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Customer Satisfaction - Science topic

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I want to publish my research done on service quality and customer satisfaction of Ethiopian coffee quality inspection and certification center. Which journal will you recommend me to contact?
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Thanks I will.
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With special reference to Hospitals and Healthcare Management.
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The application of artificial intelligence (AI) in hospitals yields many advantages but also confronts healthcare with ethical questions and challenges.
Artificial intelligence in hospitals: providing a status quo of ethical considerations in academia to guide future research - PubMed (nih.gov)
(PDF) ARTIFICIAL INTELLIGENCE IN HOSPITALS (researchgate.net)
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I am a University student taking up Masters in Business Administration major in Human Resource Development. I am looking for a research partner to collaborate and share knowledge with. My topic is about Long Service Delay and it's impact to customer satisfaction.
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Surprisingly, the pre-process cycle has the greatest influence on how customers perceive waiting times and service quality. A customer who has to wait 10 minutes in line before ordering will feel more dissatisfied than a customer who waits 10 minutes for their order to be prepared, even if the total service time for both customers was the same. Hence, this should be the first place you look to reduce wait times. ( )
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The quality of content and information that an Internet business, especially an emerging Internet business, has on web pages as part of their corporate identity has a special place in increasing customer satisfaction as well as its continuity.
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The following RG link is also very useful:
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Here, for measuring sample size , I have used Cochran formula. I took around 600 plus as respondents.
My target population is supermarket customers in Bangladesh ( all over the country).
I have 8 Exogenous variables, 1 Intervening variable (Customer Satisfaction) and 1 Endogenous variable (Customer Loyalty).
Data and insights are also being collected from 60 personnels including supermarket experts, entrepreneurs and customers by in-depth interview.
Is my sample size alright?
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Mohammad Kamrul Ahsan in general the number of respondents needs to be between 300 and over. For your side, 600 and over (600 - 800 respondents) may be convenient for the research. 365 respondents had been used in my research.
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I am researching on "Effects of Project Quality Management on Project Success( A study of Software Development)"
Dependent Variable = project success (PS)
Independent Variable = Project Quality Management (PQM)
Also, can you please suggest best indicators for Project Quality Management ?
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Estimados colegas qué indicadores me permiten medir la retención del cliente??
Gracias por sus aportes.
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Let's say I can see that my outcome metric (Customers' satisfaction with service = Service OSAT) dropped. And I want to know whether it dropped because Service OSAT dropped, or because demographic distribution changed. Maybe now we have more Male responders who usually give lower scores than Female.
Which model can help me to assess what drives Change in Service OSAT?
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Piyush Sharma thank you a lot!!! That is super helpful!
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I have a database referring to a customer satisfaction survey with 500 respondents and 23 variables based on a linkert scale. I understand that the Rating Scale Model can be a good tool for evaluating research, I would like to know if anyone could recommend an R package or syntax to process this data.
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I need it too, Please if you get let me know
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I'm doing research about customer satisfaction [Performance Independent]. Can someone help me with past studies on this topic? Preferably from 2010 to 2021 would be great!
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Hopefully the following publications could help:
  • Ambrož, M. and Praprotnik, M. (2008) Organisational Effectiveness and Customer Satisfaction, Organizacija, 41, 5, pp. 161-173.
  • Anderson, E. W. (1998) Customer satisfaction and word of mouth, Journal of service research, 1, 1, pp. 5-17.
  • Churchill, G., A. and Surprenant, C. (1982) An investigation into the determinants of customer satisfaction, Journal of Marketing Research, 19, 4, pp. 491-504.
  • Cooil, B., Keiningham, T. L., Aksoy, L. and Hsu, M. (2007) A Longitudinal Analysis of Customer Satisfaction and Share of Wallet: Investigating the Moderating Effect of Customer Characteristics, Journal of Marketing, 71, 1, pp. 67-83.
  • Danaher, P. J. and Haddrell, V. (1996) A comparison of question scales used for measuring customer satisfaction, International Journal of Service Industry Management, 7, 4, pp. 4-26.
  • Oliver, R. L. (2006) Customer Satisfaction Research, in Grover, R. and Vriens, V. (eds.) The handbook of marketing research: Uses, misuses, and future advances. Thousand Oaks, California: Sage Publications, Inc., Chapter 27, pp. 569-587.
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Dear Respondent,
I am inviting you to participate in research conducted for academic purposes to investigate the relationship between animosity and consumer perceptions. Included with this letter, there is a short scenario. After reading the scenario, please answer the questions. The results of this pretest will be used for a PhD dissertation, so the cumulative responses of the sample are important for the results rather than individual ones. Therefore, there is no need to give your name. There is no risk for you in participating and you can be assured that your responses will be confidential. The survey should take you about 5 minutes to complete. Participation is entirely voluntary. Thank you very much in advance.
Sincerely.
Muhammad Taqi - PhD candidate
Department of Business Administration
Izmir University of Economics
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done,
Good Luck!
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As a student of Fatima Jinnah women university, I am conducting my research study on “Impact of Deceptive Advertisement on Customer Loyalty with the Mediation of Customer Satisfaction; A Study on Telecom Sector of Pakistan”.
If you are a resident of Islamabad/Rawalpindi, and a user of Telecom Services, Kindly provide your valuable opinion regarding your Service Provider. Your response will be considered confidential and will use only used only for research purposes.
Thanking you in anticipation.
With regards,
Iqra Hafeez (FJWU)
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Try to target respondents more exactly...
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Thank you so much
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How is Six Sigma used in service industry?
Using the DMAIC (Define – Measure – Analyze – Improve – Control) methodology, Six Sigma helps in implementing quality in any industry by reducing defects. The defects are first identified, data is collected as to how the defects occur, and then a new method of working is implemented to reduce errors in the future
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Hello RG people, I'm studying Marketing and I am looking for an interesting title for my Postgraduate research. Any specific ideas in mind? And in which sector of business will be best to focus on?
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The following research directions and the related publications may further help:
  1. The use of artificial intelligence in marketing / four Ps (See: Verma et al, 2021; Rust, 2020)
  2. Online Marketing (See: Hajarian et al, 2021)
  3. Social Marketing (See: Diogo, 2020; Weinreich, 2006; Wymer, 2011; Cheng et al, 2011)
  4. Relationship Marketing (See: Steinhoff, 2021; Sheth, 2002; Lindgreen, 2001)
  • Cheng, H., Kotler, P. and Lee, N. R. (2011) Social Marketing for Public Health : An Introduction, in Cheng, H., Kotler, P. and Lee, N.R. (eds.) Social Marketing for Public Health: Global Trends and Success Stories. Sudbury: Jones and Bartlett Publishers, pp. 1-28.
