“Factors increasing entrepreneurs’ loss concerns and role of startup accelerators in loss protection”

The aim of this study is to analyze the factors that increase loss concerns among entre-preneurs and the underlying mechanism for loss protection. An e-mail-based survey among 335 entrepreneurs from India is employed in this paper. Using a quantitative methodology and PLS-SEM approach, the study analyzed the relationship between loss concerns and loss protection behavior and the mediating role of startup accelerator programs. Thus, human capital increases loss concerns. Participating in the startup accelerator program is the underlying mechanism to carry out protection behavior when entrepreneurs deem their venture at risk of losing money. The theoretical model explicates 70% of variances in loss concerns and 42% of variances in protection behavior. Every one-unit increase in human capital and uncertainty increases the loss concern by 28% and 10%, respectively. Participating in the startup accelerator program increases the loss protection behavior of entrepreneurs by 36%. Perceived severity increases loss protection behavior by 17%. The present study extends the protection motivation theory in the entrepreneurship literature and provides evidence that startup accelerators influence entrepreneurs in increasing loss protection mechanisms in an emerging economy.


INTRODUCTION
Survival of startups is critical as the investment involved is high.The survival rate of US startups (Carrigan, 2020) and Indian startups (Cherian, 2018) are 10%, while venture capital investments exceeded 300 billion USD (Teare, 2021).If these investments have to be good, startups' failure should be reduced.It is crucial to investigate the loss-preventing mechanisms so the survival rate of startups can be increased through the learning process (Startup Genome, 2017).Threats of markets, customers, competitors, and technologies trigger perceived severity among entrepreneurs.Entrepreneurial efficacyincludes being able to meet sales goals, make uncertain decisions, and strategically plan for the future.
Protection motivation theory (PMT) suggests that individuals protect themselves based on the perceived severity of a threatening event and cope with the threat using their self-efficacy (Rogers, 1975).This protective behavior is gained through various educational, experience, and network support gained by entrepreneurs.Entrepreneurs may accumulate experience and skills by attending incubation programs (Hackett & Dilts, 2004) or short-cohort-based accelerator programs (Hochberg, 2016).The present study aims to analyze the factors that increase loss concerns among entrepreneurs and the underlying mechanism for loss protection.The studies conducted on startup accelerators brought out many benefits.This present study's motivation in analyzing entrepreneurs' loss protection behavior arose from the influence of startup accelerators in increasing funding and network support, thus elucidating gaps identified by past accelerator studies (Shetty et al., 2020;Crison et al., 2021).

LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT
In developed countries like the western world, failure is considered a learning opportunity, while in developing countries, failure is a death sentence (Cotteril, 2012).Failure in developing countries can have severe personal consequences increasing fear of failure, leading to significant debts and loss of social status and reputation of entrepreneurs (Ucbasaran et al., 2013).As developing countries have low economic freedom (Khyareh & Mazhari, 2016), the impact of fear will be more significant.
In developed countries with high entrepreneurial opportunities, even entrepreneurs with loss aversion (Barberis & Huang, 2001) can make decisions amidst uncertainty.The number of startup activities depends on how well the country's economic policies are formulated and how many institutions are established (Sobel, 2015).Entrepreneurs will implement the corresponding protection behavior when concerns about financial losses increase.In the case of preventing health problems, various health concerns make an individual implement healthy behaviors.In the case of environmental protection, the threat to the environment makes people implement planet-friendly steps.Finally, in the case of financial loss, the threat posed by uncertainty, market, and new competition makes entrepreneurs implement loss protection behavior.
PMT has been widely applied in privacy literature to explain how users protect their information to maintain their privacy (Tsai et al., 2016;Verkijika, 2018).In privacy literature, PMT suggests that the threat of information attacks raises the awareness of users' need for privacy control.The coping mechanisms enable the users to manage the threats so privacy will not be lost.In the entrepreneurship literature, PMT suggests that the threat (perceived severity of market, customers, or technologies) raises awareness.Coping (entrepreneurial efficacy) factor equips entrepreneurs with the necessary tackling mechanism to manage the threats.Even though entrepreneurs constantly face threats, the appropriate protection mechanism is implemented to control financial losses as and when danger is sensed.This is the premise of this study.
Uncertainty is entrepreneurs' incompetency in predicting accuracy (Milliken, 1987).Entrepreneurs do not attempt to predict what will happen in the face of uncertainty but rather control the unpredictable future through their actions and options (Sarasvathy, 2001).The structured actions and strategic options should fit with the environment (Miller, 1988).Uncertainty creates hesitancy, indecisiveness, and procrastination, making entrepreneurs miss opportunities as they are unaware of how to appraise different outcomes (O' Brien et al., 2003).This leads to two scenarios: failing to act when action is required and acting when inaction is required (Shepherd, 2003) (Davidsson & Honig, 2003).Providing financial support alone is not enough, as it will not fully impact the growth potential of a startup without a well-connected network to increase critical corporate clients.
Startups can be injected with cash, but it will not help them identify the right market or gain market recognition (Sutton, 2012).In this case, connecting the startups with the corporations' upper management by the accelerators' staff using their personal relationships could improve the outlook of the startup more than seed capital would.
Frequent observations of customers' preferences and constant learning from customers help start-ups deal with the fast-changing market and consumer behavior.Startup capabilities gained from entrepreneurial and managerial capital are essential ingredients for the growth process (Garnsey et al., 2006), as entrepreneurial capital leads to startups' success.Skills are imparted through advice and mentoring sessions (Bruneel et al., 2012) in a typical accelerator program, which increases the startups' contacts, and thus, the visibility of startups (Roberts et al., 2017).Accelerators enhance the startups' growth process and validation (Chevalier et al., 2004) by delivering lectures relevant to entrepreneurs' problems, increasing the knowledge base (Davidsson & Honig, 2003).Participation in the accelerator program increases revenue by 130% in the first three months (González-Uribe & Reyes, 2021).Thus, accelerator programs pave the way for entrepreneurs when their concerns about losses increase by equipping them with financial protective mechanisms.
Perceived severity is the identification of risks and prioritizing the topmost needs of the firms to minimize resource wastage so firms can extract maximum out of the opportunities (Hubbard, 2009) Similarly, customer instability reduces value co-creation and causes loss in sales (Gomez et al., 2004).Perceived severity makes entrepreneurs aware of these pitfalls, increases awareness of market-oriented challenges, and eventually cautions entrepreneurs to avoid losses (Kollmann et al., 2017).Entrepreneurs can achieve their goals despite their perceived severity, protect themselves, and even enjoy excess returns (Cochrane, 2005) by engaging in export-oriented activity when the domestic market is hostile (Zahra et al., 1997) and by employing alternate safe options.Loss from any one source can be cushioned by expanding economic activity.Perceived severity makes entrepreneurs recognize shifts in markets, customers, and technologies quickly.
Human capital, accumulated talent, knowledge gained through education, work experience, and prior experience founding a startup (Lucas, 1988) contribute to a startup's growth.The human capital theory postulates that productivity increases with higher human capital (Becker, 1964).High human capital attracts investors, thereby funding (Shetty & Sundaram, 2019), which is very important for startup growth.Growth demands increase coordination requirements associated with a changing business environment.The feeling of loss of control by the founders and reduced flexibility in startups challenge the decision-makers in the growth phase (Garnsey et al., 2006).Firm growth rates are random and unpredictable, which may increase the risk of failure (Coad, 2009).The management procedures required to foresee shortages need to be improved among startups, which often catches them unrehearsed (Garnsey, 1998).
Growth at the right time is essential; if it happens late, entrepreneurs risk environmental changes.However, the growth phase is fraught with serious setbacks that result from external change and anachronism, reduced flexibility, and feeling of loss of control (Garnsey et al., 2006), which increases tension among founders.Generally, a startup faces the same risk as a game of poker or a betting game (March & Shapira, 1987).
This study aims to analyze the factors that increase loss concerns among entrepreneurs and the underlying mechanism for loss protection.With the aim of testing the impact of these factors on loss protection behavior and based on the literature review, the following hypotheses are proposed (Fig ure 1): H1: Uncertainty increases loss concerns.
H2: Participating in an accelerator program mediates the relationship between loss concern and protection from losses.
H3: Perceived severity increases the protection behavior of entrepreneurs in protecting from losses and failures.

