business recovery research paper

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Dispositional optimism and business recovery during a pandemic

Contributed equally to this work with: Mario Amore, Orsola Garofalo, Victor Martin-Sanchez

Roles Conceptualization, Data curation, Formal analysis, Methodology, Resources, Software, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliations Department of Management and Technology, Bocconi University, Milan, Italy, Centre for Economic Policy Research (CEPR), London, United Kingdom

Roles Data curation, Formal analysis, Methodology, Resources, Software, Visualization, Writing – original draft

Affiliations Centre for Economic Policy Research (CEPR), London, United Kingdom, Department of Strategy and Innovation, Copenhagen Business School, Frederiksberg, Denmark

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Writing – original draft

Affiliation Department of Business and Management, University of Southern Denmark, Odense, Denmark

• Mario Amore, 
• Orsola Garofalo, 
• Victor Martin-Sanchez

• Published: June 9, 2022
• https://doi.org/10.1371/journal.pone.0269707
• Reader Comments

A large literature at the crossroads of biology and cognitive psychology has shown that individuals hold generally positive expectations about future events. Despite this evidence, to date it remains unclear whether optimism has positive or negative implications for entrepreneurial activities. We examine this question in the context of the Covid-19 pandemic, which provides a unique way to study the role of optimism on the (in)ability of firms to overcome exogenous shocks. Using a large-scale longitudinal survey covering 1,632 UK firms, we find that entrepreneurs who score high on optimism were more likely to innovate and make organizational changes to their firms during the Covid-19 outbreak. Moreover, optimistic entrepreneurs experienced higher revenue growth during the pandemic. Collectively, our study sheds light on one of the psychological factors explaining why some firms can prosper and some others struggle in the wake of an external shock.

Citation: Amore M, Garofalo O, Martin-Sanchez V (2022) Dispositional optimism and business recovery during a pandemic. PLoS ONE 17(6): e0269707. https://doi.org/10.1371/journal.pone.0269707

Editor: Rogis Baker, Universiti Pertahanan Nasional Malaysia, MALAYSIA

Received: April 20, 2022; Accepted: May 25, 2022; Published: June 9, 2022

Copyright: © 2022 Amore et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data are fully available in the fig share repository and can be downloaded at this link: https://doi.org/10.6084/m9.figshare.19779859.v1 .

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Several existing studies indicate that humans are generally optimistic, i.e., they display a tendency to expect positive events in the future even when the available evidence does not support such expectation [ 1 – 3 ]. Dispositional optimism has been shown to play a key role in a wide range of human activities related to work, social relations, and health [ 4 ]. Within this literature, several studies have further documented a positive association between optimism and individual health [ 5 ]: optimistic individuals tend to experience a lower mortality risk [ 6 ] as a result of their higher propensity to take proactive steps to protect health [ 5 ] and their better emotional response to adversities, which in turn reduces the physiological strain over time [ 4 ]. In particular, optimism has been shown to be negatively associated with the risk of stroke [ 7 ], rehospitalization following coronary artery bypass surgery [ 8 ], and chronic diseases of aging and premature mortality [ 9 ]. The meta-analysis in [ 10 ] confirms that optimism is a significant predictor of positive health outcomes.

An important, yet unaddressed, question concerns whether optimism can matter not only for individual survival but also for the survival of entrepreneurial firms in the wake of negative events. This question is relevant considering the notoriously high mortality rate of new ventures, which has triggered an important debate about why some firms are better equipped than others to survive [ 11 , 12 ].

Psychology plays a key role in entrepreneurial decision-making. Several works in this realm have shown that entrepreneurs tend to display a particularly high level of optimism, which translates into a higher confidence in their ability to succeed [ 13 ]. However, as for any personal trait, optimism varies across individuals due to genetic and environmental factors [ 4 ]. Focusing on dispositional optimism is important because it may underlie variations in entrepreneurial actions, which in turn map into business outcomes [ 13 – 15 ]. The mechanism linking optimism and business outcomes is that entrepreneurs act on their confidence and personal beliefs when deciding upon the allocation and use of resources [ 16 , 17 ]. Despite a consensus on the view that optimism influences entrepreneurs’ decision-making, it remains unclear whether this influence is positive or negative for entrepreneurial firms. We examine this question by focusing on the Covid-19 pandemic, which created many unprecedented business challenges ranging from value-chain disruptions and organizational setbacks due to employee illness to problems in managing customer relationships in ways consistent with lockdown policies. While these challenges threatened the survival of many entrepreneurial firms [ 18 ], they also brought about opportunities emerging from changes in households’ daily routines and new customer needs. Coping with these challenges and turning them into opportunities requires entrepreneurs to pivot their current ways of doing business along many dimensions spanning from product innovation to organizational and supply-chain adjustments. Indeed, innovation is one of the key strategic responses that firms may enact amidst a crisis [ 19 , 20 ].