  • Diogo, V. (2020) Editorial - Taking the pulse of social marketing: the 2019 world social marketing conference, Social Marketing Quarterly, 26, 4, pp. 271-275.
  • Hajarian, M., Camilleri, M. A., Díaz, P. and Aedo, I. (2021) A Taxonomy of Online Marketing Methods, in Camilleri, M.A. (ed.) Strategic Corporate Communication in the Digital Age. Bingley, UK: Emerald Publishing Limited, pp. 235-250.
  • Lindgreen, A. (2001) A framework for studying relationship marketing dyads, Qualitative Market Research, 4, 2, pp. 75-87.
  • Rust, R. T. (2020) The future of marketing, International Journal of Research in Marketing, 37, 1, pp. 15-26.
  • Sheth, J., N. (2002) The future of relationship marketing, The Journal of Services Marketing, 16, 7, pp. 590-592.
  • Steinhoff, L. P., Robert W (2021) Commentary: Opportunities and challenges of technology in relationship marketing, Australasian Marketing Journal, 29, 2, pp. 111-117.
  • Verma, S., Sharma, R., Deb, S. and Maitra, D. (2021) Artificial intelligence in marketing: Systematic review and future research direction, International Journal of Information Management Data Insights, 1, 1, pp. 100002-100010.
  • Weinreich, N. K. (2006) What Is Social Marketing?, Available at Weinreich Communications.
  • Wymer, W. (2011) Developing more effective social marketing strategies, Journal of Social Marketing, 1, 1, pp. 17-31.
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Hi
I am currently doing a research on service quality on customer satisfaction and loyalty . I am currently on the planning and analysis results using SPSS but I am a little confused with regards to regression analysis . What would be the best steps to follow to present data ( see file attached) to show Regression analysis of relationship between service quality and customer
satisfaction.
When I am on SPSS I am not too sure where to put control variables as linear regression option only has option for dependent/independent variables . I am not too sure what model 1/2 means
Thanks in advance
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Hello Martin,
The simple answer is, model 1 includes just the so-called control variables as IVs (independent variables). Model 2 adds the target IVs to that set.
The extent to which model 2 (and therefore the target IVs) substantively add to the explanatory power of model 1 (just the control variables) may be determined by the difference in R-squared (proportion of variance in the DV that is explained/accounted for by differences in the IVs for a model) between model 2 and model 1. A "big" difference would suggest that the target IVs help to explain differences in the DV above and beyond what the control variables are able to explain/account for.
This approach is sometimes called hierarchical regression.
Good luck with your work.
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Blending two theoretical foundations of Planned Behavior Theory and Relationship Marketing Theory, exploring four main marketing constructs of Customer Retention, Satisfaction, digital service quality (e-service Quality, e.g., (Parasuraman, 2005)) in a multivariate model using Structural Equation Analysis (PLS-SEM, SmartPLS, Ringle 2015) targeting Customer Retention as dependent variable, if anyone has something in mind, I would love to hear. Thanks in advance!
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Thank you for your insightfull answer. I will try to do first step of your recommended options.
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Thanks for your answers: Olga Rauhut Kompaniets, Mohammed Chambas, Rodney Duffett, Hermann Gruenwald. Because cs is an essential variable in marketing, then, I posted this question. But, the previous question is not appropriate and doesn't express my meaning. So, I update the new question that What is the new trend of customer satisfaction? For example, the the stages involved to CS is important these days. or we may replace the customer satisfaction to customer experience or other consumer behavior variables. Thanks all.
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Hii Furong Jia, I think it is vast a question and it depends on what you are researching. But in general, customers now want hyper-personalised experiences more than ever, and big data analytics provides the findings to make this possible. One example would be NETFLIX, the company focuses hugely on market reality ( providing only what viewers want before the viewers ask for it. Therefore, enhances the whole experience and leads to high satisfaction.
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I am currently working on my master thesis and have faced some problems in designing a survey. The goal is to analyze a transition from ordinary offline retailing towards physical showrooms effectuating fulfillment of products through an online shop. I use as dependent variable customer satisfaction (reaching from 1-10) and as independent variables the following ones: F= fulfillment (1/0) 1=now 0=in 3 days A=assortment (from 10 to 20 units per shop) P=price (from 25 to 25*0,7discount->17,5) Is it possible to design a survey/ experiment in a way to get the needed data for this equation?
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I am also interested to the answers of this topic.
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Predicting human behavior is challenging. When using machine learning algorithms in human behavior research the NRMSE would be higher than when we are investigating more accurate areas (NRMSE < 0.1), but what is the acceptable range?
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Md. Qaiser Reza Dear Mr Qaiser Reza;
Thank you for your response. That link is a very useful source, and I myself had participated in the answers too. But I am to find the acceptable error range exclusively in the human behavior field.
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Hello everyone,
As I am writing my thesis, I have come across a question. I am analyzing how franchisee satisfaction (measured by likert scale of 1-5 ) is affected by various factors, such as support given by franchisors, trust between franchisee and franchisors, and more--all of which are qualitative and measured via 1-5 (strongly disagree to strongly agree). However, I do not know what statistical regression to run to establish a meaningful and correct analysis on how the factors contribute to franchisee satisfaction. Could you please enlighten me? Thank you very much.
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Here you need something called weighting, try to check any reference is statistical methods or design of experiments to understand the steps for the equation.
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We are conducting a study on the level of customer satisfaction regarding a milk tea shop's online delivery services. We have a population of 29488, With a 95% confidence level, can we use a 10% margin error in selecting sample size?,
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Your satisfaction survey must also consider attributes of the evaluated service described by the target audience of your survey. Otherwise, if your variables were elaborated based on a third-party scale, you will have a much larger error than the statistic.
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The relationship between a company and its customer is not purely financial. It's a two-way street with unpredictable traffic. Companies spend millions on increasing customer satisfaction and loyalty yet there are cases of successful corporations that are hated and beloved businesses going bankrupt.
How would you explain the dependence between customer's loyalty and company's profitability?