Samples and data collection
Quantitative analysis is the most common method for survey-based research and gives accurate results (Queirós et al., 2017).Online questionnaire for surveys offers many advantages (Taherdoost, 2016).A structured questionnaire was sent to entrepreneurs belonging to all corners of India.These entrepreneurs' email addresses were registered with a Technology Business Incubator supported by the Government of India.A total of eight hundred and fourteen entrepreneurs were contacted, and 335 responded to the online questionnaires representing the sample population.

Analysis
Empirical data were analyzed using Partial Least Square (PLS) analysis.Structural equation modeling (SEM) was used to assess structural and measurement models.Constructs validity and reliability were checked using various tests.Convergent and discriminant validity was checked using confirmatory factor analysis (Hair et al., 2016).Since PLS was used with SEM in a two-step analysis, the measurement model, followed by SEM, was analyzed.
The convergent validity test result is shown in In discriminant validity tests (Bagozzi et al., 1991), the distance between the constructs is measured; in other words, constructs should not be related or correlated to each other.As a result, AVE values surpass the threshold value of 0.5.Table 3 shows that each construct's discriminant validity condition is satisfied (Fornell & Larcker, 1981).
The condition to satisfy discriminant validity is that the values of correlation items in any construct should be less than the AVE (Hair et al., 2010).Discriminant validity testing is supported as per Table 3. Construct loadings are listed in Appendix A, Table A2.

RESULTS
PLS-SEM analysis was performed to assess the proposed model.The path measurement model reveals that the R2 value for loss concern is 0.70, and protection behavior R2 is 0.42.The model shows that loss concerns variance is explained by 70%.Thus, the variables predict the model well.Protection behavior variance is explained by 42% of the variables.Figures A1 and A2 show the model values.The factor loadings are above the recommended threshold value of 0.5, ranging from 0.853 to 0.990 (Table A2).A collinearity test was performed to test if the method was biased.Variance inflation factor values are less than 0.3; hence, the model is considered free of method bias.Figure 2 shows the result of the structural model.

Assessment of model fit
Pretests are conducted to avoid measurement and sampling errors (Kumar, 2015).Model fit was tested using SRMR and NFI fit measures.The SRMR fit measure is the Standardized Root Mean Square Residuals (SRMR), and the NFI fit measure is the Normed Fit Index (NFI) method.The former is the index of the average of standardized residuals between hypothesized and observed correlations.The latter compares the Chi-Square value with a benchmark value.This study reported the SRMR value as 0.098 and the saturated model as 0.092.

Testing the hypotheses and the mediating effect
The result shows that uncertainty is positively and significantly related to loss concerns, with path coefficient = 0.103, t = 1.913, and p = 0.03, indicating that H1 is supported.Furthermore, the mediation effect from the accelerator between loss concerns and protection behavior is supported with the path co-efficient = 0.361, t = 2.144, and p < 0.001, indicating that H2 is supported.
The mediating effect of loss concern on protection behavior is transmitted through the accelerator.
Since the direct relation between loss concern and protection behavior is positive and significant after introducing the accelerator as mediating variable, partial mediation relation is supported.
H3, suggesting the relationship between perceived severity and protection behavior, is supported by the path coefficient = 0.173, t = 3.254, and p < 0.001.Human capital increases loss concerns, supporting H4 with the path coefficient = 0.284, t = 5.421, and p < 0.001.There are substantial variances between groups supporting all the proposed hypotheses.

