A Study on Elderly Entrepreneurial Intention in the Hospitality and Tourism Industry in China

Abstract

Elderly entrepreneurship is becoming increasingly important as a response to the impact of the aging population and the resulting demand on government support systems, as well as a means of ensuring long-term economic and social development. The purpose of this study is to investigate the elderly's entrepreneurial intentions in the hotel and tourism sector in Ma'anshan City, Eastern China. The researcher used an online survey of older people aged 50 to 64 in a tourism destination that is approaching an aging society stage to see if the Theory of Planned Behavior can explain the entrepreneurial ambitions of the elderly in the hospitality and tourism industry. There were 391 questionnaires gathered in all, 367 of which were valid. The data was analyzed using descriptive statistics and regression analysis. The study reveals that personal attitudes toward entrepreneurial behavior and perceived behavior control are highly influenced by societal norms. It also shows that personal attitude and perceived behavior control are antecedents of the elderly's entrepreneurial intent in this particular industry. This research adds to the research on geriatric entrepreneurship in hospitality and tourism, as well as human resource development for seniors in China, helping to alleviate the country's aging demographic concerns.

1. Introduction

Countries or areas across the world’s various regions have reached different stages of population aging (United Nations, 2019). Increased life expectancy, declining fertility rates, and the aging baby boom generation lead to a rising proportion of the elderly (Biron & St-Jean, 2019). A growing number of older people will affect how and to what extent they stay in their jobs or remain economically active through other means (Kautonen et al., 2011). The accelerated aging population raises several concerns regarding business creation (Biron & St-Jean, 2019), thus keeping seniors within the active population could positively affect health and the economy (Heimonen, 2013).

As one way of responses to the challenge of aging population, elderly entrepreneurship has a positive impact on giving full play to the advantages of the human capital of the elderly, improving their quality of life, reducing the pressure on the government to provide for the aged, and promoting social and economic development (Kerr, 2019; Bond et al., 2005; Kautonen et al., 2014). Moreover, entrepreneurship as a career choice for seniors promotes economic growth and job creation for societies (Heim, 2015; Biron & St-Jean, 2019).

SMEs’ prevalence in hospitality and tourism is a dominant feature of this sector (Lashley & Rowson, 2007). Low entry barriers, low financial requirements, and the perception of low skill sets required may entice many entrepreneurs or small business owners with little experience to start firms in the hotel and tourism industry (Lee-Ross & Lashley, 2010:169). Elderly entrepreneurship, particularly in the hotel and tourism industries, could be a viable employment option in later life. It has the potential to encourage the elderly, create value, increase employment, and promote economic development, all of which can help to mitigate the negative effects of population aging (Kautonen et al., 2014).

The emergence of new enterprises is the result of individuals’ cognitive processes, which has been recognized by certain studies (Segal et al., 2005; Liñán & Chen, 2009; Liñán et al., 2013). Since the entrepreneurial intention is a precursor to entrepreneurial behavior (Krueger et al., 2000; Kolvereid & Isaksen, 2006; Douglas, 2013), an understanding of the entrepreneurial intentions of the elderly should shed light on the determinants of entrepreneurship. Therefore, investigating seniors’ entrepreneurial intentions could help promote entrepreneurship development in specific areas.

Elderly entrepreneurship has become more common. However, many previous studies are focused on entrepreneurship among college students and youth (Luc, 2020; Bui et al., 2020; Chung & Lee, 2020). This study utilized the Theory of Planned Behavior (TPB) proposed by Ajzen (1991) to identify the effect of personal attitude (PA), subjective norms (SN), and perceived behavioral control (PBC) on the entrepreneurial intention (EI) of the elderly, specifically in hospitality and tourism industry. This study conducted an online survey of elderly aged 50–64 in Ma’anshan, a city in Eastern China. Ma’anshan is a tourism destination and has been claimed as entering an aging society stage, and this city is one of the areas with a higher degree of aging. Data of the seventh national census in 2020 shows the population aged 60 and above accounted for 21.73% of the city’s permanent population, of which aged 65 and above accounted for 17.53% (Ma’anshan Municipal Bureau of Statistics, 2021).