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Dear Valeria Demchenko,
This type of relationship can be studied by analyzing the correlation between the change in the level of spending on advertising campaigns presenting the company's product and / or service offer, the level of effectiveness and efficiency of these campaigns, and the change in the level of financial revenues from sales of the company's offer. In addition, it is also important to take into account periodically conducted market research in order to diagnose changes in consumer preferences, including changes in citizens' awareness of the brand and mission of a specific company, assessment of its activities and product and / or service offer.
Best wishes,
Dariusz Prokopowicz
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Hi folks. I am going to write a master thesis this term. My master's program is on Business & Marketing. I would like to have your ideas on this issue. I was thinking of game publisher branding. I did my research, but there was not much to dig in. What would be interesting to dig into in this topic? I would appreciate it if you could come up with ideas related to customer satisfaction, consumer behavior, or branding :)
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In the last year there's been a surge in e-sports consumption, including some major players as newcomers (F1). You could look at how the COVID pandemic has changed the way people consume games (including Twitch), meaning we no longer just "play" but also share them and see competitions.
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We have a data set from N=193 participants. They assessed Corporate Image, Employer Image, Customer Experience and Employer Attractiveness (on Likert scales) for 8 different companies (each of the participants assessed all 8 companies). Employer Attractiveness is the DV. We ran regression for the total of 193*8 = 1544 observations to identify which of the IDVs (Corporate Image, Employer Image, Customer Satisfaction) has the largest impact on Employer Attractiveness (which is our research question). Now feedback of reviewers is mixed and irritating. One says, we must run a SEM in order to discern impact strength of the IDVs. Another says, we should apply a repeated-measures/within-subjects design. Can anybody help?
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Hermann Lassleben Based on the comments, your work might have some latent variable.
Good luck.
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Dear researchers,
I feel a bit confused about the moderator and mediator. In my model, I want to test if the six dimensions of online customer experience influence customer satisfaction, in turn, influences repurchase intention. And I have read from the literature that corporate image has a hola effect, which means if your company has a good image, it might offset customers' unsatisfying experience and still drive customers' repurchase intention. I personally feel it is a moderator, but I am not quite sure. Thanks a lot!
Kara
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Thank you all!!!!! I have added it as a moderator finally for what I aim to test.
Regards
Kara
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In our research on customer behavior towards online shopping we're using a number of constructs such as perceived behavioral control, perceived efficiency of e-commerce marketplace, sustainable consumption, economic benefits, customer satisfaction level, intention, etc. Any share of evidence or guidance would be extremely appreciated. Thank you.
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Thanks a lot, Oliva M. D. Martins, Karen Bayne, Zubair Nawaz, Gonçalo Brás for your valuable contributions.
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I am trying to quantify the benefits for an organization  when introduces FinTech, not from a customer perspective but from the corporation perspective. Even though the benefits can be numerous (in terms of cost, growth/ profitability, efficiency, security, customer satisfaction), I was thinking of using the measure '% of customers using alternative channels' and/ or '% of transactions performed from alternative channels' for the following reasons:
1. The measures can be publicly available for a listed company and
2. They include numerous benefits in one measure, such as customer satisfaction, decreasing costs and increasing efficiency.
Do you believe they are good measures and are they actually publicly available?
If not, are there other measures which are publicly available? Is profitability or cost alternative, good proxies?
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George Markides Total Revenue, Profitability Rate, and Cost Percentage
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My question is how to measure the impact of customer satisfaction (proxied by the ACSI, which is a product-based measure) on a firm's financial performance (e.g., Profitability ratios, which are firm-level measure). I am thinking of using this data as it is, since the product reputation might generally affect a firm's financial performance. I would be appreciated if you send me article(s) supporting the previous argument. Thank you
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I agree with @ Gautam Mahajan Sir
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Hi
I work on the relationship between quality management and customer satisfaction. If anyone has not published an investigation, please send me the results.
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Quality management improves final customer satisfaction
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I have just published a paper in Transport Policy about the mediator role of satisfaction in public transport (https://doi.org/10.1016/j.tranpol.2020.09.011) using data from the same survey in five cities (Madrid, Rome, Berlin, Lisbon and London). I have found that satisfaction exerts a complete mediator role between service quality and behavioral intentions in urban and metropolitan public transport services.
My personalized Share Link is https://authors.elsevier.com/a/1c1pU,L-HRby6v (valid before Dec 27, 2020).
I would appreciate feedback from anybody that has compared both models (partial vs. full mediator) in the field of public transport or in any other fields?
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Passenger satisfaction is not guaranteed if the quality of the services that public transit delivers do not result in increased passenger perceptions of value in relation to the fares paid. Therefore, providing passenger-value-oriented quality services is crucial for public transit companies if they are to satisfy their passengers and thus increase re-patronage/word-of-mouth behavior, and consequently customer loyalty.
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Hello, I am running a survey to measure the relationship between customer satisfaction of airline customer service during COVID19 and their future purchase intention (1 to 10 scale). Although the responses are clear unsatisfied and no intention to use the same airline again but the statistical analysis (Spearman) shows very weak relationship between the variables 34% ! Regression analysis,R is 0.1 . What I have been missing here please ? (sample size is 258)
Ps: If anyone is willing to contribute as co-author and do the methodology, they are welcome to pm me
Thank you
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Amal Hosny Abdelsalam Mohammed, Hi, If I understand your question, I believe you are conflating two issues. It's possible to have two ranked variables which clearly differ in, or don't differ in, their median (both tend to similar low values, etc.)--and yet have the _correlation_ between the two variables be very weak. In your example, this could happen if it's true that the satisfaction answer tends, collectively to be Low and the FlyAgain answer tends, collectively, to be low, but for individuals, the factors for when these low values are assigned are totally or largely unrelated. Additional noise can be added for considerations of how and why people assign possible non-low values, such as 4 versus 5 versus 8, etc. . Tools like Mann-Whitney are generally for comparing separate groups--like how males answer satisfaction versus how females answer satisfaction. But you're looking at dependent variables for how the same individuals answer a pair of questions.
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Dear All,
I am funny to study research. I would like to continue to do research and prospective topics would like to study is "Innovation of MS on customer satisfaction".
I am interesting international program.
Please kindly all to advise university.
MS = Marketing + Service
POM
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If you are interested to study PHD program in Thailand , you have to contact to Professor of that Univ. or Institute working in the field related to your research, Take recommendation letter from him, then write to univ. / institute for PDF fellowship.Unless you have fellowship , it is difficult to pursue the said programme.
