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This study aims to explore US hotel guests’ privacy concerns with a twofold aim as follows: to investigate the privacy categories, themes and attributes most commonly discussed by guests in their reviews and to examine the influence of cultural proximity on privacy concerns.

This study combined automated text analytics with content analysis. The database consisted of 68,000 hotel reviews written by US guests lodged in different types of hotels in five European cities. Linguistic Inquiry Word Count, Leximancer and SPSS software were used for data analysis. Automated text analytics and a validated privacy dictionary were used to investigate the reviews by exploring the categories, themes and attributes of privacy concerns. Content analysis was used to analyze the narratives and select representative snippets.

The findings revealed various categories, themes and concepts related to privacy concerns. The two most commonly discussed categories were privacy restriction and outcome state. The main themes discussed in association with privacy were “room,” “hotel,” “breakfast” and several concepts within each of these themes were identified. Furthermore, US guests showed the lowest levels of privacy concerns when staying at American hotel chains as opposed to non-American chains or independent hotels, highlighting the role of cultural proximity in privacy concerns.

Hotel managers can benefit from the results by improving their understanding of hotel and service attributes mostly associated with privacy concerns. Specific suggestions are provided to hoteliers on how to increase guests’ privacy and on how to manage issues related to cultural distance with guests.

This study contributes to the hospitality literature by investigating a neglected issue: on-site hotel guests’ privacy concerns. Using an unobtrusive method of data collection and text analytics, this study offers valuable insights into the categories of privacy, the most recurrent themes in hotel guests’ reviews and the potential relationship between cultural proximity and privacy concerns.

The “sharing economy” has blurred the lines between personal and commercial operations for many sectors of the economy. A convergence has occurred between hotel companies and home sharing platforms, as Airbnb is investing in brick-and-mortar hotels, and conversely hotel companies are investing in home sharing platforms as each of the sectors tends to mimic the other. Important aspects for the hosts of Airbnb are the quality of social interaction between guest and host and the level of authenticity of social exchanges provided by interactions with locals. There is both a quantitative and qualitative demonstration of professionalization within Airbnb's organization. The aim of this research is twofold: to measure to what extent guests are aware of the professional level of the host and to evaluate the importance of these professional aspects at the different moment of the vacation process (booking, stay, and post experience).

Robo-advisory has become an increasingly popular asset management tool in recent decades. This paper studies the association between robo-advisor usage and perceived financial satisfaction.

Using data extracted from the National Financial Capability Study 2015 (NFCS2015), the present study carried out a logistic analysis that examines the association between robo-advisory and perceived financial satisfaction. This model also studies the interaction effect of age on this association.

The present study finds that robo-advisor usage is positively correlated with a person’s perceived financial satisfaction after controlling for covariates related to financial literacy and other demographic factors. Moreover, the present study reveals that age moderates the association between robo-advisory usage and financial satisfaction. The results are robust after regressing financial satisfaction on robo-advisory by different age groups.

This paper extends existing literature on robo-advisory by showing that robo-advisory usage relates to a higher level of financial satisfaction. This finding helps understand the rapidly increasing trend of robo-advisory in the financial industry. Moreover, the present study reveals a moderate effect of age on the association between robo-advisory usage and perceived financial satisfaction.

This paper aims to review, systematize and integrate existing research on disposition effect and investments. This study conducts bibliometric analysis, including performance analysis and science mapping and thematic analysis of studies on disposition effect.

This study adopted a thematic and bibliometric analysis of the papers related to the disposition effect. A total of 231 papers published from 1971 to 2021 were retrieved from the Scopus database for the study, and bibliometric analysis and thematic analysis were performed.

This study’s findings demonstrate that research on the disposition effect is interdisciplinary and influences the research in the domain of both corporate and behavioral finance. This review indicates limited research on cross-country data. This study indicates a strong presence of work on investor psychology and behavioral finance when it comes to the disposition effect. The findings of thematic analysis further highlight that most of the research has focused on prospect theory, trading strategies and a few cognitive and emotional biases.

The findings of this study can be used by investors to minimize their biases and losses. The study also highlights new techniques in machine learning and neurosciences, which can help investment firms better understand their clients’ behavior. Policymakers can use the study’s findings to nudge investors’ behavior, focusing on minimizing the effects of the disposition effect.

This study has performed the quantitative bibliometric and thematic analysis of existing studies on the disposition effect and identified areas of future research on the phenomenon of disposition effect in investments.

This study aims to propose an integrated view and emphasize the importance of bank intangible value binding in customers' robo-advisory adoption. It explores the relationship between robo-advisors and traditional banking and defines the role of bank intangible assets value. It also attempts to understand if trust in the banking institution and the financial consultant determines the effect of these relationships.

The target sample of the study was investors who currently use wealth management services. This study collected 228 valid questionnaires and then executed structural equation model analysis to test the hypotheses.

Results showed that intangible value bindings play a mediating role, which positively affects consumers' willingness to adopt robo-advisors. Consumers' trust in banks and financial consultants are antecedent variables, which positively affect the intangible value bindings between consumers and banks. In addition, when the consumers' investment amount is higher, it will weaken the positive relationship between the intangible value binding and robo-advisor adoption intention.

Most of the past studies have focused on whether robo-advisors would replace personal financial consultants. This study proposes a hybrid model that contains both robo-advisors and traditional banking services, which encourage the acceptance of robo-advisors.

We analyze the role of trust as a driver of speculative investment decisions in technology firms.

