Market Positioning Using Cross-Reward Effects in a Coalition Loyalty Program

2017 ◽  
Author(s):  
Valeria Stourm ◽  
Eric Bradlow ◽  
Peter Fader
Keyword(s):  
Loyalty Program ◽  
Market Positioning ◽  
Reward Effects

The next generation: Experiences of higher educated Turkish-Dutch on The Hague labour market

2014 ◽  
Vol 11 (2) ◽  
pp. 206-217
Author(s):  
Karijn G. Nijhoff
Keyword(s):  
Higher Education ◽  
Qualitative Study ◽  
Labour Market ◽  
Education System ◽  
Minority Groups ◽  
Personal Characteristics ◽  
Market Positioning ◽  
The Hague ◽  
The Relationship ◽  
Dutch City

This paper explores the relationship between education and labour market positioning in The Hague, a Dutch city with a unique labour market. One of the main minority groups, Turkish-Dutch, is the focus in this qualitative study on higher educated minorities and their labour market success. Interviews reveal that the obstacles the respondents face are linked to discrimination and network limitation. The respondents perceive “personal characteristics” as the most important tool to overcoming the obstacles. Education does not only increase their professional skills, but also widens their networks. The Dutch education system facilitates the chances of minorities in higher education through the “layering” of degrees. 

The Second Red Scare and the Unmaking of the New Deal Left

2012 ◽  
Author(s):  
Landon R. Y. Storrs
Keyword(s):  
New Deal ◽  
Red Scare ◽  
Loyalty Program ◽  
Federal Employee ◽  
The Great Depression ◽  
Policy Ideas ◽  
Political Views ◽  
Consumer Movements ◽  
The Right ◽  
The New Deal

The loyalty investigations triggered by the Red Scare of the 1940s and 1950s marginalized many talented women and men who had entered government service during the Great Depression seeking to promote social democracy as a means to economic reform. Their influence over New Deal policymaking and their alliances with progressive labor and consumer movements elicited a powerful reaction from conservatives, who accused them of being subversives. This book draws on newly declassified records of the federal employee loyalty program—created in response to fears that Communists were infiltrating the U.S. government—to reveal how disloyalty charges were used to silence these New Dealers and discredit their policies. Because loyalty investigators rarely distinguished between Communists and other leftists, many noncommunist leftists were forced to leave government or deny their political views. This book finds that loyalty defendants were more numerous at higher ranks of the civil service than previously thought, and that many were women, or men with accomplished leftist wives. Uncovering a forceful left-feminist presence in the New Deal, the book shows how opponents on the Right exploited popular hostility to powerful women and their “effeminate” spouses. The loyalty program not only destroyed many promising careers, it prohibited discussion of social democratic policy ideas in government circles, narrowing the scope of political discourse to this day. This book demonstrates how the Second Red Scare undermined the reform potential of the New Deal and crippled the American welfare state.

A Review on Sentiment Classification: Natural Language Understanding

2019 ◽  
Vol 13 (1) ◽  
pp. 20-27 ◽  
Author(s):  
Srishty Jindal ◽  
Kamlesh Sharma
Keyword(s):  
Natural Language ◽  
Sentiment Analysis ◽  
Social Networking Sites ◽  
Natural Language Understanding ◽  
Business Analytics ◽  
Language Understanding ◽  
Text Data ◽  
Data Set ◽  
Market Positioning ◽  
Illegal Activities

Background: With the tremendous increase in the use of social networking sites for sharing the emotions, views, preferences etc. a huge volume of data and text is available on the internet, there comes the need for understanding the text and analysing the data to determine the exact intent behind the same for a greater good. This process of understanding the text and data involves loads of analytical methods, several phases and multiple techniques. Efficient use of these techniques is important for an effective and relevant understanding of the text/data. This analysis can in turn be very helpful in ecommerce for targeting audience, social media monitoring for anticipating the foul elements from society and take proactive actions to avoid unethical and illegal activities, business analytics, market positioning etc. Method: The goal is to understand the basic steps involved in analysing the text data which can be helpful in determining sentiments behind them. This review provides detailed description of steps involved in sentiment analysis with the recent research done. Patents related to sentiment analysis and classification are reviewed to throw some light in the work done related to the field. Results: Sentiment analysis determines the polarity behind the text data/review. This analysis helps in increasing the business revenue, e-health, or determining the behaviour of a person. Conclusion: This study helps in understanding the basic steps involved in natural language understanding. At each step there are multiple techniques that can be applied on data. Different classifiers provide variable accuracy depending upon the data set and classification technique used.

Loyalty program in Africa: risk-seeking and risk-averse adventurers

2014 ◽  
Vol 69 (2) ◽  
pp. 137-157 ◽  
Author(s):  
Shogo Mlozi
Keyword(s):  
Consumer Behavior ◽  
Consumer Products ◽  
Loyalty Programs ◽  
Risk Averse ◽  
Loyalty Program ◽  
Content Type ◽  
Risk Seeking ◽  
Proposed Model ◽  
First Time ◽  
The Relationship

Purpose – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Design/methodology/approach – This article aims to test the relationship between expected attractiveness-satisfaction-loyalty for international adventure tourists visiting Tanzania. The proposed model is based on travel consumer behavior theoretical constructs extracted from the literature. Findings – The findings for overall model differed from the moderating factors of high risk, low risk, first-time visit and repeat visit. Also, the results are interesting when satisfaction is tested as a mediator. Practical implications – Practitioners could consider the fact that repeat visits may change tourists’ perceptions toward destination and may even increase their inclination to take on risks. This may impact innovation of consumer products in tourism. Also, policy makers could benefit on how loyalty programs can be developed to increase performance. Originality/value – The study offers specific strategic recommendations toward different groups of tourists (i.e. first-time, repeat visitors, risk averse, risk seeking) and proposes logic for setting up a loyalty program as a long-term strategy for success.

Separating customer heterogeneity, points pressure and rewarded behavior to assess a retail loyalty program

2021 ◽  
Author(s):  
Alina Nastasoiu ◽  
Neil T. Bendle ◽  
Charan K. Bagga ◽  
Mark Vandenbosch ◽  
Salvador Navarro
Keyword(s):  
Loyalty Program ◽  
Customer Heterogeneity
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