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Hi
I’m conducting a meta-analysis regarding the relationship between “leadership” and “customer satisfaction”. In order to reduce the availability bias, I’m attempting to find unpublished studies.
Does anyone have any unpublished studies in this regard?
Thanks!
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# Pantouvakis, A. and Patsiouras, C. (2016), "Exploring the role of leadership style on the service quality-customer satisfaction link: Evidence from a B2B environment", International Journal of Quality and Service Sciences, Vol. 8 No. 1, pp. 88-101. https://doi.org/10.1108/IJQSS-01-2015-0006
# EMPIRICAL EVIDENCE FOR THE RELATION BETWEEN CUSTOMER SATISFACTION AND BUSINESS PERFORMANCE. file:///C:/Users/USER/Downloads/erimrs20010613144003.pdf
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Concepts related with Green Marketing, Analytical methods of Green Marketing. Prospects and Challenges of Green Marketing.
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I am trying to find if there is a link between perceived service quality (mainly urban services) and tourist satisfaction. I will be asking tourists through a questionnaire (five point likert scale, strong disagree to strong agree) some questions to capture their satisfaction with various urban services and their overall satisfaction with the visit.
The literature I read uses mainly three methods: i) Chi square test for independence ii) Log-linear regression iii) Fisher exact test (for small sample size). Chi-square test might indicate if there is correlation between dependent variable (tourist satisfaction) and independent variable (perceived urban service quality). Log-linear shows how much variability in dependent variable is due to independent variable.
All methods are related and used to find correlation/association/dependence. However, I cannot find a clear way to calculate sample size. Many articles seem to use a sample size anywhere between 100 and 500 without specifying how they arrived at that number or why they chose that number. I can do that same, but how would I justify that number?
I am looking for a formula to figure out how many questionnaires I should target. The annual tourist population is around 300K. I will be doing survey for about 2-3weeks. All variables are categorical.
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It depends on many things: objectives, study design, data collection methods, distribution etc. If it's a cross sectional study with normal distributed data then you can use easier formula used commonly. Your topic is basically qualitative one. Anyway you focused on quantitative approach and you do by using scales but should be used mixed method for getting better outcomes and also in-depth in this type of topic.
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I am currently working on my master thesis and have faced some problems in designing a survey. The goal is to analyze a transition from ordinary offline retailing towards physical showrooms effectuating fulfillment of products through an online shop.
I use as dependent variable customer satisfaction (reaching from 1-10) and as independent variables the following ones:
F= fulfillment (1/0) 1=now 0=in 3 days
A=assortment (from 10 to 20 units per shop)
P=price (from 25 to 25*0,7discount->17,5)
Is it possible to design a survey/ experiment in a way to get the needed data for this equation?
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You need to design items to measure the constructs (customer satisfaction, fulfillment and assortment) that you have. How do you get price data from a survey? Is it over time or for 5 years? Survey data is at a pt. in time unless you want to do longitudinal data which is not easy to survey.
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What is the value perceived by the customer in strategic marketing?
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Everything we want. Marketing is the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large.
M.Tetvadze
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Currently researching the literature for drafting the topic.
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... This study aims to show the impact of the logistics management on customer satisfaction in small and mid-sized Algerian industrial companies, by interviewing the companies managers and everybody in charge of the logistic process, the interview questions will be based on some literature review issues. ...
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To know what cultural aspects have an impact on the FM, whether on working procedure, customer satisfaction, company hierarchy etc.
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Alexander, K. (2013). Facilities management: theory and practice. Routledge.
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Hello..
Example of my question is the following statement in a survey:
"I encourage my friends to buy this brand"
In the analysis stage, can I define this statement to represent (measure) more than one variable, for example Brand Loyalty, and Customer Satisfaction ??
Thank you
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Totally agree that you need to keep the questionnaire as short and concise as you can. (And on re-reading my response not entirely sure I am being helpful in regard to length.) However, it would seem that you have not analyzed / broken down the constructs as thoroughly as you could. i.e. different variables make up the constructs.
Early in the questionnaire you should test awareness of brands … maybe it is a simple factor that people are not aware of the product/brand.
You may also be interested in the pricing differentials. i.e. if brand X is the premium brand you could look at how much cheaper the closest competitor has to be to switch purchase. Maybe brand image is not as important as price!
Then presuming you have established the buying factors either by groups or a literature review, you would position the different brands on the scales that describe them. (e.g. for a food product the two ends of a semantic differential could be extremely pleasant taste / not at all pleasant tasting)
If I was measuring brand loyalty, I would consider several indicators and where applicable have a probe: Why do you say that?
(In the following I am trying to think of the type of questions that would be useful. Assume brand X is the focus…)
1) Purchase profile:
Which brands of product are you aware of? (spontaneous)
Show list Which of these brands of product have you ever used?
If uses target brand: How many out of the last 10 times that you bought this product did you buy brand X ?... or could rather ask this Considering this list of Brands – of your last 10 purchases of this product how many were Brand X, Brand Y, Brand Z and so on.)
2) Attitude to brands: For the top three brands: What words would you use to describe brand X? Brand Y? Brand Z?
Is Brand X better/the same/ not as good as other brands?
3) Usage time: For approximately how long have you used Brand X? OR When did you start using brand X?
4) Substitution: If Brand X was not available would you
a) Not buy the product at all
b) Go to an outlet where you could buy brand X
c) Buy another brand
d) Buy another product type
e) Other (state)
5) Recommendation: How likely are you to recommend brand X to your friends? (very likely / likely / neither likely, nor unlikely / unlikely / very unlikely)?
6) Unique benefits: What benefits does brand X have that the other brands do not have?
7) Comparison of brand features --- Use Likert scales to measure the importance of product features. Then use semantic differentials to get the respondents to rate the different brands on the product features.
You can see that in some of the above one question can provide insight into different aspects of the various brands relative positions….
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Customer retention is more powerful than customer satisfaction:
a.over 60% of an organizations future revenue will come from existing customers.
b.a 2% increase in customer retention has an equivalent impact upon profitability as a 10% reduction operating costs.
c.91% of the unhappy customers will never purchase goods and services from you again. d. it costs 5 times as much to attract a new customers as it costs to keep an old one.
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Hennig-Thurau, T., & Hansen, U. (Eds.). (2013). Relationship marketing: Gaining competitive advantage through customer satisfaction and customer retention. Springer Science & Business Media.