The survey conducted by this study was used to test whether TPB helps explain the EI of the elderly in the hospitality and tourism sector in this city. Understanding the entrepreneurial intention of the elderly will help to clarify the determinants of entrepreneurship in the hospitality and tourism industry, thus promoting the entrepreneurial development of the elderly in China. Also, at the time of writing, no other research has been undertaken of China’s elderly exclusively at this level. The research results have the potential for the government, institutions, and academic institutions to provide guidance, assistance, and specialized related projects for the elderly entrepreneurship.

2. Literature Review

2.1. Elderly Entrepreneurship and Entrepreneurial Intention

Entrepreneurship is a process with different phases of discovering, evaluating, and exploiting opportunities to create future goods and services (Baron & Shane, 2007; Shane & Venkataraman, 2000). Some scholars argue that the elderly are less likely to engage in entrepreneurial activity than young people to start a business (Singh & DeNoble, 2003; Kautonen et al., 2011). Lévesque and Minniti (2006), Kautonen et al. (2014) believed the relationship between age and entrepreneurship follows an inverse U-shape for owner-managers. Older individuals avoid investing time in risky activities with no immediate rewards, like starting a business (Kautonen et al., 2011). Some research proves that age harms entrepreneurial intention (Tornikoski et al., 2012; Maâlaoui & Razgallah, 2019) because when individuals get older, they adopt more conservative and less risky behavior that is not associated with personality traits. Ahmad et al. (2014) proved that small businesses run by seniors are more long-lasting and successful because they are undertaken by mature and experienced individuals who benefit from various advantages related to age, like more significant financial resources, personal networks, and experiences (Maâlaoui & Razgallah, 2019; Kurek & Rachwal, 2011; Ahmad et al., 2014).

The senior entrepreneurial process is a complex phenomenon that occurs over time, and it requires adopting different lenses to analyze it (Matos et al., 2018). Consequently, understanding entrepreneurial intention formation is essential (Al-Jubari et al., 2019). Literature shows that intentions play a very relevant role in starting a new firm, and the cognitive approach provides additional insights into the complex process of entrepreneurship (Liñán & Chen, 2009; Baron, 2004). Thus, understanding the elderly’s intentions may directly impact the implementation of their entrepreneurial activities (Gimmon et al., 2019).

The level of attractiveness of entrepreneurial activity among seniors may be influenced by societal perceptions (Lévesque & Minniti, 2011). Besides, entrepreneurial intention among seniors also depends on the individual’s work history (Carr & Sequeira, 2007; Kautonen et al., 2010) and the desire to adopt entrepreneurial behavior (Shane, 2000). Further, opportunity recognition, inspiration, and having assistance from friends also impact senior entrepreneurs’ decision to start a business (Ahmad et al., 2014).

2.2. Theory of Planned Behavior

According to TPB, the intention to start a business derives from evaluating perceived personal capability and perceived social pressure an individual feels to perform the behavior (Ajzen, 2005). TPB allows researchers to focus on entrepreneurial intentions, obstacles, and senior entrepreneurs’ social environment (Matos et al., 2018:520). Thus, it is adopted as a conceptual model in the present study. Furthermore, since TPB has been widely used to predict EI, it would be noteworthy to investigate the EI of a specific population in one particular area within a specific industry. In this way, this study can test the EI of the elderly in the hospitality and tourism sector in an Eastern Chinese city.

