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Investor risk perception is a personalized judgement on the uncertainty of returns pertaining to a financial instrument. This study identifies key psychological and demographic factors that influence risk perception. It also unravels the complex relationship between demographic attributes and investor's risk attitude towards equity investment.

Exploratory factor analysis is used to identify factors that define investor risk perception. Multiple regression is used to assess the relationship between demographic traits and factor groups. Kruskal–Wallis test is used to ascertain whether the factors extracted differ across demographic categories. A risk perception framework based on these findings is developed to provide deeper insight.

There is evidence of the relationship and influence of demographic factors on risk propensity and behavioural bias. From this study, it is apparent that return expectation, time horizon and loss aversion, which define the risk propensity construct, vary significantly based on demographic traits. Familiarity, overconfidence, anchoring and experiential biases which define the behavioural bias construct differ across demographic categories. These factors influence the risk perception of an individual with respect to equity investments.

The reference for the framework of this study is limited as there has been no precedence of similar work in academia.

This paper establishes that information seekers make rational decisions. The paper iterates the need for portfolio managers to develop and align investment strategies after evaluation of investors' risk by including these behavioural factors, this can particularly be advantageous during extreme volatility in markets that concedes the possibility of irrational decision making.

This study highlights that regulators need to acknowledge the investor's affective, cognitive and demographic impact on equity markets and align risk control measures that are conducive to market evolution. It also creates awareness among market participants that psychological factors and behavioural biases can have an impact on investment decisions.

This is the only study that looks at a three-dimensional perspective of the investor risk perception framework. The study presents the relationship between risk propensity, behavioural bias and demographic factors in the backdrop of “information” being the mediating variable. This paper covers five characteristics of risk propensity and eight behavioural biases, such a vast coverage has not been attempted within the academic realm earlier with the aforesaid perspective.

The paper aims to clarify the multivariate effects of follower communication apprehension (CA) and demographic dissimilarity on follower perceptions of the leader–follower relationship quality (i.e. measured by leader–member exchange (LMX) theory). This study examined the possible mediating effects of follower CA on the relationship between demographic dissimilarity and LMX.

Research was collected from self-report ratings of one member of the dyad; several proactive techniques were utilized to reduce common method variance in the development and administration of the survey instrument. In total, 260 (N = 260) full-time hospitality industry employees participated in the study.

The results of this study indicate demographic dissimilarity has minimal effect on LMX and CA. However, the results indicated that follower CA was negatively related to follower perceptions of LMX quality. In addition, the results indicated that tenure working with the supervisor was negatively related to follower CA and positively related to follower perceptions of LMX quality.

Research results may lack generalizability, and causality cannot be confirmed. Future studies utilizing longitudinal designs and/or data collected from each member of the dyad may provide support for current findings.

This paper includes implications for understanding how situational characteristics influence follower CA and perceptions of LMX to encourage supervisors to increase communication with new subordinates, especially during the organizational acculturation process, thus reducing turnover. Furthermore, the significant relationship between age dissimilarity and CA offers practical implications for managing and celebrating generational differences in the workplace and bridging the gap between generations by maximizing communication between supervisors and subordinates. Communication is an essential consideration in the hospitality industry linked to creativity, relationship building and enhanced service experiences. Ultimately, this paper provides guidance for leaders to build sustainable, positive relationships with subordinates through more effective communication and build more inclusive service-based organizations.

This paper contributes to communication and leadership management practices by addressing four major problems: (1) limited research on situational characteristics that inhibit LMX quality, (2) limited research on communication variables as antecedents to LMX, (3) minimal research on the relationship between CA and LMX and (4) non-existent research on CA as a mediating variable in the relationship between demographic dissimilarity and LMX.

This research develops a data-driven statistical model capable of predicting a US Army Reserve (USAR) unit staffing levels based on unit location demographics. This model provides decision makers an assessment of a proposed station location’s ability to support a unit’s personnel requirements from the local population.

This research first develops an allocation method to overcome challenges caused by overlapping unit boundaries to prevent over-counting the population. Once populations are accurately allocated to each location, we then then develop and compare the performance of statistical models to estimate a location’s likelihood of meeting staffing requirements.

This research finds that local demographic factors prove essential to a location’s ability to meet staffing requirements. We recommend that the USAR and US Army Recruiting Command (USAREC) use the logistic regression model developed here to support USAR unit stationing decisions; this should improve the ability of units to achieve required staffing levels.