Structural Equation Modeling analysis in the context of blockchain technology supports our hypotheses.

Our findings indicate that a general propensity to trust technology leads to trusting beliefs in a service based on technology and that trusting beliefs in a technological service leads to a higher propensity to invest in any firm associated with that service. In addition, we show that in a non-technological context, there is no evidence for such an effect of trusting beliefs in a service on investment decisions. These results support the notion that trusting beliefs are facilitators of speculative investment in technology firms.

The research advances knowledge about the influence of trust in technology on investment decisions; its findings can help build new theoretical models regarding investment decisions using Fintech.

For investors, it is important to realize the potential bias identified in this study, so they can actively avoid adhering to it, thus avoiding exposure to unnecessary risk. Further, beyond individual investors, investment firms take active measures to avoid biases in their own decision-making. Banks and investment firms can help guide their clients about trust-based bias when building their investment portfolio.

Although trust in information systems has been studied extensively, research on the relationship between trust in technology and decisions to invest in technology-related firms is limited.

This study employs firm-level data to evaluate how the knowledge economy impacts the financing constraints of businesses across 106 low- and middle-income nations, focusing on the influence of technological transformation on corporate financing choices.

The research centers on privately held, unlisted firms and examines the distinct effects of knowledge at both the within-country and between-country levels using a panel dataset. Rigorous sensitivity and endogeneity analyses are conducted to ensure the reliability of the findings.

The findings indicate that greater levels of the knowledge economy correlate with reduced financing constraints for firms. However, this effect varies depending on the location within a country and across different geographical regions. Firms situated in larger urban centers and more innovative regions reap the most significant benefits from the knowledge economy when seeking external funding. Conversely, firms in smaller cities, rural areas and regions characterized by structural and institutional inefficiencies in knowledge generation experience fewer advantages.

The impact of knowledge exhibits variability not only within and among countries but also between poor and affluent developing nations, as well as between larger and smaller countries. The knowledge effect on firms' access to external finance is influenced by factors such as financial openness and development, educational quality, technological absorption capabilities and agglomeration conditions within each country.

The purpose of this paper is to study and describe several biases in investment decision-making through the review of research articles in the area of behavioral finance. It also includes some of the analytical and foundational work and how this has progressed over the years to make behavioral finance an established and specific area of study. The study includes behavioral patterns of individual investors, institutional investors and financial advisors.

The research papers are analyzed on the basis of searching the keywords related to behavioral finance on various published journals, conference proceedings, working papers and some other published books. These papers are collected over a period of year’s right from the time when the most introductory paper was published (1979) that contributed this area a basic foundation till the most recent papers (2016). These articles are segregated into biases wise, year-wise, country-wise and author wise. All research tools that have been used by authors related to primary and secondary data have also been included into our table.

A new era of understanding of human emotions, behavior and sentiments has been started which was earlier dominated by the study of financial markets. Moreover, this area is not only attracting the, attention of academicians but also of the various corporates, financial intermediaries and entrepreneurs thus adding to its importance. The study is more inclined toward the study of individual and institutional investors and financial advisors’ investors but the behavior of intermediaries through which some of them invest should be focused upon, narrowing down population into various variables, targeting the expanding economies to reap some unexplained theories. This study has identified 17 different types of biases and also summarized in the form of tables.

The study is based on some of the most recent findings to have a quick overview of the latest work carried out in this area. So far very few extensive review papers have been published to highlight the research work in the area of behavioral finance. This study will be helpful for new researches in this field and to identify the areas where possible work can be done.

Practical implication of the research is that companies, policymakers and issuers of securities can watch out of investors’ interest before issuing securities into the market.

Under the Social Implication, investors can recognize several behavioral biases, take sound investment decisions and can also minimize their risk.

The essence of this paper is the identification of 17 types of biases and the literature related to them. The study is based on both, the literature on investment decisions and the biases in investment decision-making. Such study is less prevalent in the developing country like India. This paper does not only focus on the basic principles of behavioral finance but also explain some emerging concepts and theories of behavioral finance. Thus, the paper generates interest in the readers to find the solutions to minimize the effect of biases in decision-making.

Financial services industry is increasingly showing interest in automated financial advisors, or robo-advisors, with the aim of democratizing access to financial advice and stimulating investment behavior among populations that were previously less active and less served. However, the extent to which consumers trust this technology influences the adoption of rob-advisors. The resemblance to a human, or anthropomorphism, can provide a sense of social presence and increase trust.

In this paper, we conduct an experiment (N = 223) to test the effect of anthropomorphism (low vs medium vs high) and gender (male vs female) of the robo-advisor on social presence. This perception, in turn, enables consumers to evaluate personality characteristics of the robo-advisor, such as competence, warmth, and persuasiveness, all of which are related to trust in the robo-advisor. We separately conduct an experimental study (N = 206) testing the effect of gender neutrality on consumer responses to robo-advisory anthropomorphism.

Our results show that consumers prefer human-alike robo-advisors over machinelike or humanoid robo-advisors. This preference is only observed for male robo-advisors and is explained by perceived competence and perceived persuasiveness. Furthermore, highlighting gender neutrality undermines the positive effect of robo-advisor anthropomorphism on trust.

We contribute to the body of knowledge on robo-advisor design by showing the effect of robot’s anthropomorphism and gender on consumer perceptions and trust. Consequently, we offer insightful recommendations to promote the adoption of robo-advisory services in the financial sector.