On the one hand, optimism may have raised the ability of entrepreneurs to imagine pathways to overcome pandemic-related challenges and behave more proactively. This view stems from the idea that optimism is positively associated with a successful adaptation to stressful events [ 21 , 22 ] and with the ability to undertake organizational changes [ 23 ]. On the other hand, optimism may have created an illusory sense of control, exposing entrepreneurs to heuristics and biases, and leading them to errors in judgment [ 24 ]. These features may be especially problematic in times of crisis, which make resources more scarcely available and the cost of mistakes potentially larger. Did dispositional optimism improve or worsen the entrepreneurial response to the pandemic shock?

To answer this question, we employ a large multi-wave survey covering entrepreneurs based in the United Kingdom (UK). We start by showing a large negative impact of Covid-19 on our sample firms: one third of them were completely closed during the spring lockdown, and 72% of them reported a revenue drop (which amounts to 37%, on average). Yet, several entrepreneurs took actions to cope with Covid-19: around 30% of them tried to innovate their products or processes, whereas 25% of them changed their organizational structure. The key finding of our study is that dispositional optimism explains large variations in the likelihood of such entrepreneurial actions during the pandemic: optimistic entrepreneurs were more proactive in making organizational changes and innovate during the Covid-19 outbreak. In parallel, optimistic entrepreneurs have more positive beliefs regarding the time needed for their business to fully recover from the crisis, and a higher likelihood to experience a revenue increase in the future (even controlling for the size of revenue drop). Finally, optimistic entrepreneurs hold more positive expectations about macroeconomic conditions. Those actions and beliefs translate into superior business outcomes: our data reveal a positive association between dispositional optimism and growth during the pandemic period.

Collectively, our results suggest that dispositional optimism is significantly associated with effective entrepreneurial actions in the wake of the Covid-19 pandemic. Our work contributes to research on the implications of Covid-19 for entrepreneurship and management [ 18 , 25 ] and, more generally, on the drivers of business resilience during hard times [ 26 – 29 ]. It also complements existing works on how individual beliefs [ 30 ] and economic expectations [ 31 , 32 ] evolved during the pandemic. Finally, we expand the large literature on how optimism affects business outcomes by leveraging on a new context such as the Covid-19 pandemic, which prompted many entrepreneurs to engage in business actions functional to overcome the pandemic period. While, as said, the association between optimism and performance is still debated in the literature, our results point to a beneficial role of optimistic tendencies during a time of crisis.

Materials and methods

Covid-19 has proven to be one of the most dreadful viruses of the recent human history. In the UK, the virus experienced a rapid diffusion starting from late February (i.e. when the first case was identified): the daily number of infections reached its maximum on April 9 th (with 5,450 cases), whereas the daily number of deaths peaked on April 22 nd (with 1,224 deaths). Data are drawn from: https://covid19.who.int/region/euro/country/gb . The surge of Covid-19 in the UK led to a four-month lockdown (from March to June 2020), which constrained the activities of 5.8 million among entrepreneurs, small and medium-sized enterprises and self-employed [ 33 ]. Importantly, contrary to the second outbreak that affected many countries in the fall of 2020, the spring outbreak was unprecedented and entirely unexpected. Thus, it provides a useful context to analyze the readiness of entrepreneurial actions to the pandemic.

Survey design

All participants in this study gave informed consent, and ethical approval was provided in written form and before data collection started by the Research Ethics Office of King’s College London, the institution where Victor Martin-Sanchez was based at the time of starting this project.

Survey methods have been widely used to understand the impact of Covid-19 on the entrepreneurship landscape; e.g. [ 34 ]. We sent our first survey through Prolific Academic at the beginning of June 2020, during which the Covid-19 shock has, at least in part, already been incorporated into revenues, and entrepreneurs had time to implement business actions to face the pandemic. The survey was sent to 2,000 entrepreneurs whose business was based in the UK. To encourage participation in the survey, we provided a participation fee of 5£ per hour, as well as three lottery prizes of 300£, 150£ and 150£. Additionally, there was a set of incentivized questions where participants could get an extra 0.30£ by: (1) providing the range-estimate of the number of Covid-19 contagion cases in the UK at end of July; (2) providing the position of the UK in the ranking of the countries with most contagion cases; and (3) being randomly selected in one of the Holt-Laury questions (explained later). The survey contains a total of 30 questions regarding entrepreneurs’ demographic and business characteristics (before and during the spread of Covid-19), as well as questions regarding the specific actions taken during the pandemic period, and expectations about the future diffusion of Covid-19. We received 1,632 usable responses, which amount to an 82% response rate. The final sample satisfies the following criteria: (1) the respondents are currently business owners; and (2) they reside in the UK.

Dispositional optimism, i.e. the key explanatory variable in our study, can be thought as a general expectation that more good things, rather than bad, will happen in the future [ 3 , 35 ]. To measure the extent to which individuals expect that good (resp. bad) things will be plentiful, we use the revised Life Orientation Test (LOT-R), developed in [ 35 ] and widely employed in business research [ 14 , 15 , 36 , 37 ]. The LOT-R has ten items: three (questions 1, 4, and 10) measure optimism, another three (questions 3, 7, and 9) measure pessimism, and four items (questions 2, 5, 6, and 8) serve as “fillers”. Respondents rate each item on a 5-point scale: “Strongly disagree” (0 points), “Disagree” (1 point), “Neutral” (2 points), “Agree” (3 points), or “Strongly agree” (4 points). The final measure of dispositional optimism is computed by summing the scores of questions related to optimism and pessimism, where the latter are reverse-coded. It ranges from 0 to 24, and higher values indicate a higher level of optimism.