PA towards behavior is defined as an individual’s overall evaluation of the outcomes associated with the behavior (Ajzen & Cote, 2008; Liñán & Chen, 2009), it refers to the degree to which individuals believe a given behavior is attractive or not attractive (Jimmieson et al., 2008), and this evaluation is linked to intention (García-Rodríguez et al., 2015). Ajzen (2005) argues that people develop attitudes from their beliefs about the consequences of performing a behavior. In the context of EI, PA relates to the degree to which the individual holds a positive or negative personal valuation about being an entrepreneur (Liñán & Chen, 2009). Furthermore, it is based on perceived consequences of the behavior and whether it will lead to desired positive or negative outcomes (Lee-Ross, 2017; Engle et al., 2010). Therefore, to encourage elderly entrepreneurship, it is vital to adopt positive values regarding entrepreneurial activity and show appreciation for senior entrepreneurs. Doing so would contribute towards the development of positive entrepreneurial attitudes. Thus, it is hypothesized that:

H1: Personal attitude towards entrepreneurship positively affects the elderly’s entrepreneurial intention in the hospitality and tourism sector.

Individuals’ assessments of their ability to accomplish a specific activity are referred to as perceived behavioral control (PBC) (Ajzen, 2005; Ajzen & Cote, 2008). Control beliefs about the availability of circumstances that can permit or hinder the behavior’s performance determine it (Malebana & Swanepoel, 2015). PBC refers to a personal assessment of one’s competence and control in becoming an entrepreneur, as well as perceived feasibility, in the context of EI (Liñán & Chen, 2009; Lee-Ross, 2017). If individuals perceive that their significant others would approve of them engaging in the entrepreneurial behavior; and if the entrepreneurial activity is positively valued in the society, that will enhance their entrepreneurial perceived behavioral control (Dohse & Walter, 2012; Liñán et al., 2013; Uygun & Kasimoglu, 2013), which in turn positively influences EI. Since PBC could be positively related to the intentions of the entrepreneurial behavior (Rueda et al., 2015; Kolvereid & Isaksen, 2006; Krueger et al., 2000), it is hypothesized that:

H2: Perceived behavioral control positively affects the elderly’s entrepreneurial intention in the hospitality and tourism sectors.

Subjective norm (SN) refers to individuals’ perceived social pressure to perform or not perform their intended behavior (Ajzen & Cote, 2008) when they believe that significant social referent people would approve or disapprove of such behavior and are motivated to conform to such referents’ expectations (Ajzen, 1991). In the context of EI, SN assesses the perceived social pressure to carry out or not carry out entrepreneurial behaviors (Liñán & Chen, 2009), as relevant referent persons, such as friends, colleagues, and family members, would approve of the decision to become an entrepreneur or not (Ajzen, 2001; Pruett et al., 2009). The involvement of SN in TPB has not been established either in terms of a putative direct interaction between SN and EI or an indirect relationship between PA and PBC and start-ups (Garca-Rodrguez et al., 2015; Krueger et al., 2000; Liñán & Chen, 2009). In the literature on entrepreneurship, the existence or not of a direct relationship between SN and EI is still a topic of open dispute and curiosity (Schlaegel & Koenig, 2014; Malebana & Swanepoel, 2015). However, if relevant persons are involved in the decision to become an entrepreneur, it is plausible to assume a positive association between this variable and EI (Ajzen, 2001). Therefore, consistent with the above, the following hypothesis is proposed:

H3: Subjective norms positively affect the elderly’s entrepreneurial intention in the hospitality and tourism sector.

Because values imparted by family, friends, and peers lead to more positive perceptions of PA and PBC (Liñán & Chen, 2009), it’s possible that SN has a causal effect on both PA and PBC (Liñán & Santos, 2007). Social norms have been shown to influence PBC and PA perception in previous studies (Liñán & Santos, 2007; LiánLiñán & Chen, 2009; Garca-Rodrguez et al., 2015). As a result, it’s reasonable to believe that SN, PA, and PBC of being an entrepreneur have good correlations. The following hypotheses are thus proposed:

H4: Subjective norms positively affect the elderly’s attitude toward entrepreneurship in the hospitality and tourism sectors.

H5: Subjective norms positively affect the elderly’s perceived behavioral control in the hospitality and tourism sectors.

