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The purpose of this study is to identify the drivers of loyalty model in the coffee shop industry in Indonesia based on service quality, store atmosphere and price fairness mediated by customer satisfaction.

The sample size used for this study was 384 customers from 16 most comfortable coffee shops in Jakarta based on Nibble's survey. Confirmatory factor analysis was employed to confirm the attributes of each factor and to assess the validity and reliability, average variance extracted and composite reliability was applied. Further hypothesis testing was performed using structural equation modeling.

The result shows that customer loyalty is affected by service quality – comprising 5 subdimensions: tangible, reliability, responsiveness, assurance and empathy – and price fairness mediated by customer satisfaction. It was found that service quality plays a significant role in the coffee shop industry in Indonesia. However, the store atmosphere was found rejected.

This is the first study integrating service quality, store atmosphere, price fairness and customer satisfaction to study the customer loyalty model in the coffee shop industry in Jakarta.

The purpose of this study is to investigate whether equity market timing has a persistent impact on the firm’s capital structure or not. In achieving this purpose, there are two hypotheses developed in this study. The first hypothesis is that historical price-book-value (PBV) negatively affect leverage; while the second hypothesis is that historical PBV ratio negatively affects the change of cumulative on leverage. The sample of this study is cross sectional data obtained from the Indonesia Stock Exchange for 2001–2011 research period. The author disentangles the sample into subsamples based on IPO+k, in which k is the number of years after the initial public offering (IPO). The results show that most of the regression coefficients in the historical PBV do not have negative impact on the capital structure and only a small part of the regression coefficient of the historical PBV has a statistically negative impact on the capital structure. Therefore, the findings of this research conclude that equity market timing doesn’t have persistent impact on capital structure of the firms in Indonesia.

This study aims to determine the effect of Islamic branding, experiential marketing and word of mouth on college decisions and to find marketing strategies through strengthening Islamic branding based on experiential marketing to increase the number of students at Muhammadiyah-Aisyiyah Higher Education.

This study used a quantitative method, with data collection carried out using a survey method by giving questionnaires to respondents. The respondents' criteria are active students, at least in semester three, who have studied at Muhammadiyah-Aisyiyah Higher Education in Indonesia, using a sampling technique with accidental sampling. Data analysis used Partial Least Square - Structural Equation Modeling to determine the estimated results or model predictions.

The results showed a significant direct effect of experiential marketing, Islamic branding and word of mouth on college decisions. There is an indirect effect between experiential marketing and Islamic branding on college decisions through word of mouth, but the word-of-mouth variable could not mediate the relationship between experiential marketing and Islamic branding on college decisions perfectly.

The limitation of the results of the study is that it uses respondents who are and have participated in learning activities on the Muhammadiyah-Aisyiyah Higher Education, where the Muhammadiyah-Aisyiyah Higher Education has added value compared to other private campuses. The added value on the Muhammadiyah-Aisyiyah Higher Education is the overall learning activity based on Kemuhammadiyahan Islam in Indonesia. Islam Kemuhammadiyahan is the identity of the Islamic branding strategy on the Muhammadiyah-Aisyiyah Higher Education, which is only owned by the Muhammadiyah-Aisyiyah Higher Education.

This study recommends marketing strategies through strengthening Islamic branding based on experiential marketing to increase the number of students at Muhammadiyah-Aisyiyah Higher Education.

The novelty of this research is the addition of experiential marketing and Islamic branding variable measurements on word of mouth and college decisions, especially prospective students to study at Islamic Higher Education in Indonesia.

The purpose of this paper is to assess green marketing as an influential factor in the purchase of real estate. In this study, the consumer citizenship behaviour of young individuals will be studied with an assessment of real estate purchase intention, strategic green marketing orientation (GMO) and tactical GMO.

The sample frame consists of young consumers from India’s metropolitan cities. The respondents were in the range of 18 to 35 years of age. These cities provide a high standard of living, more career options and better educational opportunities. Five separate sections of a standardised questionnaire were used, and a structural equation model was used to assess a total of 393 valid replies.

Green marketing impacts the behaviour that influences the desire of young customer to buy green real estate.

As the focus of this study is primarily on major cities, future research may study similar behaviour in non-metropolitan cities. The study can also be conducted among consumers of other age groups.

The originality, to the best of the author’s knowledge, exists in examining how young consumers’ opinions about green marketing impact their intentions to purchase green houses and real estate in India. This study will be accessible to all parties involved in the housing and real estate industries.

Although the bubble tea market has been growing rapidly in recent years, not many studies have been conducted to understand why consumers revisit bubble tea stores. This study aims to understand consumers' intention to revisit bubble tea stores drawing on the theory of planned behaviour (TPB).

Using the online survey method, data are collected from 166 bubble tea drinkers in Malaysia. Partial least squares structural equation modelling (PLS-SEM) is used to verify the hypotheses.

The findings indicate that attitudes, subjective norms and perceived behavioural control have a significant positive influence on revisit intention. In addition, product quality, price fairness and store atmosphere have a significant positive influence on attitudes. Support is not found for the positive influence of service quality on attitudes.

This study provides fresh insights into the factors that influence consumers' intention to revisit bubble tea stores with empirical data from Malaysia. Furthermore, this study also offers useful practical recommendations to bubble tea store owners or franchisers on how to retain consumers.

The primary aim of this study is to review the studies from different dimensions including type of methods, experimentation setup and evaluation metrics used in the novel approaches proposed for data imputation, particularly in the machine learning (ML) area. This ultimately provides an understanding about how well the proposed framework is evaluated and what type and ratio of missingness are addressed in the proposals. The review questions in this study are (1) what are the ML-based imputation methods studied and proposed during 2010–2020? (2) How the experimentation setup, characteristics of data sets and missingness are employed in these studies? (3) What metrics were used for the evaluation of imputation method?

The review process went through the standard identification, screening and selection process. The initial search on electronic databases for missing value imputation (MVI) based on ML algorithms returned a large number of papers totaling at 2,883. Most of the papers at this stage were not exactly an MVI technique relevant to this study. The literature reviews are first scanned in the title for relevancy, and 306 literature reviews were identified as appropriate. Upon reviewing the abstract text, 151 literature reviews that are not eligible for this study are dropped. This resulted in 155 research papers suitable for full-text review. From this, 117 papers are used in assessment of the review questions.

This study shows that clustering- and instance-based algorithms are the most proposed MVI methods. Percentage of correct prediction (PCP) and root mean square error (RMSE) are most used evaluation metrics in these studies. For experimentation, majority of the studies sourced the data sets from publicly available data set repositories. A common approach is that the complete data set is set as baseline to evaluate the effectiveness of imputation on the test data sets with artificially induced missingness. The data set size and missingness ratio varied across the experimentations, while missing datatype and mechanism are pertaining to the capability of imputation. Computational expense is a concern, and experimentation using large data sets appears to be a challenge.

It is understood from the review that there is no single universal solution to missing data problem. Variants of ML approaches work well with the missingness based on the characteristics of the data set. Most of the methods reviewed lack generalization with regard to applicability. Another concern related to applicability is the complexity of the formulation and implementation of the algorithm. Imputations based on k-nearest neighbors (kNN) and clustering algorithms which are simple and easy to implement make it popular across various domains.