Niyoosha Jafari Momtaz, Somayeh Alizadeh and Mahyar Sharif Vaghefi
Nowadays, because of more availability of products, there is an increasing need for companies to establish a strong relationship with their customers. As the fast food industry is…
Abstract
Purpose
Nowadays, because of more availability of products, there is an increasing need for companies to establish a strong relationship with their customers. As the fast food industry is not an exception and has a competitive environment, analyzing customers' behavior helps bridge this gap. Data mining techniques help to segment customers as well as to drive improved customer relationship management. This paper seeks to address these issues.
Design/methodology/approach
This study proposes a new model based on RFM model for defining customers' value as well as using K‐means algorithm to segment restaurants' customers. In addition, the authors combine a new category in the account portfolio analysis in order to analyze the behavior of each cluster.
Findings
A real dataset of an Iranian fast food restaurant chain is employed to show the procedure of the authors' model. The customers are segmented into four clusters. The clusters are analyzed and named based on categories in the account portfolio analysis. The result of this analysis shows that there is no significant difference between the behavior of the most valuable customer and customers who have left the restaurant. Therefore, restaurant managers should seek other reasons for detecting churn behavior.
Originality/value
This paper helps managers in the fast food industry to readily analyze their customer behavior in order to understand their needs and establish strong relationships.
Details
Keywords
Somayeh Alizadeh, Meena Chavan and Hamin Hamin
The purpose of this paper is to explore the key aspects of service quality within the outpatient context. The secondary aim is to compare views on quality of health service by…
Abstract
Purpose
The purpose of this paper is to explore the key aspects of service quality within the outpatient context. The secondary aim is to compare views on quality of health service by Caucasian and non-Caucasian patients in Australia.
Design/methodology/approach
A mixed-method approach was adopted for this study. Qualitative data were collected from 40 patients to develop a scale for measuring health service quality. Quantitative data were collected using self-administered questionnaires available in English, Arabic, Persian, Chinese and Vietnamese. A total of 447 patients in six outpatient clinics completed the survey and data were analyzed using the structural equation modeling technique.
Findings
The qualitative findings determined eight dimensions of quality for outpatient care as follows: doctor professionalism; doctor empathy; doctor expertise; treatment outcome; staff concern; timeliness; tangibles; and operation. The quantitative findings indicated that factors related to technical aspect of care, including doctor expertise and treatment outcome were assumed the strongest predictors of overall health care quality in both Caucasian and non-Caucasian groups. Furthermore, no significant discrepancy was found between these two groups’ ratings of overall service quality and satisfaction with care.
Originality/value
The study captured ethnically diverse patients’ perspectives on health service quality and highlighted the significance of technical quality, which is generally neglected in service quality measures.
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Somayeh Fadaei and Alireza Pooya
The purpose of this paper is to apply fuzzy spectrum in order to collect the vague and imprecise data and to employ the fuzzy U control chart in variable sample size using fuzzy…
Abstract
Purpose
The purpose of this paper is to apply fuzzy spectrum in order to collect the vague and imprecise data and to employ the fuzzy U control chart in variable sample size using fuzzy rules. This approach is improved and developed by providing some new rules.
Design/methodology/approach
The fuzzy operating characteristic (FOC) curve is applied to investigate the performance of the fuzzy U control chart. The application of FOC presents fuzzy bounds of operating characteristic (OC) curve whose width depends on the ambiguity parameter in control charts.
Findings
To illustrate the efficiency of the proposed approach, a practical example is provided. Comparing performances of control charts indicates that OC curve of the crisp chart has been located between the FOC bounds, near the upper bound; as a result, for the crisp control chart, the probability of the type II error is of significant level. Also, a comparison of the crisp OC curve with OCavg curve and FOCα curve approved that the probability of the type II error for the crisp chart is more than the same amount for the fuzzy chart. Finally, the efficiency of the fuzzy chart is more than the crisp chart, and also it timely gives essential alerts by means of linguistic terms. Consequently, it is more capable of detecting process shifts.
Originality/value
This research develops the fuzzy U control chart with variable sample size whose output is fuzzy. After creating control charts, performance evaluation in the industry is important. The main contribution of this paper is to employs the FOC curve for evaluating the performance of the fuzzy control chart, while in prior studies in this area, the performance of fuzzy control chart has not been evaluated.
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Keywords
Shahram Sedghi and Somayeh Ghaffari Heshajin
Genetics, a discipline of biology, is one of the most recent and rapidly advancing disciplines in science. This study aims to present a bibliometric analysis of the genetics…
Abstract
Purpose
Genetics, a discipline of biology, is one of the most recent and rapidly advancing disciplines in science. This study aims to present a bibliometric analysis of the genetics research output of Iranian authors, map the intellectual structure of these studies and investigate the development path of this literature and the interrelationships among the main topics.
Design/methodology/approach
This study searched the Web of Science database for documentation of Iranian-published genetics research published up to 2020. Further, this study used HistCite software to profile and analyze the most cited articles and references and to draw their historiographies.
Findings
A database search revealed 21,329 documents that created the study population. The highest cited publications based on the Global Citation Score (GCS) and Local Citation Score (LCS) achieved scores of 602 and 47, respectively. The publication growth rate study demonstrated consistent expansion over time. The scientific maps based on LCS and GCS had five and four clusters, respectively. Furthermore, journal articles emerged as the predominant type of publication.
Practical implications
The significance of this study is in its contribution to understanding the genetics research position in Iran, informing policymakers and researchers, helping scientific collaboration and its impact on public attitudes and quality of life. The results of the present study, with benefits for various groups of communities, such as policymakers, academic groups and public society, can bridge the gap between theoretical research and practical implications.
Social implications
The results of this study, by helping future advancement in health care, medical genetics and disease prevention, may have a direct and indirect positive influence on the quality of life. Furthermore, it may lead to more informed discussions on health care and biotechnology as well as influencing public attitudes and perceptions.
Originality/value
Ultimately, this study concludes that despite the proliferation of publications in terms of quantity and complexity, especially in areas such as disease diagnosis, prevention and treatment, there remains a need for more attention to other facets of genetics such as biology and biotechnology. Iranian publications are most related to population genetics, human genetics, molecular genetics, medical genetics, genomics, developmental genetics and evolutionary genetics out of 10 branches of genetics. This study reveals patterns in scientific outputs and authorship collaborations and plays an alternative and innovative role in revealing Iranian research trends in genetics.