3. Research Methodology

3.1. Data Collection and Measurement Instrument

The instrument chosen for the study was adopted from previous studies (Liñán & Chen, 2009; Malebana & Swanepoel, 2015; Politis et al., 2016; Chung & Lee, 2020). Applying a structured and validated entrepreneurial intention survey, this research studied the application of TPB in elderly entrepreneurship (Liñán & Chen, 2009). It explored the effects of PA, SN, and PBC on the EI of the elderly. In addition, all the questions emphasized entrepreneurship in the hospitality and tourism sector because of this study’s topic. Questions measuring EI and its antecedents were based on a five-point Likert scale (1 = total disagreement, 5 = total agreement), and this approach was also validated in previous studies on entrepreneurship intention (Malebana & Swanepoe, 2015; Chung & Lee, 2020; Zhao et al., 2005; Liñán & Chen, 2006).

The questionnaire also included demographic infor- mation, namely, gender, educational background, marital status, income level, insurance, prior employment experience, and prior entrepreneurial exposure. These demographic factors and others related to previous experience might not affect the EI directly but could be very useful to identify their effect on PA, SN, and PBC (Liñán & Chen, 2009), and could have some influence on the factors that predict EI (García-Rodríguez et al., 2015). Previous entrepreneurial exposure includes “currently own a business; have tried to start a business before; from the entrepreneurial family background; have friends who run a business and know other people who are entrepreneurs”, with 1 = Yes and 0 = No.

3.2. Population and Sampling Method

There is no agreement in the literature about what age comprises “elderly”. Many scholars define elderly entrepreneurship as starting a new business or being self employed from 50 and above (Bruin & Dupuis, 2003; Ainsworth, 2015; Kautonen et al., 2008, 2011). Kautonen et al. (2010) stated that senior entrepreneurs are the “third age” entrepreneurs aged between 50 and 64. The current legal retirement age in China is 60 for men. Women in management and technical positions retire at the age of 55, whereas women in production, operation, or service positions retire at 50 (State Council of China, 1978a; State Council of China, 1978b). That is, the minimum age for withdrawing from the labor market according to the law is 50. Thus, this study defined 50 as the starting age of the Chinese elderly population and elderly entrepreneurship as discovering, evaluating, and exploiting future goods and services at age 50 and above.

By conducting an online survey using the professional questionnaire platform, the Wenjuanxing questionnaire program, this study evaluated the entrepreneurial intentions of elderly aged 50–64 in Ma’anshan City, Anhui Province, China. Questionnaires were anonymous, using a pragmatic approach, a convenience sample of senior students in Vocal Music classes and Business English classes in two universities for the elderly and senior people in morning Tai Chi training classes. By generating a poster containing the questionnaire QR code, the author shared it on WeChat and invited respondents to fill in the questionnaire. The respondents used their mobile phones to scan the QR code and were directed to the questionnaire’s link to fill in the form and submit it. A pilot study was conducted with eight senior adults to identify any possible questionnaire issues. The pilot study showed that the elderly could use WeChat to scan the QR code and quickly answer questions and that all of the questions were clear. To preserve confidentiality, all questionnaires were completed anonymously. In terms of sample size, Tabachnick and Fidell (2007: 613) recommend having at least 300 instances for factor analysis. After removing invalid answers, 367 questionnaires were found to be valid in this study.

4. Data Analysis and Results

The data was analyzed using SPSS 26 software. Descriptive statistics were used for the frequency analysis of the data collected. The associations between the PA towards becoming an entrepreneur, PBC, SN, and EI were tested using multiple regression analysis. Using linear regression analysis, the association between PA, PBC, and SN was examined.

4.1. Analysis of Demographic Variables of Respondents

The numerical characteristics of demographic variables reflected the distribution of the surveyed objects. Among them, Mean represents the central tendency, and Standard Deviation represents volatility. The main features of the sample are summarized in Table 1.