Next, we follow [ 38 ] to assess individuals’ risk preferences (which can matter too in responding to the pandemic and hence confound the effect of optimism). In the Holt and Laury’s framework, every player is given a list of ten rows of paired gambles and for each gamble he/she must indicate a preference by choosing either Option A or Option B. The payoffs of gambles in the two options are constant but they differ in the probability of each payoff: for the first pair of gambles there is a 10% chance of receiving the high payoff for either option, while for the last pair of gambles there is a 100% probability of receiving the high payoff. What usually occurs is that Option A is chosen for the first decision and then, at some point before the last decision row, the respondent switches to Option B. The switching point measures individual risk preferences: the higher the point, the greater the individual’s risk aversion.

To shed light on the effectiveness of entrepreneurial actions implemented during the spring of 2020, we conducted another survey in May 2021 in which we asked the same entrepreneurs questions about their firms’ revenues and employees, together with a few other questions (including optimism, described above). Of the 1,632 respondents to the survey sent in June 2020, we were able to get usable responses from 996 entrepreneurs.

Sample characteristics.

Table 1 shows the summary statistics for the main individual and business-related variables (taken from the first survey wave). As shown, the entrepreneurs in our sample are on average 40 years old, 64% of them are women, and 19% hold an advanced degree (Master or PhD). The average level of optimism is equal to 14, which is at par with the value found in Scheier et al. (1994). Examining business characteristics, we find that the average firm is 7 years old and has 1.8 full-time employees as of December 2019. The subsequent rows show that Covid-19 caused a significant economic downturn: one third of entrepreneurs reported that their business was entirely closed during the spring lockdown, and 72% of them reported a drop in revenues. The average change in revenues in January-April 2020 relative to the same period in 2019 was -37%. While we will use revenue change in the analysis, our data also contain information on employees. The average change in the number of total employees was -9%.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0269707.t001

Focusing on the actions undertaken to face the Covid-19 pandemic, Fig 1 shows that almost one fourth of the entrepreneurs in our sample made organizational changes to their business, whereas one third of them in introduced some form of product or process innovation.

Note: The figure indicates the fraction of businesses which report to have introduced product or process innovation, and organizational changes during January-April 2020.

https://doi.org/10.1371/journal.pone.0269707.g001

Our survey contains two questions where we asked entrepreneurs to provide a textual description of innovation and organizational adjustments. Parsing this information, we found that the three most frequently cited types of innovation are in the area of digital systems (66%), product or process expansion (13%), and delivery systems (8%). The three most frequently cited types of organizational change are about workplace adjustments, e.g. flexible work schedule, remote-working etc. (33%), job retention schemes (20%), and business model adjustments (12%). Our survey also contains a question regarding whether the entrepreneurs have applied to any governmental support scheme; 35% of them have done so (with no systematic differences by the level of dispositional optimism).

Our measure of optimism used so far is based on individual beliefs during the uptake of the virus. This raises the question of whether there was a reverse-causality mechanism whereby better business outcomes may have made entrepreneurs more optimistic. In addressing this point, it is useful to keep in mind that optimism is a highly stable trait [ 5 ], which features small within-subject variations even in the wake of drastic life events [ 39 ]. As anticipated, our second survey contains a set of questions which—for a given individual—enable us to compute dispositional optimism at two different points in time (i.e. June 2020 and May 2021). Consistent with the notion of stability of optimism, the correlation between these two measures is 0.77. Fig 2 shows the positive association (and linear fit) between optimism over time.

Note: The figure illustrates the relationship between optimism in the first survey wave (June 2020) and the second wave (May 2021). The dots represent the observations whereas the green line is the linear fit.

https://doi.org/10.1371/journal.pone.0269707.g002

Entrepreneurial actions during the spring lockdown

As we discussed, several works in the literature suggest that optimistic entrepreneurs tend to engage in potentially wasteful actions; others suggest that optimistic entrepreneurs are better positioned to make proactive actions to improve performance in the wake of aversities. Theoretically, these mechanisms can have opposite effects on the ability to overcome a pandemic. We move to the data to understand the sign of this relationship.

Our first piece of evidence concerns the association between optimism and organizational change or innovation during the pandemic. We probe into this issue in Fig 3 , which shows that high-optimism entrepreneurs were much more likely to both innovate (in terms of products or processes) and make organizational changes to their business in the period from January to April 2020.