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I'm conducting a comparative customer satisfaction study (comparison between costumer satisfaction of public transport services in differentes cities of the same country)..I'm realy confused because I couldn't find any clear response in literature. Some authors used the same sample size while others used differents sample sizes!! The empirical litterature is inclusive about this..what do you think?
NB: I'm using a 5 Likert Scale (1=very unsatisfied...5=very satisfied) for 13 items in my survey
I hope find a quick response for my question...thank you in advance
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To have equal sample sizes is not at all a must.
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Looking specifically for research that has highlighted a strong correlation between customer satisfaction score growth/drop and growth/drop in revenue.
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Objective of the Study:
1. To determine the Retail Marketing Mix Elements towards Retail industry.
2. To determine the Impact of Retail Marketing Mix Elements on the Customers Buying Behavior & Customer Satisfaction
3. To Know the buying behavior and customer satisfaction towards the retail industries in Pune Region.
4. To Highlight on the Purchasing Pattern, Expenditure Pattern and Buying Perception of Customers.
5. To Know the opportunities and Challenges before Retail Industry, and to suggest the suitable remedies to overcome the problems
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Extensive research on this topic has been done. If u still want to pursue this topic. Search for new variables.
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I'm doing a research using QFD tools.
The research is about designing service for public transportation in Bandung.
The population i use (so far) is the population in Bandung which approximately about 3 million.
I found couple of rule of thumb in determining sample size such as Malhotra (minimum of 200) or Hair ( minimum of 5 per variable, but i found this rule of thumb in factor analysis chapter. So yeah i'm a bit unsure). 
I know formula for determining sample size for Mean, but what i measure here is a questionnaire with Likert scale. And so far i haven't found suitable formula/theory in determining sample size for Likert scale. 
if any of you familiar with this please kindly let me know
thank you
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To measure performance, I would not worry about the sample. If I would worry with whom to compare me. I understand that the key is to locate the best in the world, the best regions of the world in the case of the issue and other actions that are culturally very close. The comparative evaluation is good, it will show where the disadvantages are, analyzing costs, tariffs, inputs, resources, quality of processes and losses of all kinds. Take the opportunity to share a publication in which you will compile various cases of the public sector.
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Most people expect businesses to behave the way friends do—like they trust and care about each other. How can we elevate the human experience in any organization?
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Thank you! Following! Best regards: Julia Doncheva
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Deep eye, a novel automatic data visualization system leverages ML techniques as black-boxes and expert specified rules with promising results.
What is your thought on automatic data visualization?
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Anything you can to us Dennis Mazur ?
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I am doing research on the above topic. What are determinants of customer satisfaction in case of classic theatre or performing arts in general?
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Interesting topic. Scientific research in specific fields of art, such as theater, for example, is now particularly important because the development of theatrical art is determined by many factors. On the one hand, the development of the theater is threatened by new online media. On the other hand, in some countries, along with the increase in citizens' incomes, the number of people visiting theaters is growing.
Best wishes
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Please help me by recommending the basic factors those affect the customer satisfaction in context of Online shopping.
I will be highly pleased and thankful if anyone recommend me the previous published "conceptual framework for customer satisfaction" in respect of online shopping.
Thanks .......
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You can read the end of my JBR (2014) :
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Service quality
Customer satisfaction
customer loyalty
customer relationship management
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SERVQUAL cannot really 'measure' service quality. Quality of service is subjective, determined by the receiver. Therefor its measurement should be based on a measure of customer perception. A 10.000 feet definition would be Q=E-P, quality of service is expected service minus perceived service. Determine key result indicators for both, and do the math. A negative outcome reflects a negative perception, etc.
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Iam working on the effect of marketing practices with 7ps on customer satisfaction. so i need measurement scale on marketing mix and customer satisfaction.
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For the concept of satisfaction, you must first do a research in a theoretical framework: The Dissonance Theory, The Contrast Theory, Expectancy-Disconfirmation Paradigm, Inferred versus Direct Disconfirmation, The Comparison Level Theory, The Value Percept Theory, The Equity Theory, The Evaluative Congruity Theory... Then you propose the model of your research. Regarding the elements of the marketing mix, it's much easier.
here are some works that can help you:
Bearden, W.O. & Teel, E.J. (1983). Selected Determinants of Consumer Satisfaction and Complaint Reports, Journal of Marketing Research, 20, 21-28.
Botterill, T. D. (1987). Dissatisfaction with a construction of Satisfaction, Annals of Tourism Research 14: 139-141.
Cadotte, E. R., Woodruff, R. B ., & Jenkins, R. J. (1987). Expectations and Norms in Models of Consumer Satisfaction Journal of Marketing Research 24, 305-14.
Erevelles, S. & Leavitt, C. (1992). A Comparison of Current Models of Consumer Satisfaction / Dissatisfaction Journal of Consumer Satisfaction /Dissatisfaction and Complaining Behavior, 5, 104-114.
LaTour, S. T. & Peat, N. C. (1979). Conceptual and Methodological issues in consumer satisfaction research, Advances in Consumer Research, 6, 431-437.
Tse, D. K., & Wilton, P. C. (1988). Models of Consumer Satisfaction Formation: An Extension. Journal of Marketing Research, 25(2), 204. doi:10.2307/3172652
Olander, F., (1979) Consumer Satisfaction: A Sceptic’s view. Aarhus Denmark.
Oliver, L. R. (1997). Satisfaction a behavioral perspective on the consumer, The McGraw-Hill Companies, Inc. New York.
good luck
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service quality
customer satisfaction
customer loyalty
customer relationship management
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Model of operational risk management based on the synergy of quality management principles, risk mamagement principles and total quality management approach.
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Any one who can guide me on finding measurement scale on marketing mix and customer satisfaction?
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Please check the article in pdf. format available at:
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I am working on a study about hotels, which analyzes the possible influence of job sastifacción (MSQ, 20 questions of scale 1 to 5) on customer satisfaction (scale 1 to 5, questions that evaluate different departments of the hotels). I have data from 12 hotels and a sample of 65 workers (supervisors from 5 departments) and approximately 14,000 clients, who indicated their satisfaction with each department (5 evaluations) of these hotels. I want to estimate a model of structural equations, but I do not know how to match these data, because the subjects answered different questions (tests).