Table 1: Sample Demographic Characteristics

According to the frequency analysis results of each variable, the distribution met the requirements of the sampling survey. The proportion of men in the survey was 23.4%, and the ratio of women was 76.6%. Very healthy and healthy people accounted for the vast majority, reaching 87.5%, whereas unhealthy and poorly healthy people accounted for 3.7%. 73% of the survey respondents had a high school degree, 14.7% had a university degree or above, and 12.3% had a junior high school degree or below. 68.9% of the survey respondents had a monthly income between RMB 2, 001 (307.83 US Dollars) and RMB 6, 000 (923.01 US Dollars), 23.4% had a monthly income of more than RMB 6, 000, and 6.8% had a monthly income of less than RMB 2, 000 (307.67 US Dollars). The insurance coverage rate was very high, with medical insurance accounting for 97.3% and pension insurance accounting for 98.1%. 19.1% of the respondents had business and service experience. 7.1% of the respondents were currently running their own business in terms of prior entrepreneurial exposure, 22.6% had tried to start a business, 5.7% were from an entrepreneurial family background, 29.7% had business friends, and 46.6% knew other entrepreneurs.

4.2. Reliability and Validity

The initial stage was to determine the scale’s dependability. Cronbach’s reliability test, according to Straub (1989), can be used to examine measurement internal consistency. Cronbach’s alpha coefficient was calculated for the questionnaire and the different constructs in this study. The Alpha values, according to Table 2, varied from 0.859 to 0.972. A Cronbach’s Alpha score of 0.7 or above was regarded as acceptable, while values of 0.8 or higher were preferred (Pallant, 2002: 100). The overall Cronbach Alpha coefficient in this study was 0.974, which was also higher than the 0.7 threshold for all components. As a result of the constructs’ high-reliability scores, the questionnaire questions were reliable.

Table 2: Description and Reliability Analysis of the Entrepreneurial Intention Questionnair

The validity analysis was the next phase. Confirmatory factor analysis was used in this study to assess the validity of research constructs using the Kaiser-Meyer-Olkin (KMO) measure of sample adequacy and Barlett’s test of sphericity, which were the two suggested constructs validity tests (Hair et al., 1998). KMO was 0.954, which was higher than the 0.5 threshold (Hair et al., 1998). In addition, Bartlett’s test of sphericity score for all factors was 0.000, which was much lower than the 0.05 threshold. As a result of both statistics, the data was eligible for factor analysis. See Table 3.

Table 3: Validity Analysis of the Entrepreneurial Intention Questionnaire

4.3. Relationships Among Variables

The Pearson product-moment correlation coefficient was used to evaluate the link between demographic factors, EI antecedents, and EI. Preliminary investigations were carried out to check that the assumptions of normality, linearity, and homoscedasticity were not violated (Pallant, 2002: 135). The value of the correlation coefficient reflected the strength of the association between two variables, with a value of >0.5 indicating a very strong relationship (Pallant, 2002: 134; Cohen, 1988: 79–81).

The Pearson correlations between the independent and dependent variables were over 0.3, which was desirable, according to Table 4. (Pallant, 2002: 158). Both scales (PA, SN, and PBC) were significantly linked with EI (0.756, 0.668, and 0.868, respectively), demonstrating that EI had a significant and positive relationship with PA, SN, and PBC. Each of the three independent variables correlates with less than 0.7 (0.695, 0.686 and 0.650, respectively). As a result, all variables may be kept (Pallant, 2002, p 0.158). EI (r = –0.287, p 0.01), PA (r = –0.274, p < 0.01), SN (r = –0.240, p < 0.01), and PBC (r = –0.270, p < 0.01) all demonstrated a significant and negative connection with gender. Marital status, monthly income level, previous work experience, and medical insurance were among the demographic characteristics that had no significant link with EI. However, there was a significant association (r = –0.143, p 0.01) between pension insurance and EI. However, there was a significant association (r = –0.143, p < 0.01) between pension insurance and EI. The findings also revealed that if a person comes from an entrepreneurial family, has friends who operate businesses and knows other entrepreneurs, their chances of becoming someone who now runs a business or has attempted to start one improve. These factors had significant and positive correlations, with correlation values ranging from 0.217 to 0.576, p < 0.01. It confirms the impact of role models in adopting an entrepreneurial profession, which is in line with a previous study (Malebana & Swanepoel, 2015).