Note: The figure on the left (right) indicates the fraction of businesses which report to have made any innovation (organizational change) during January-April 2020, separately for entrepreneurs below and above the median threshold of optimism. The vertical line denotes the average fraction.

https://doi.org/10.1371/journal.pone.0269707.g003

We confirm these results in Tables 2 and 3 , where we estimate a set of linear probability models in which the dependent variables are, respectively, a dummy identifying instances of organizational change ( Table 2 ) or innovation ( Table 3 ) made during the Covid-19 pandemic. In these regressions, the key explanatory variable is dispositional optimism. Standard errors are adjusted for heteroskedasticity.

https://doi.org/10.1371/journal.pone.0269707.t002

https://doi.org/10.1371/journal.pone.0269707.t003

As shown in Column (1), optimism is positively associated with the likelihood of organizational and innovation upgrades: the coefficients of dispositional optimism are all positive and their significance is consistently around the 1% level.

Our regressions include a large set of control variables at the individual and business level to ameliorate concerns of omitted factor bias. An important driver of the tendency to make changes to the business during the pandemic was its exposure to the Covid-19 shock: firms that were more severely affected by Covid-19 (e.g. because they operate in industries directly hit by the lockdown policies) may have featured stronger incentives to make organizational changes; in turn, the revenue change of a firm during the pandemic may have been associated with the entrepreneur’s optimism (e.g. because of a different sorting of optimists and pessimists across sectors). To account for this potential source of omitted factor bias, in Column (2) of Tables 2 and 3 we control for the percentage change in revenues during the pandemic (which in our descriptive table we reported to be around -37%). Additionally, in Column (3) we explicitly control for industry effects by means of a (16-grouping) set of industry dummies (see S1 File ). Even keeping revenue change constant across entrepreneurs and estimating within-industry effects, dispositional optimism is positively associated with organizational change and innovation during the pandemic.

In the subsequent columns, we further control for a host of firm characteristics like the year when the business was founded, the number of employees before Covid-19, and a dummy equal to one whether the business was closed during the lockdown, as well as individual characteristics such as the entrepreneur’s age, his/her risk-aversion, gender, and educational attainment. The coefficients of these control variables indicate that more educated and risk-prone entrepreneurs were better equipped to react to Covid-19. That said, our main finding withstands the inclusion of these controls: in economic terms, the results in the most comprehensive specification (Column 5) indicate that a standard deviation increase in dispositional optimism is associated with a 2.5 times higher probability of organizational change, and 3 times higher probability of innovation.

Entrepreneurial expectations

Expectations are key in entrepreneurial decision-making because they guide the selection of strategic reference points and organizational aspirations. In this section, we explore how optimism shaped entrepreneurs’ expectations in the period following the spring lockdown (i.e. from June 2020 onward). We organize this analysis around three dimensions: (1) business-related outcomes; (2) diffusion of the pandemic in the UK; (3) macroeconomic conditions.

We start by providing some descriptive evidence by using the answers to a survey question about the estimated period necessary to restore revenues to the pre Covid-19 level of December 2019. Inspecting the distribution of this variable, we find that 80% of entrepreneurs expect a full recovery within one year. However, this finding varies depending on the level of optimism: 57% of high-optimism entrepreneurs (i.e. above the median threshold) expect a recovery within 6 months, whereas the fraction is 6 percentage points lower for low-optimism entrepreneurs (see S1 File ). Of course, the estimated recovery period depends on the size of the revenue drop and other business characteristics. Hence, to provide more compelling evidence, we estimate a regression in which the dependent variable is a continuous measure of the recovery period (in months), and the explanatory variables are entrepreneurs’ optimism together with the set of firm- and individual-level controls used so far. Results in Table 4 show that a standard deviation increase in optimism is associated with about a half-year faster expectation of revenue recovery. Importantly, this result is derived by controlling for the drop in revenues experienced during the spring lockdown. In Columns (2) and (3) of the table, we further show that optimism is positively associated with the expectation that revenues will exhibit an increase over the next year. Instead, optimism is not significantly associated with the likelihood that the business will be open in September 2020.

https://doi.org/10.1371/journal.pone.0269707.t004

We move to entrepreneurial expectations regarding the spread of the pandemic in the UK. Our survey contains a question where participants are asked to provide an estimate of the number of Covid-19 contagion cases at the end of July. To do so, they can choose between a set of pre-formulated answers displayed in terms of 5 thousand increments relative to the contagion cases at the time of the survey. Panel A of Table 5 shows the responses obtained (in which each subsequent category indicates a more severe diffusion of the pandemic). In Panel B of the table, we then show the results of an ordered logit regression in which the dependent variable is given by the different ordered responses shown in Panel A. Optimism appears to be negatively associated with the estimated severity of the pandemic in the UK.

https://doi.org/10.1371/journal.pone.0269707.t005

In conclusion, we estimate the association between entrepreneurial optimism and macroeconomic expectations. To do so, we take advantage of two survey questions which ask participants to estimate the UK’s GDP growth in the full years of 2020 and 2021. As Fig 4 shows, the average answers are -9% and -2%, respectively. However, consistent with our previous results, the distribution of responses from high-optimism individuals is slightly shifted to the right (i.e. they provide higher estimates of GDP growth).