I have thought of starting from the customer data base and then matching the evaluation of each client with the satisfaction of the evaluated worker.
The problem is that the data is repeated a lot. For example, for hotel 1 there are 1956 responses from customers, but there are only 5 responses from workers. I can match the evaluation of department 1 with the satisfaction of worker 1, but that answer will be repeated 1956 times,. I think this will affect the correlation and, therefore, the model of structural equations.
Is there any way to solve this problem? I have tried to find articles with similar studies, but they do not explain in detail how they made the different samples match. Thanks for your attention. I hope you can help me.
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As the sample size is robust two-way ANOVA can be used. But for large data it is important to look at histograms to understand the summary measures. The outliers also need to be addressed. Post this data editing regression will deliver results if the dependent variable is on metric scale.
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TITLE: Leveraging Artificial Intelligence & Image Processing for Online Inspection of Packed Cases
1.BACKGROUND: Leaves of a crop are threshed and are packed into 200 Kg cases. 10% of these packed cases are later inspected for conformity to the master case approved by the customer in terms of Color, Ripeness and Uniformity. The quality inspection processes are manually operated and rely on the judgmental experience of the experts. The judgment is heavily driven by personal, business and environmental factors and is highly subjective.
2.PROBLEM DESCRIPTION: Inspection is a crucial activity to ensure customer satisfaction. Although it doesn’t eliminate the defects in the product, it helps identify the defective products before they are dispatched to the customer. The limitations with the existing inspection process is multi-fold. • While Customer expects all the cases to be inspected, due to space and man-power constraints, today, the business is able to achieve only 10% inspection. • As the inspection process happens one day after the cases are processed, due to limitations with Expert availability, real-time corrective actions in the factory in case of deviations in product quality gets difficult • Due to human involvement in the visual inspection, there is inherent subjectivity involved in the process
3. PROBLEM STATEMENT: To automate in real-time, the packed case inspection using Machine Learning and Image Processing techniques and enhancing the objectivity of the inspection process.
4. PROJECT DELIVERABLES: (a) To develop 3 separate algorithms which imitate Color, Ripeness and Uniformity inspection while keeping the processing time for each of the algorithms under 1 minute each (b) The developed Algorithms to be generic of the grade type for all Color, Ripeness and Uniformity dimensions (c) To identify patterns for Color, Ripeness & Uniformity inspection, if any by understanding the way Algorithm is functioning
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You definitely can. You could either develop independent models for each aspect of the inspection process, or develop a single multi label model for the whole inspection process.
I'd probably consider only using ml / ai models for characterising ripeness and uniformity and using other computer vision techniques for characterising colour.
In terms of real time operation, something like the Nvidia Jetson tx2 board would allow you to run complex machine learning algorithms in real time and meet the time constraints you specify.
Hope this helps.
Alex
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A little over a decade ago, Vineet Nayar CEO of HCLT, developed the model “Employee First Customers Second” or EFCS, for his firm and in so doing built a highly successful business around that paradigm and scored major accolades for re-inventing the 21st Century Business Management Model leading to a book of the same name.
How is the model in practice one decade later ?
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To quote CK Prahlad from his foreword to the book (Employees First Customers Second), this book is a narrative of organizational transformation and a practical guide for managers who wish to achieve similar results, as well as a story of the personal transformation of a CEO.
What struck me as significant about the book were the following aspects:
It is about the journey of an organization very Indian in its origins and culture
and about the experiences of an Indian CEO in bringing about change within
this psyche – this means it is a journey we can all relate very well to and draw
a lot of practical lessons from.
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I am doing survey research of customer right now so that I want to identify the minimum percentage that can be stated customer satisfy towards the service and quality of company. May I guess is it between 70 % and 90 %. I need the exact percentage about this. May anyone can give me assistance to answer my question. Thanks a bunch.
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One small note to my previous post:
when measuring customer satisfaction, it is sometimes appropriate to consider the "zone of tolerance" – The difference between level of quality expectations and level of quality desires.
See for example:
Van Riel, A., Semeijn, J., & Janssen, W. (2003). E-service quality expectations: A case study. Total Quality Management & Business Excellence, 14(4), 437–450. doi:10.1080/1478336032000047255
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Intention to recommend, intention to revisit, WOM, E-WOM, customer loyalty, customer satisfaction, customer trust, customer retention are already overflowing. Any new and rare suggestion? I appreciated so much for all your ideas!
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I don't understand the question. A model doesn't come into being like a recipe that you adapt as you like. If you want to work empirically (that's how I understand your question), it has to be driven by theory, right?
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I have 6 IVs as web experience dimensions which shows relationship to DV customer satisfaction, the the same model extends and DV customer satisfaction as IV showa relationship with another DV customer loyalty with mediation of Trust. is it possible to run this two stages model in PLS.
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You can even test more complicated models. The only thing which one needs to keep in mind is the presence of a theory or arguments behind every path.
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Good evening,
I am currently writing my dissertation using SPSS and I would like to know if PCA should be run selecting ALL the items of the questionnaire or just the items belonging to each variable.
Here is the example:
I have 8 variables in the questionnaire measured by 3 or 4 items each. So, let's say the first is customer satisfaction (CS). It has CS1(ex: I am satisfied with the product), CS2, CS3, CS4 as items. Then I have customer experience (CE) which has CE1, CE2, CE3. And so on.
Do I have to run factor analysis first on Customer satisfaction and its 4 items and so on with each variable separately or do I select alla the items of the questionnaire (CS1,CS2,CS3,CS4,CE1,CE2,CE3,....) and run the analysis?
I am quite confused.
N.B. Scales were not created by me, they were taken from other studies.
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There are some methodological issues here.
1) It seems you confuse PCA with factor analysis. They are different. Principle component analysis (PCA) is descriptive like dimension reduction technique. It accounts for total variance/covariance within the data. Factor analysis (FA) is a latent variable approach. It models the shared variance/covariance within your data. (covariance matrix minus uniqueness).
2) Factor analysis assumes your data is multivariate normally distributed. So the factor analysis you are referring to only deals with continuous data. I think the manifest variables in your data are probably discrete.
3) Item response theory (IRT) models deal with discrete manifest variables. You should look into that. But there are other issues there. For example, you probably don't have enough data to get good parameter estimates.
4) My suggestion is to keep it simple. Since it's a published survey. Is there a paper that provides weights to compute composite scores?
