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Considering the important development that research on debt financing decisions of family firms (FFs) has undergone in recent years, we aim to assess the current state of the literature with the latest advances in this field.

We undertake a systematic review of 42 journal articles published on this topic in recent years.

As a result of our work, new directions for the advancement of this research field are established, such as the consideration of different methodologies and sources of heterogeneity of FFs, the need for an integration of the supply and demand side of funds or the importance of evaluating a diversity of firm-specific and contextual factors affecting the debt financial behaviour of FFs.

Considering the notable development of the field of debt financing decisions of FFs in recent years, we find it opportune and valuable to revise the advances and trends published in the most recent papers. Thus, by connecting previous and current knowledge, we provide an updated integrative model of the state of the art and posit key research questions to solve in the future.

The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

The research aims to examine the influence of perceived value (PV) dimensions on brand loyalty of luxury car owners and to examine the mediating role of attitudinal loyalty (AL) between PV dimensions and behavioral loyalty (BL).

Primary data for the study were gathered from the luxury car owners in Kerala, India. The construct measurements have been adopted from previous research studies. Structural equation modeling with the partial least square (PLS) technique was used to analyze the measurements and conceptual model.

The findings show that out of four PV dimensions among luxury car owners, the hedonic value (HV) significantly influences their AL. Economic value influences BL, and social values have an impact on AL as well as BL, but the relationship of functional value with any is not supported by the results. AL is a strong predictor of BL, and it actively mediates the relationship of HV and symbolic value with BL.

The manufactures of luxury cars provide more importance to hedonic and symbolic elements while launching new models and consider the price perceptions of the targeted customers while making decisions related to brand attachment and brand loyalty.

This study contributes to the decision-making of the rapidly growing vehicle market by examining the perceptions and by providing the effects of perceived values among luxury car owners. Also, it extends the literature by developing a framework for PV dimensions on AL and BL and also incorporated the mediating role of AL.