This research meets a direct request from the USAREC, in conjunction with the USAR, for assistance in developing models to aid decision makers during the unit stationing process.

This study aims to explore the connection between demographic traits and the choice of attraction patterns among international repeat tourists.

The study employed a questionnaire survey to collect data from 1550 international repeat tourists who visited Tanzania between November 2022 and July 2023. Convenient sampling was employed as tourists were selected from the three international airports of Tanzania, namely Kilimanjaro International Airport, Julius Nyerere International Airport, and Abeid Aman Karume International Airport. A multinomial logistic regression model was used to examine the impact of socio-demographic characteristics on the selection of attraction patterns among international repeat tourists.

The study revealed that demographic factors, including age, marital status, income level, occupation, and education level, exhibit statistically significant correlations with preferences for distinct attraction patterns. This significance was established through a p-value of less than 0.05 for all the aforementioned variables.

This study is primarily focused on international repeat tourists, thereby limiting insights into the preferences of domestic tourists. To better inform strategies aimed at attracting a larger domestic tourist base, future research may prioritize the investigation of choice of attractions patterns among domestic tourists in relation to their demographic characteristics.

This study contributes to the nuanced understanding of international tourist behavior by unraveling the extent to which demographic traits impact tourists’ choices of attraction patterns, thereby providing insights crucial for effective marketing strategies, improved visitor experiences, and sustainable tourism development strategies.

Rural consumers’ in- and out-shopping intention has been a research topic for many years. This study investigates the relationship between social identity and rural consumersʼ intent to shop within their local community, along with a number of moderating demographic variables. Using a sample of respondents from the Midwest, this study found a significant and positive relationship between rural consumers who socially identify with people in their local community and their intent to inshop. The influence of several demographic moderators is also explored, and implications for practice and future re-search are discussed.

To examine demographic factors and travel motivations among leisure tourists in Tanzania. Specifically by examining the influence of demographic factors on travel motivation among local and international leisure tourists in Tanzania.

Approach is quantitative and applied descriptive statistics, independent t-test and ANOVA.

The findings showed that age, gender and family size as demographic factors significantly influenced travel motivation among local and international leisure tourists.

Future studies to consider different approaches including collection of data during the peak season, use qualitative method and conduct studies in other parts of the country to explore demographic factors and travel motivations of tourists.

To assist tourism stakeholders in their design of promotional tools to market tourism products/services to different tourists as opposed to homogeneous marketing campaigns.

Examined the influence of demographic factors and travel motivation among local and international leisure tourists in the context of Tanzania.

This study aims to analyze how ready a firm is to transform into Industry 4.0 using the Readiness Index (INDI 4.0) assessment. It also investigates the differences (before and after) of the program “Making Indonesia 4.0” in 2018 in socioeconomic and demographic aspects.

The INDI 4.0 assessment involved a self-evaluation by 622 companies across 13 industry sectors, subsequently verified by the Ministry of Industry. This study incorporates discussions with industry experts to enhance the interpretation of the analytical findings.

This study explores the interrelation among the components of INDI 4.0 across different levels, assessing the readiness of each sector for Industry 4.0. The findings reveal the diverse impact of implementing Industry 4.0 in Indonesia on socioeconomic and demographic aspects. Furthermore, the study proposes several policy recommendations for the Indonesian government’s consideration.

This study’s scope is confined to the industrial context of Indonesia, as the assessment components are tailored to the specific characteristics and culture of the country’s industry. Subsequent research endeavors can leverage this study as a foundational reference, adapting the components to align with the particular interests of other nations.

Businesses, especially those in Indonesia, can employ these findings to evaluate their position in the context of Industry 4.0 transformation compared to their industry. Simultaneously, the Indonesian government can use these results as a starting point to evaluate and potentially enhance their policies related to Industry 4.0. We recommend five policy proposals for the Indonesian government: diversifying measurement models, shifting terminology, emphasizing soft skills, promoting continuous learning and implementing Center of Digital Industry Indonesia 4.0 (PIDI 4.0) initiatives.

This study offers a broad impact of Industry 4.0 implementation in socioeconomic and demographic aspects in Indonesia, such as income, job-shifting, age, educational background and gender.

To the best of our knowledge, no prior research has explored the repercussions of industrial implementation on socioeconomic and demographic facets.