Table 4: Correlations Among Variables

Note: ** Correlation is significant at the 0.01 level (2–tailed). *Correlation is significant at the 0.05 level (2-tailed). 1: EI; 2: Gender; 3: Marital Statuses; 4: Health; 5: Education; 6: Monthly Income; 7: Primary Work Experience; 8: Medical Insurance; 9: Pension Insurance; 10: Currently Own a Business; 11: Tried to Start a Business Before; 12: Entrepreneurial Family Background; 13: Friends Run Businesses; 14: Know Other Entrepreneurs; 15: PA; 16: SN; 17: PBC.

Multicollinearity and violation of the assumption of error independence were investigated in the data. The findings of the collinearity diagnostics were displayed in the table Coefficients, which could be used to assess multicollinearity. Two values were given: Tolerance and VIF. The Tolerance values for all the independent variables were 0.422, 0.460, and 0.471, they were all greater than 0.100, suggesting that the multicollinearity condition had not been broken. T All the independent variables’ VIFs (variance inflation factors) were 2.372, 2.175, and 2.121, respectively. As a result, they were all much below the cutoff value of 10, showing that multicollinearity was not an issue (Pallant, 2002: 158). See Table 5.

Table 5: Coefficients

The relationship between one continuous dependent variable and several independent variables or predictors could be investigated using multiple regression (Pallant, 2002: 148). The validity of Ajzen’s (1991) TPB in predicting EI was investigated in this study, which examined whether the theory could be applied to the specific field of forecasting the EI of Chinese elderly workers in the hotel and tourism industry. EI and its antecedents were included in a multiple regression model, with EI as the dependent variable and PA, SN, and PBC as the independent variables.

The model was statistically significant (F (3.363) = 498.193, p < 0.01), and Durbin Watson = 1.980, according to the Multiple regression scores. Furthermore, the modified R Square revealed how much of the variance in the dependent variable (EI) the model explained (which includes the variables of PA, SN, and PBC). The number, in this case, was 0.803, indicating that the linear combination of the three predictor variables explained 80.3% of the variance in EI.

The most significant beta coefficient in this study was 0.641, which was for PBC. When the variation explained by all other variables in the model was adjusted for, this variable made the most significant unique contribution to explaining the dependent variable (Pallant, 2002: 161). EI would increase by 0.685 times if PBC increases by one unit. PA had a somewhat lower Beta value (0.275), indicating that it provided a less unique contribution. Nonetheless, both PA and PBC contributed to the prediction of EI in a statistically significant way (p > 0.05). As a result, both the first and second hypotheses were confirmed. The findings reveal that EI arose from people’s attitudes toward becoming entrepreneurs or starting businesses. Individuals also acquired preferences for starting a business depending on their self-efficacy, or capacity to undertake an entrepreneurial activity. SN was the least effective predictor of EI, contributing nothing to the model (p > 0.05). There was no correlation between SN and EI. As a result, the third hypothesis was disproved.

The model also revealed significant associations between SN and PA (=0.695, p < 0.05) and SN and PBC (=0.650, p < 0.05) using the sample data. As a result, the fourth and fifth hypotheses were shown to be true. It was in line with the findings of previous research (Liñán & Chen, 2009; García-Rodríguez et al., 2015). SN influenced PA’s decision to become an entrepreneur in the hospitality and tourism industry, as well as PBC, which explained EI (Liñán & Chen, 2009). In summary, the research data supported Hypothesis 1 and Hypothesis 2, but not Hypothesis 3. However, this study also confirmed that social norms positively impacted personal attitude and perceived behavior control of becoming an entrepreneur in the hospitality and tourism industry, which explained entrepreneurial intention. Therefore, the data supported Hypothesis 4 and Hypothesis 5. See Table 6.