The upper (lower) graph illustrates the kernel density of the responses to a question which asks entrepreneurs to estimate the GDP growth in the UK in 2020 (2021). The histograms are reported separately for entrepreneurs below and above the median threshold of optimism. The vertical lines denote the average value.

https://doi.org/10.1371/journal.pone.0269707.g004

This finding is confirmed by the regression analysis in Table 6 , which shows how a standard deviation increase in dispositional optimism is associated with a half percentage point higher expectation of GDP growth in 2020, and a 0.8 percentage point higher expectation of GDP growth in 2021.

https://doi.org/10.1371/journal.pone.0269707.t006

Performance

Our results so far have shown that high-optimism entrepreneurs engaged in a different set of actions (more oriented toward innovation and change) and exhibited a different set of expectations concerning the post-pandemic period. Yet, the analysis is silent about whether these attributes had a positive effect on ventures’ performance. The literature is replete with evidence showing that optimistic entrepreneurs destroy firm value due to unrealistic expectations or a tendency to discard external signals. At the same time, optimism may facilitate proactiveness and change, and hence improve the adaptation to difficult circumstances. As discussed in the data section, our follow-up survey in May 2021 contains a set of questions which allow us to measure revenue growth from 2019 to 2020, which can be used as a proxy of ventures’ success. Table 7 , Column 1, shows that dispositional optimism (measured in June 2020) is positively associated with revenue growth in the full year of 2020. This result is useful to discern the value implications of the results documented so far: optimism entrepreneurs were more proactive in making changes and also grew more during the pandemic. Column 2 shows that the result is robust to using the measure of optimism from the second survey wave (i.e. as of May 2021).

https://doi.org/10.1371/journal.pone.0269707.t007

Discussion and conclusion

While new ventures are crucial to spur technological progress and growth, they are notoriously subject to high failure rates. An important stream of research has aimed at understanding how entrepreneurs’ personal traits can help explain which businesses will thrive and which others will fail [ 40 , 41 ]. Dispositional optimism is one such trait. Indeed, existing works in this area show that optimism has far-reaching implications not only for individual behaviors [ 36 ] but also for the businesses that individuals lead. Some studies have found that optimistic entrepreneurs invest in disparate innovative projects [ 14 ] and tend to experience lower financial performance [ 15 ], while others have shown that optimism is conducive to organizational change [ 23 ] and is positively associated with business success [ 42 ]. Our contribution to this literature has been to explore the relationship between optimism and entrepreneurial actions during the Covid-19 pandemic, which drove out of business a significant number of firms and prompted a massive reallocation of output across and within industries. Understanding the ability of entrepreneurs to face these unprecedented challenges is thus crucial for both managerial and policy-making perspectives.

Our evidence, based on a comprehensive survey on UK entrepreneurs, indicates that new ventures experienced significant damages during the spring outbreak of Covid-19, though the impact was highly heterogeneous across firms. The key finding emerging from our study is that optimism helps to explain part of this heterogeneity across firms. In particular, we find that firms led by optimistic entrepreneurs had a higher likelihood of innovation and organizational changes, which were useful to weather the pandemic shock. Moreover, optimistic entrepreneurs display more positive beliefs toward future events: they expected their businesses to fully recover over shorter periods of time and, more generally, they had rosier expectations about macroeconomic conditions. Finally, examining data on ventures’ performance, our data reveal that high-optimism entrepreneurs grew more than low-pessimism entrepreneurs over the entire pandemic year of 2020. Collectively, our study reveals a bright side of dispositional optimism: it improves entrepreneurs’ readiness and facilitates successful adaptation to a negative shock.

Before concluding, we shall acknowledge that—despite the inclusion of a comprehensive set of control variables in the regression analysis—our study remains correlational in nature. To tease out more directly the causal effect of optimism on the ability of individuals to overcome a shock, a fruitful approach could be to leverage manipulations of optimism in a laboratory setting. Alternatively, future studies could use cross-sectional variations in optimism while exploiting the periods before and after a temporally well-defined shock (unlike Covid-19, which does not have a sharp ending point and thus does not permit a clear comparison of pre/post-shock periods).

Supporting information

Table A1. Classification of sectors. Table A2. Estimated recovery period—by optimism level.

https://doi.org/10.1371/journal.pone.0269707.s001

• View Article
• PubMed/NCBI
• Google Scholar
• 32. Dietrich A, Kuester K, Muller G, Schoenle R. 2022. News and uncertainty about Covid-19: Survey evidence and short-run economic impact. Journal of Monetary Economics, forthcoming.
• 34. Gompers P, Gornall W, Kaplan S, Strebulaev I. 2021. Venture capitalists and Covid-19. Journal of Financial and Quantitative Analysis, forthcoming.

• Link to Follow us on Twitter
• Link to Like us on Facebook
• Link to Connect with us on LinkedIn

Ivey Business Journal

The business of recovery.

• Share on LinkedIn
• Share on googlePlus
• Share on facebook
• Share on twitter
• Share by email

The COVID-19 outbreak offered businesses around the world a simple choice: adapt or die. Some organizations responded by engaging in digital transformation, while others focused on performing a social role by embracing charity, philanthropy, and other community-based activities. Results have understandably been mixed, and not just because of the unprecedented nature of the disruption created by the pandemic.