DISCUSSION
Many factors increase the loss concerns of entrepreneurs.Contextualizing PMT with the loss concerns and protection behavior to prevent losses (Gaskill et al., 1993), this study analyzed the impact of human capital, uncertainty in an entrepreneurial environment, perceived severity, and self-efficacy on loss concerns and protection behavior.All hypotheses in this study are supported.
An interesting finding in this study is that human capital does not influence protection behavior though it increases loss concerns.This contradicts the previous findings that showed human capital leading to the survival of startups (Gimmon & Levie, 2010;Huggins et al., 2017).Of the three necessary human capital variables (industry experience, education, and prior startup experience), industry experience increased survival (Delmar & Shane, 2006).The study did not differentiate education and experience.The source of funding also plays a role in survival.Keogh and Johnson (2021) reported that industry experience contributed to survival and success when the funding was from angel investing but worked against survival when funding was from a venture capitalist.
The finding of H1, uncertainty increases loss concerns, matches with prior studies focusing on making decisions in an ill-structured environment.
Reasoned action in an ill-structured environment (Packard et al., 2017), financing in uncertain circumstances (de Bettignies & Brander, 2007), innovation quality (Dougherty & Heller, 1994), and time to enter the market (Lévesque & Shepherd, 2004) increase loss concerns.There is a positive relationship between uncertainty and protection behavior because the well-planned financial structure focuses on high profit (Stone, 2003) and prevents loss.
There are many mechanisms to avoid losses.This study showed accelerator participation as an underlying mechanism for preventing losses.Past studies showed that entrepreneurs participating in accelerator programs are from an elite set of universities, receive their first round of funding sooner, and are likely to be acquired sooner (Winston-Smith & Hannigan, 2013).In addition, accelerators typically run a short-duration cohort-based program that increases startup survival (Chatterji et al., 2019).H2 showed that one of the reasons for this survival could be the various loss protection strategies learned by entrepreneurs from attending accelerator programs.
The finding on H3, the positive relationship between perceived severity and protection behavior, matches with a recent study conducted on organizations' protection behavior (Sundaram & Shetty, 2022) and online protection behavior (Boerman et

CONCLUSION
This study aimed to analyze the factors that increase loss concerns among entrepreneurs and the underlying mechanism for loss protection.Findings suggest accelerators mediate between financial loss concerns and loss protection behavior.Uncertainty and human capital increase the financial loss concerns.Perceived severity increases loss protection behavior.The structured cohort-based accelerator programs are effective in imparting financial loss sensing abilities and the corresponding loss protection behavior.The reason accelerators are impactful is that the awareness of entrepreneurs increases multifold through the connections they make with knowledgeable and influential individuals that accelerator programs introduce them to in addition to the intense knowledge lectures.Human capital accumulated through education and experience increases the financial loss concerns because entrepreneurs are already aware of the pitfalls in the nascent stage of startups.However, this awareness alone is insufficient to convert into loss-protective measures to prevent losses.
The theoretical implication of this study is that the protection motivation theory applied in the entrepreneurship context is very scarce.This study addresses this lacuna by selecting the relevant factors and their impact on protection from losses.A practical implication is that accelerators shall have specific courses on increasing entrepreneurs' forecast ability, which will make entrepreneurs manage their resources effectively while constantly looking for ways to increase sales.The curriculum followed in the accelerators can be deployed in the startup incubators and other entrepreneur mentors.Human capital and self-efficacy are essential indicators in predicting losses.Entrepreneurs may choose founders having high human capital and self-efficacy.Founder teams may be formed with the skill sets such as the ability to meet sales goals, innovate new products and services, make decisions under uncertainty, and perform financial analysis to conquer financial losses effectively.

Table 1
shows the demographic profile of participants in this study.Male participants occupy 65.6%, and female participants are 34%.The majority of the participants are from the 26 to 35 age group.Most participants have Bachelor's degree, followed by a Master's and then a doctorate degree.

Table 1 . Sample characteristics Characteristics Sample Frequency % of population
three scale items were removed; hence, the final scale has five items.The adversarial sentence was added for the attention check, and thirteen samples that failed the attention check were removed.

Table 2
Fornell and Larcker (1981)se the items are within a construct.Cronbach's alpha value greater than .7 shows good reliability.As shown in Table2, Cronbach's values are above .7,rangingfrom.86 to .92.Fornell and Larcker (1981)suggested a threshold for average variance extracted of .50.This analysis reported values ranging from .642 to .766.