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Hi all,
How best to analyze the data i have on "Knowledge Management Maturity Level" in Relation to "Customer Satisfaction" over the last 5 years?
See data in the attachment which im trying to analyze.
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The objective, as mentioned, is not clear. It is to be made more specific and more clear.
I mentioned that the sample size is small (not reasonably large) if objective is to study the relationship (regression) between "Knowledge Management Maturity Level" and "Customer Satisfaction". In this case, the set of 5 pairs of data on "Knowledge Management Maturity Level" and "Customer Satisfaction" corresponding to the 5 years 2013 , 2014 , 2015 , 2016 , 2017, is not reasonably large to obtain findings with reasonably high degree of accuracy..
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Measurements for customer satisfaction.
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there are 5 measures which can measure customers satisfaction and
1-Empathy
2- Responsiveness
3- Assurance
4- Physics
5- Reliable
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As part of my doctoral research, I intend to monitor customer satisfaction before and after an intervention in training customer service representatives in a particular aspect of service provision. The organisation completes regular customer satisfaction surveys and has offered access to this. My supervisor would like me to either independently validate this data, or triangulate with my own survey. I think it's unlikely that the organisation will allow me direct access to customers to perform my own survey, so I'm looking at validation instead. Not sure how to go about that though.
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You could have a group of peers validate the instrument or possibly your committee can validate.
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What theory applies in this case:
, how the variable of H1( price increase to customer retention), interact with H2 (price increase to customer satisfaction ), and therefore with H3 (Customer retention to customer satisfaction).
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I echo Christian Arnold's remarks about the model. However, there may be some insights from the relationship marketing literature you could adapt. Retention and satisfaction might, for example, be discussed in terms of behavioral vs. attitudinal loyalty. A customer might be displeased with Netflix's price increase (indicated by a reduction in satisfaction) yet voluntarily continue the relationship with Netflix (retention). Loyalty in this example is behavioral rather than attitudinal; the customer is retained because (perhaps) they see no viable alternative to obtain the benefit sought.
Another example (one often used by Peppers and Rogers) is Ryanair, the deep-discount airline. Customer satisfaction with Ryanair is low, yet retention is high, because there are no viable alternatives for the benefit customers seek: getting quickly and inexpensively from the UK to say, Spain for the weekend. Behavioral loyalty is high, but attitudinal loyalty is low, leaving Ryanair vulnerable in the event a viable alternative does emerge.
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Hi
I am trying to evidence the benefits of using a 10 point customer satisfaction scale if anyone has any recent papers or articles that would support this or demonstrate the benefits.
I am particulary interested in the use in the UK public sector - especially in Social Housing customer satisfaction surveys.
I really feel that a 10 point scale adds much more depth to that data over a traditional verbal, five point scale but want to make sure I have a robust backing for this!
Thanks
Eve
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Hello Eve. The argument is a statistical one; 1 to 10 scales offer greater variability (variance) when compared to 1 to 5 or 1 to 7 Likert scales. I recommend the use of 1 to 10 scales, specialy if you expect arround 80% of the answers to fall in the top or bottom ends of 1 to 5 or 1 to 7 scales. Best Regards.
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I m doing a research on POS and Customer satisfaction.
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POS is an umbrella concept. We are unable to measure it directly. A lot of POS-related constructs such as Psychological capital (hope, optimism, efficacy, and resiliency; as Dhani Shanker Chaubey mentions), Mindfulness organizing, Virtuousness, etc. Some have been conceptualized and operationalized at the organizational/unit level, some at the individual level, and some at both level. A very good ref book is The Oxford Handbook of Positive Scholarship, Edited by Cameron KS & Spreitzer GM; Oxford Uni Press 2012.
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Can we use control variables like (age, gender, education, or other categorical, demographic variables etc...) along with other constructs(endogenous variables) while running/testing SEM-PLS model.
Ex ; Usually we are running path model on likert scale, e.g. for assessing the path/drivers of customer satisfaction/loyalty, Can we simultaneously test the effect of Gender, Age, Education etc.. in the same model?
#SmartPLS
Regards,
Abhay
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Agree with you
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I just want to find the relationship between these two constructs. Is there any correlation between Service Quality and Customer Satisfaction? Which one is independent and which is dependent variable? Perhaps you can refer me to some quality papers that have investigated the relationship between these two constructs.
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Extensive research has been done on these constructs across service industries.How ever some moderated or mediated relationships may be tested. Mostly customer satisfaction is studied as a dependent variable.
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I have seen a lot of theories talking about service industry and customer satisfaction but very few on Manufacturing.
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Theories and models are similar. Many of the consumer behaviour models viz. Assael' framework, Jagdish N Sheth's model in the field of Consumer Behaviour are very popular for manufacturing industries.
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I am looking for a basic survey tool to adapt in my study. The survey will be used as an additional source of evidence in a field experiment. Hence, I am looking for a survey with few questions.
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Could anybody share papers on measuring customer perception and satisfaction towards adoption of mobile banking services?
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PLS READ THIS PAPER
Integrating Quality Features into Technology Acceptance Model for Examining the Acceptance of Mobile Banking
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The aim is to create an alternative model of airport service card. I want to focus on the performance and importance of the single factor that influence airport service quality
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I would recommend to implement Llosa's Tetraclasse model. See that document on page 13. Best regards.
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I want to do factor analysis for finding the factors that affect the dependent variable such as customer satisfaction. There are observed variables as indicators/items for identifying the latent constructs or factors. There are observed variables to measure the dependent variable such as customer satisfaction. If, I do not include the observed variables taken for measuring the dependent variable along with the indicators for doing factor analysis, what will be the effect?
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I understand that you may have a model with a set of independent variables and a dependent variable. May be, you will run a regression analysis later on where the relationship is/are further examined in terms of their direction and magnitude. However, the purpose of factor analysis is different from that of regression. The classification of dependent and independent variable is applicable when you are trying to find a relationship; hence, there is no consideration of dependent or independent variable when you are conducting a factor analysis. The purpose of factor analysis is to see which observed variables load/clusters around a factor so that you can extract valid factors out of many observed variables. In other words, it helps you find out dimensions (if any) of latent variables. It turns out that your independent variable will be treated just like another variable in the factor analysis, therefore, you need to include it in the factor analysis to see whether observed variables really represent/load on the "independent" variable.
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I need this part from the journal
The journal name :
Services innovation impact to customer satisfaction and customer
value enhancement in airport.