Simply put, the traditional tools of crisis management are not enough to maximize a firm’s chances of survival in today’s chaotic environment, which calls for a more holistic strategy. Indeed, in order to overcome the significant challenges introduced by COVID-19 and light up opportunities hidden in the outbreak’s dark tunnel, firms need to embark on a born-again journey of self-discovery and healing similar to the mental health recovery process. This involves accepting the need to engage in a grieving process that shapes a new raison d’être for the firm after rejecting traditional thinking and redefining business practices across the organization.

The conceptualization of deploying a business recovery process to develop a new, sustainable, and profitable business model in response to a crisis follows Albert Bandura’s social cognitive theory of human agency, which states that people are agents of their experience and not merely passive respondents to a deterministic environment or automatons driven by neurocognitive processes. Following this logic, firms should engage in a recovery process to proactively face any form of major disruption (digital, environmental, organizational, social, or viral). But deploying a recovery strategy in the corporate world, especially during a pandemic, requires clarity regarding its definition, not to mention how corporate managers should implement the process.

Based on my research and consulting work with clients across numerous industries, this article outlines the logic and stages of the Business Recovery Strategy Framework (see below, and explains how it can help managers organize their thinking and plan innovation while enabling them to adapt their organizations to the emerging behaviours and trends that represent the “new normal.”

Exhibit 1: Business Recovery Strategy Applied to Pandemic Disruption

Battling Inertia and Nostalgia 

One of the most commonly accepted realities of business is also one of the most ironic: successful firms with established business practices fail to adapt to unexpected changes in the market. As a result, these companies can experience a tough or easy recovery process depending on their ability to disengage from established organizational and business practices. Disengaging from a firm’s so-called best practices, of course, isn’t easy, since managers associate them with positive outcomes. But this association is based upon previous experiences, and when conditions change, previous best practices may no longer be a suitable driver of success. In fact, when facing a disruption, making decisions based on established best practices can be extremely costly.

Why do managers stick with established modes of thinking when dealing with the unexpected? Blame a combination of corporate inertia and nostalgia.

When facing a fluid external environment, these two factors lead many firms to consider internal change an additional threat. This, in turn, blocks the development of new modes of thinking or actions that can open the door to innovations and dramatically improve competitiveness in a new environment.

In business circles, being blinded by inertia and nostalgia when a disruptive force exposes an opportunity is often described as having a “Kodak moment.” Managers of Eastman Kodak—which filed for bankruptcy in 2012—infamously failed to disengage from established modes of thinking as they oversaw the invention of a technology that led to the company’s demise as an industry leader. As a result, instead of revolutionizing the sector after developing the first digital camera, the company tried using the new technology as a prop to support its existing business model.

As Forbes contributor Chunka Mui noted in a 2012 article on the legendary corporate blunder, the choice “to use digital as a prop for the film business culminated in the 1996 introduction of the Advantix Preview film and camera system, which Kodak spent more than $500M to develop and launch. One of the key features of the Advantix system was that it allowed users to preview their shots and indicate how many prints they wanted. The Advantix Preview could do that because it was a digital camera. Yet it still used film and emphasized print because Kodak was in the photo film, chemical and paper business.”

“Simply put, Kodak managers couldn’t read the writing on the wall because they put products over customers in their thinking. And unfortunately, glorifying established practices is common when businesses face the need to change.”

With management thinking stuck in the past, the photography pioneer simply assumed consumers would want a digital camera that still required them to buy film and pay for prints. And as the company kept investing in its film division, competitors focused on the opportunities created by the industry’s disruption. In 2013, Kodak entered Chapter 11 bankruptcy protection, emerging with a new focus on commercial printing.

Simply put, Kodak managers couldn’t read the writing on the wall because they put products over customers in their thinking. And unfortunately, glorifying established practices is common when businesses face the need to change. This is particularly true among CEOs of large B2B companies, where a mix of melancholy affection and convictions related to previous success prevent established companies from seeing a new context as a suitable period to undo their current business practices and modes of thinking, which are limiting their ability to strategically respond to disruptive forces. But it is a real problem for consumer-focused ventures as well.

Ultimately, corporate inertia and nostalgia will always lead to a loss of competitive advantage. Take, for example, the experience of small furniture businesses that have faced a perfect storm thanks to cheaper Chinese furniture, the advent of giant low-cost competitors such as IKEA, and 3D printing. This is an “adapt or die” situation. But many of these companies ironically, and firmly, believe that their previous path to success is part of their DNA even when that path is no longer profitable.

Whenever our normal is altered by a major disruption such as the current COVID-19 pandemic, fear and resistance are inevitable as we are hit with a flood of unanswered questions: Will the economy tank? Should our firm fire people? Should we cancel business and innovation projects? Can we develop better business practices than our pre-crisis practices? Is survival even possible?

This is a natural response. However, based on fear and resistance, this way of thinking tends to idealize pre-crisis situations. And as my academic research and years of consultancy work with small and large companies in multiple different sectors has shown, the “it-was-better-before mindset” doesn’t provide the foundation required for forming a relevant adaptation strategy that generates new business opportunities during a crisis. Instead, it leads to putting innovation on hold, which prevents the activation of a creative and proactive process that can expose new opportunities generated by changes in the market and competitive landscape.

