complicate or simplify consumer purchase decisions. Therefore, the purpose of this paper is to investigate how different online product information (i.e. the choice set size and the popularity information and its presentation) affect consumers’ decision making and the related market outcomes. Design/methodology/approach This research relies on information-processing theories and social learning theory. By stepwise conducting two 2×2 within-subject factorial design experiments, this research examines the effects of the choice set size, product popularity information and product presentation on consumers’ decision making and the aggregated market outcomes. Findings The results show that product popularity information led consumers to either simplify or complicate their decision strategy, depending on the size of the choice sets. Additionally, presenting products by their popularity in descending order resulted in consumers making decisions with a larger decision bias. The results also show that the presence of product popularity was more likely to forge a “superstar” structure in a large market. Practical implications The research suggests that e-retailers and e-marketplace operators should carefully utilize product popularity information. Multiple mechanisms that shape different shopping environments with different orders are necessary to create a long-tailed market structure. Originality/value This study found the mixed effects of product popularity information when it is presented in different environments (i.e. the large/small choice set and the sorted/randomized product presentation). The overuse of popularity information may induce consumers’ decision bias.

Sign in / Sign up

Export Citation Format

Share Document