Table 6: Hypothesis Test Results

Note: *p-value < 0.1; **p-value < 0.05; ***p-value < 0.001. Significant at the 0.05 level.

5. Discussion

This research examined the elderly’s entrepreneurial intentions in the hotel and tourism sector in Ma’anshan City, Eastern China. It used the entrepreneurial intention questionnaire (EIQ) to assess the EI of the elderly in the hospitality and tourism business in Ma’anshan City. The findings corroborated previous research, the instrument’s dimensionality was found to be trustworthy and satisfactory, and TPB was shown to be a useful model for understanding the entrepreneurial intentions of the elderly in Ma’anshan City’s hospitality and tourism sector.

The effect of three independent variables, PA, SN, and PBC, on EI, was also investigated, as well as whether SN had a positive effect on PA and PBC. According to the findings, the complete EI model accounted for 80.3 percent of the variance in entrepreneurial intention. The 18.7% disparity could not be explained or was caused by other factors not taken into account by TPB. Some demographic or external characteristics, on the other hand, were found to be significantly linked with these antecedents (Liñán & Chen, 2006, 2009). It revealed out that motivation antecedents explained intention, whereas all other variables had indirect effects, which was consistent with the TPB (Ajzen, 1991, 2001, 2002).

The findings showed that entrepreneurial intent was influenced by an individual’s attitude toward starting a firm as well as his or her self-efficacy, or capacity to execute entrepreneurial behavior (Lee-Ross, 2017). The impact of social norms on entrepreneurial intent was not significant. It is possible that persons in their 50s and 60s with a lot of social life experience were less affected by their families’ and peers’ perceptions. Their attitude towards entrepreneurship and their perception of the difficulty of entrepreneurship had a more significant impact on their entrepreneurial intention (Chung & Lee, 2020).

Another point to note is the contrast between this study and prior studies on college students or graduate students (Al-Jubari et al., 2019; Lee-Ross, 2017; Bui et al., 2020; Akhter et al., 2020; Garca-Rodrguez et al., 2015). The elderly who had retired or were about to retire provided the data for this study. In past studies, college students were frequently used as a research population, and the studies benefited from a sample of similar age and qualifications, resulting in a more homogeneous sample (Liñán & Chen, 2006). TPB’s relevance to entrepreneurship has received a lot of empirical support. The present study uses the elderly as a sample and comes to the same conclusions as to the younger generation.

6. Implications and Conclusion

This study contributes to academic research on elderly entrepreneurship in the hotel and tourism sector, as well as senior human resource development in China. The findings of this research add to the use of TPB in elderly entrepreneurship in the hotel and tourism industries. This research focuses on elderly entrepreneurship as a means of addressing the challenges raised by the aging society’s development. The findings validate the majority of the hypotheses, demonstrating that personal attitude and behavioral control are antecedents of senior people’s entrepreneurial intentions in the hospitality and tourism industries. Furthermore, while the findings do not reveal a relationship between subjective norms and entrepreneurial purpose, they do show that social norms have a significant positive impact on personal attitudes toward entrepreneurial action and perceived behavioral control.

According to the conclusions of this study, policymakers should give the required support for senior entrepreneurs who want to start enterprises in the hospitality and tourism industries, as well as enhance the elderly’s human resources through entrepreneurship, resulting in more job opportunities. Entrepreneurship among the elderly plays an important role in the economy, particularly in the hotel and tourism industries, where the feasibility is strong and becoming an entrepreneur is a positive decision. The more the emphasis on elderly entrepreneurship and the higher the value of becoming an entrepreneur as a career choice for the elderly, the higher the number of potential elderly entrepreneurs. Elderly entrepreneurship in hospitality and tourism is critical for seniors to engage fully in society in this age of longevity. China’s ability to successfully respond to the effects of an aging population while maintaining long term economic and social development is critical.

*Acknowledgements:

This study is supported by grants from Ma’anshan Teacher’s College, China. Grant No: 2021xjzdky05.