Our paper studies a central issue with a long history in economics: the relationship between population and economic growth. We analyze the joint dynamics of economic and demographic growth in 111 countries during the period 1960–2019.

Using the concept of economic regime, the paper introduces the notion of distance between the dynamical paths of different countries. Then, a minimal spanning tree (MST) and a hierarchical tree (HT) are constructed to detect groups of countries sharing similar dynamic performance.

The methodology confirms the existence of three country clubs, each of which exhibits a different dynamic behavior pattern. The analysis also shows that the clusters clearly differ with respect to the evolution of other fundamental variables not previously considered [gross domestic product (GDP) per capita, human capital and life expectancy, among others].

Our results indirectly suggest the existence of dynamic interdependence in the trajectories of economic growth and population change between countries. It also provides evidence against single-model approaches to explain the interdependence between demographic change and economic growth.

We introduce a methodology that allows for a model-free topological and hierarchical description of the interplay between economic growth and population.

This paper aims to study and measure the level of the psychological well-being, of the employees in IT/ITES organizations and to find out whether the psychological well-being (PWB), of the IT/ITES employees significantly varies with their socio-economic and demographic profiles.

Study was conducted among the employees in IT/ITES companies in Infopark, a cluster of companies, in Cochin. There are 30,000 employees estimated as working in different companies in Infopark. Considering the size of the population, the researcher targeted 1200 sample respondents (covering 4% of the population) and distributed 1400 questionnaires to IT/ITES employees of different companies in Infopark. The response rate was 78%, hence, the researcher could get back 1092 filled questionnaires. However, out of 1092, filled questionnaires, 24 questionnaires (2.20%) were found to be either incomplete or with mistakes and hence not in usable nature. These were eliminated from the final sample. The final sample for this study is (1092–24) thus taken as 1068 IT/ITES employees (3.56%) in Infopark, Kochi. psychological well-being (PWB) of the employees in IT/ITES organizations was measured using the PWB scale by Ryff (1989). Data analysis was done using parametric tests like, independent sample test and analysis of variance.

The current study tries to explain the variation in PWB, of IT/ITES employees with respect to their socio-economic and demographic profiles. Based on the independent sample t-test and one-way ANOVA test results relating to H1a (gender), H1b (age), H1c (work-experience) and H1d (employment level) the overall hypothesis H1: PWB exhibited by the IT/ITES employees significantly varies with their socio-economic and demographic profiles is rejected. Hence it is concluded that PWB among IT/ITES employees do not significantly differ with respect to their socio-economic and demographic profile.

The study results may help the academia, trainers and researchers to identify new ways of improving PWB among employees. It will also help them to focus on training programmes, targeting toward the betterment of PWB. Policymakers' role is significant in promoting PWB among employees so as to ensure sustainable organizational performance.

The study will help managers to provide a conducive work place where employees are psychologically mature and carry positive attitude toward work, work environment and co-workers. Planned interventions are necessary to enhance team spirit, cooperation, cohesiveness and collaboration among employees.

With the study findings new psychosocial interventions could be offered to the IT/ITES professionals in the form of training and personality development programmes. This will directly influence team effectiveness among employees.

A study on PWB has not yet been done among the Infopark employees. Thus, a study to assess the level of PWB carried out among IT/ITES professionals in Kochi is quite a new approach. A study of this nature is believed to help employers take measures for enhancing the PWB which will help to improve the team performance and thus the performance of the company as a whole.

This paper explores the empirical relationship between population age structure and bilateral trade.

The author includes age structure in both log and Poisson pseudo-maximum likelihood (PPML) formulations of the gravity equation of trade. The author studies relative age effects, using differences in the demographic structure of each country-pair.

The author finds that a relatively larger share of population in working age increases bilateral exports. This is robust to various estimation models, as well as to changes in the method of specifying the demographic controls. Old-age shares have a negative, but less robustly estimated impact on trade. Estimating instead the balance of trade between trading partners produces similar results, with positive effects of age structure peaking later in working life.

Global populations are poised to undergo a massive transition. Trade a crucial way that the demographic deficits of one country may be offset by the dividends of another as comparative advantages shift along with the size and strength of their underlying workforce.

The author’s work is among the first to quantify the effect of relative age structure between two countries and their bilateral trade flows. Focusing on the aggregate flows, relative age shares and PPML estimates of the trade relationship, this paper provides the most comprehensive picture to date on how age structure affects trade.