Deploying a Business Recovery Strategy

Defining and implementing a business recovery strategy counters the natural inclination to idealize established business practices and modes of thinking when facing any major disruption, including a pandemic. But effectively deploying the framework to overcome inertia and nostalgia and emerge as an industry leader requires understanding that the process is a three-stage journey of self-discovery, reinvention, and goal setting that takes place in the context of a “new normal.”

STAGE ONE —Undergoing the disabling power of disruption: When first impacted by an event like the COVID-19 pandemic, firms are thrust into a state of unawareness, where they are suddenly dependent on others for context and ideas about how to react. At this stage, decision-making is driven by either hope or a feeling of powerlessness, while management strives to engage in actions that reduce employee stress and maintain stakeholder confidence. Measures taken often include policy changes affecting the entire organization or targeted departments such as human resources, sales, communications, and finance. A firm, for example, might move to enable employees to express their fears along with how the sudden disruption has affected their personal life and workplace productivity.

STAGE TWO —Change possible, but time limited: As a disrupted firm develops situational awareness, it becomes less dependent on external forces for context and ideas. In this stage of developing self-responsibility, management’s focus shifts toward exploring possibilities in the disruptive environment. During this “let’s-try-something” stage, interaction with employees can move beyond making sure everyone is coping as individuals by bringing employees from different departments together to creatively reflect on how to best move forward and manage three main priorities—clients, suppliers, and employees—in the new context. And by empowering employees to participate in the firm’s business recovery, management opens the door to creating a new sense of purpose across the entire organization.

STAGE THREE —Commit and act for change: Once aware of its situation and self-dependent, a firm can move to make logical changes that positively address—and even take advantage of—disruptions in both the workplace and market. After accepting the need to change and proactively engaging employees in the process, management exposes the light at the end of the pandemic tunnel by focusing on helping departments identify their new strengths and needs while redefining best practices for the new normal. During this stage, leadership generally knows what needs to happen and can express these needs to employees and external collaborators as they move to reinvent operations to thrive in the “new normal.”

Redefining Business Practices for a “New Normal”

The business world as we knew it just a few months ago will not survive the pandemic. But as tough as the coronavirus outbreak has been to manage, there is no question that the chaos created has presented businesses with an excellent opportunity to step back and reinvent themselves in ways that simply would not have been considered voluntarily under non-crisis conditions.

Indeed, thanks to COVID-19, it has never been easier to justify attacking deeply rooted convictions and established business practices.

But successfully navigating the business recovery process requires all concerned to like “the new me.” To help stakeholders appreciate the reinvented firm, managers should take the following actions to align key business practices with the new normal:

BUSINESS STRATEGY: When facing a “new normal,” a firm’s strategic review process should be demystified. Instead of being exclusively led by top managers, strategy development in times of major crisis should take a holistic and multidisciplinary approach.

ORGANIZATION: In a “new normal” context, firms should set up a committee charged with anticipating possible future disruption in order to maintain a readiness to quickly adapt to unexpected and dramatic changes in the competitive landscape or market conditions.

FINANCE: In a “new normal” situation, firms should engage in relevant cost reduction strategies while creatively sourcing the funding necessary to avoid cutting key employees and budgets.

HUMAN RESOURCES: When social distancing needs subside and reduce the need for remote working, employers should consider a hybrid path forward instead of a return to previous workplace practices. This path forward should be based on both the productivity results achieved during the pandemic period as well as the needs and feelings of employees.

CUSTOMER: In the post-pandemic era, companies should ensure they understand exactly how customers coped with the crisis along with the related new customer needs and behaviours that the crisis created. This requires shifting from traditional market research tools (e.g., surveys and big data) to more immersive and ethnographic methods to collect richer insights and data.

MARKETING. In the “new normal,” companies should implement a more bottom-up marketing strategy. Thinking needs to shift from a product-centric to a more customer-centric logic as well as from traditional marketing—based on the 4Ps or 7Ps of Kotler (Kotler, 2003; Kotler et al., 2001)—to the new experiential marketing and its 7Es (Batat, 2019).

COMMUNICATION AND BRANDING: Moving forward, companies should focus more on value and consider empathic communication and branding strategies. Consumers need to know that brands care and are active as social actors.

DIGITAL: This pandemic crisis has highlighted both the positive and negative sides of digital transformation, presenting an opportunity for a rethink. Companies should consider strategies that are more of a combination of the physical and digital, or “phygital” (Batat, 2019). This can help companies better connect their physical spaces to their digital spaces, offering more positive and productive experiences to employees and customers.

Cutting budgets, firing people, freezing projects, or canceling events is not the only way to respond when challenged by the unexpected. Whether the crisis at hand is technological, social, economic, political, or viral, the holistic recovery process outlined above can help firms move beyond comfort zones and emerge from any disruption as a faster and stronger competitor by developing new modes of thinking and acting.