Author : James K.C. Chen*, Amrita Batchuluun, Javkhuu Batnasan
Asia University, Taichung, Taiwan
I need this part from the journal (page 223)
(5 questions for service innovation SI1eSI5, respectively as Appendix Table 1. A pre - test of the questionnaire was done to verify the reliability of the scale items).
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I'm doing a research on customer satisfaction with the pharmacy's service in Vietnam. In my study Q-samples consists of 40 statements divided into 5 areas (customer satisfaction with (1) pharmacy, (2) medicines, (3)medicines use, (4) consulting, (5) attitude and knowledge).
I need to calculate the Q-participants sample size to represent all people in Vietnam.
I intend the sample size as follows:
A. Your gender: (a1) Male (a2) Female
B. What is your current age?
(b1) 18 to 29 years    (b2) 40 to 49 years    (b3) 60 – 69 years
(b4) 30 to 39 years    (b5) 50 to 59 years    (b6)  70 years or older
C. Education completed:
(c1) Less than high school graduate
(c2) High school graduate
(c3) Technical school
(c4) University or College graduate
(c5) Masters or other higher degree
Q-participants sample size = ([A].[B].[C]) x 3 = (2 x 6 x 5) x 3 = 60 x 3 = 180 participants
Will this calculation be reasonable?
I look forward to receiving advice!
Thank you!
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Way too many participants. Here is a message that I posted to the Q list just today. Sorry for the delay but there has been a problem with my ResearchGate account.
From: Steven Brown <sbrown@kent.edu> Date: Tuesday, October 3, 2017 at 8:34 PM To: Q-Method Discussion List <Q-METHOD@LISTSERV.KENT.EDU> Subject: Re: Inquiry about determining the number of participants in the P-set
The different points of view about volunteer value already exist before the Q study is undertaken, and the purpose of the study is to adopt a strategy that will enhance the likelihood that those factors will appear.  The central principle that has usually been recommended in this endeavor is Brunswik’s (1947, 1956) representative design, which mandates bringing a representative set of participants into contact with a representative set of stimuli, and the operation for achieving this has usually been expressed in terms of one of Fisher’s (1935) experimental designs, most typically the factorial variant.  It is unclear whether Susan Carter Kahl has structured her “approximately 50 indicators of volunteer value,” but she has given hints as to how her P-set might be structured––i.e., in terms of (a) nonprofit funders, (b) senior leaders, and (c) volunteer administrators, which can be thought of as three levels of a completely randomized (or one-way ANOVA) design.  (There might be other groups that could be suggested; e.g., academic and professional experts on volunteer organizations.)  Are there other person variables that might be considered pertinent, e.g., gender?  If so, then the previous levels could be cross-classified with (d) female and (e) male, giving rise to a 3x2 factorial arrangement (2-way ANOVA).  I am not recommending gender, which may be irrelevant insofar as volunteer values are concerned, but if we accept this 3x2 = 6-cell design for illustrative purposes, and if we accept a goal of 40 or so respondents, our design would dictate that we seek out approximately 7 participants from each of the 6 combinations––i.e., 7 female funders (ad), 7 male funders (ae), 7 female senior leaders (bd), etc.––for a total of 7x6 = 42 participants, with all combinations represented.  It should be noted that as a practical matter, we rarely seek out exactly equal numbers per cell, but the design provides us with an ideal and a map that we use when seeking out participants.  We expect that these six logical categories will eventually be superseded by the functional categories that emerge. As to the desirable number of participants, this cannot be determined in advance.  The important matter is not the number of Q sorters in general, but the number of persons defining each of the Q factors; i.e., the number of persons who have factor loadings that are pure for each of the factors.  As a rule of thumb, we like to have 4 to 6 persons with relatively high factor loadings that are purely loaded on each factor; however, we don’t know in advance how many factors there will be, nor do we know which participants will be on which factors.  If there are only three factors, we only need about 15 participants (5 per factor), but since we don’t know who will end up where, we over–sample––hence, the suggestion that 30-40 Q sorters be obtained in the hopes that after the factors have been obtained, each will have at least a half dozen or so that are purely defining. Doing first-order analyses by demographic groups isn’t a good idea, in general, since it bears similarities to the R-methodological focus on variables.  We bow to those demographics in the P-set structure, but then abandon the ANOVA designs, and their variance analyses, in favor of the Q factors (Stephenson, 1993-1994) because the latter are functional (Brown, 2002).  If there is truly a functional distinction between nonprofit funders and senior leaders, then members of these groups will appear for the most part on separate factors when all factor analyzed together.  If they don’t, then the factors constitute more accurate expressions of the situation. References Brown, S.R. (2002).  Structural and functional information.  Policy Sciences, 35, 285-304. Brunswik, E. (1947).  Systematic and representative design of psychological experiments.  Berkeley and Los Angeles: University of California Press. Brunswik, E.  (1956).  Perception and the representative design of psychological experiments (2nd ed.).  Berkeley: University of California Press. Fisher, R.A. (1935).  The design of experiments.  Edinburgh, UK: Oliver & Boyd. Stephenson, W. (1993-1994).  Introduction to Q-methodology.  Operant Subjectivity, 17, 1-13.
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I am working on similar project where my project based on customer satisfaction on Malaysia Airlines.
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Yes, I did
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Hello everyone,
I have collected the user requirements from various stakeholders for my project. Now the major challenge is to convert these user statements/user wishes into technical specifications. I have found from my literature review that QFD (Quality function deployment) can be one of the options for converting the statements into requirements. However, since I have many statements which have been collected, I am not sure how to proceed with the QFD analysis of user statements. In total around I have 72 user statements. Does anyone has experience of doing this type of user statements analysis? If yes, it would be great if you can share your inputs.
Best Regards
Parth
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Hi,
I have used the QFD in the hospital. My experience in using this method has shown that many customer expectations do not match the organization's functions and objectives.
firstly, you can screen and rank your customers' expectations using stakeholder feedback. Then enter the most important customer expectations into QFD.
You can use one of the MCDM methods for ranking (TOPSIS, AHP, SAW and so on).
In this way, your results will be more practical. And the owners will welcome the results.
Good luck
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What literature do you recommend for digital transformation strategy and its impact customer satisfaction?
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Dear Leonidas A. Papakonstantinidis ,
Thank you for your concern and useful advice and I appreciate your support .
Regards
Raed
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