But a successful recovery will always depend on how well business leaders understand what exactly enables the process to work. In other words, failing to disengage from established practices and ways of thinking will never help management regain control of a disrupted firm’s fate—it will only ensure the business remains a passive victim of the unexpected.

REFERENCES:

Atkinson and M. Hammersley, “Ethnography and Participant Observation,” in N. K. Denzin and Y. S. Lincoln (Eds.), Handbook of Qualitative Research (London, UK: Sage, 1994), 248–261.

Bandura, “Social Cognitive Theory: An Agentic Perspective,” Annual Review of Psychology 52 , no. 1 (2001): 1–26.

Batat, Experiential Marketing: Consumer Behavior, Customer Experience, and The 7Es (London, UK: Routledge, 2019).

P. Bate, “Whatever Happened to Organizational Anthropology? A Review of the Field of Organizational Ethnography and Anthropological Studies,” Human Relations 50 , no. 9 (1997): 1147–1175.

Collins and S. Crowe, “Research, Recovery and Mental Health: Challenges and Opportunities,” Mental Health and Social Inclusion 20 , no. 3 (2016): 174–179.

Easterby-Smith and D. Malina, “Cross-Cultural Collaborative Research: Toward Reflexivity,” The Academy of Management Journal 42 (1999): 76–86

Kotler, Marketing Management , 11th Ed. (Prentice Hall International Editions, 2003).

Kotler, G. Armstrong, J. Saunders, and V. Wong, Principles of Marketing , 3rd European Ed. (Prentice Hall, Pearson Education Limited, 2001).

Leave a Reply Cancel reply

Please submit respectful comments only, including full name, professional title, and contact information (only name and title will be posted). Required fields are marked *

Name/Professional Title *

Phone Number *

Save my name, email, and website in this browser for the next time I comment.

© Copyright 2022 Ivey Business School Foundation. All rights reserved. Privacy Policy .

Advertisement

Small business disaster recovery: a research framework

• Original Paper
• Published: 16 January 2014
• Volume 72 , pages 597–616, ( 2014 )

Cite this article

• Maria I. Marshall 1 &
• Holly L. Schrank 1  

3193 Accesses

69 Citations

4 Altmetric

Explore all metrics

No man is an island, Entire of itself. Each is a piece of the continent, A part of the main. If a clod be washed away by the sea Europe is the less… John Donne (1572–1631)

Exogenous, non-normative shocks to small businesses such as natural disasters have been understudied. Moreover, most disaster research on small businesses has focused on business recovery as a dichotomy at one point in time. However, disaster recovery for small businesses is an iterative process set in the context of individual, family/household, and community recovery over time. A new dynamic research framework for small business recovery is proposed which allows for a shared framework and vocabulary.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Predicting small business demise after a natural disaster: an analysis of pre-existing conditions

Analysis of post-disaster damage and disruptive impacts on the operating status of small businesses after hurricane katrina, the effect of cash flow problems and resource intermingling on small business recovery and resilience after a natural disaster.

The Small Business Recovery and Demise Project was funded by the National Science Foundation Grant #0856221.

Aldrich DP (2012) Building resilience: social capital in post-disaster recovery. University of Chicago Press, Chicago, IL

Book   Google Scholar  

Alesch DJ (2003) Complex urban systems and extreme events: toward a theory of disaster recovery. Public Entity Risk Institute, Fairfax, VA

Google Scholar  

Alesch DJ, Holly JN (1996) How to survive the next natural disaster: lessons for small business from Northridge victims and survivors. Pan Pacific Hazards Conference, Disaster Preparedness Resource Centre, University of British Columbia, Vancouver, Canada

Alesch DJ, Holly JN, Mittler E, Nagy R (2001) Organizations at risk: what happens when small businesses and not-for-profits encounter natural disasters. Public Entity Risk Institute, Fairfax, VA. http://www.riskinstitute.org/uploads/ptrdocs/Organizations_at_risk.pdf . Accessed May 22, 2006

Aono F, Tanaka S, Hayashi H, Shigekawa K, Miyano M (1998) Disaster victim’s behavior after the great Hanshin-Awaji Earthquake Disaster ~ the case of Nishinomiya-city. In Annual Conference of the Institute of Social Safety Science (No. 8, pp. 36-39) (in Japanese) as cited by Kimura R (2007) Recovery and reconstruction calendar. J Disaster Res 2:465–474

Barbour H (2009) Bay St. Louis harbor project a big step in ground zero Katrina recovery. Downloaded 22 Feb 2013 from http://msdisasterrecovery.com/index.php?option=com_content&view=article&id=73&Itemid=37&lang=us

Bell MA (2002) The five principles of organizational resilience. Gartner Research ID:AV-15-0508

Berke PR, Kartez J, Wenger D (1993) Recovery after disaster: achieving sustainable development, mitigation, and equity. Disasters 17:93–109

Article   Google Scholar  

Bolin RC (1976) Family recovery from natural disaster: a preliminary model. Mass Emerg 1:67–277

Bolin RC, Stanford L (1991) Shelter, housing and recovery: a comparison of U.S. Disasters. Disasters 15:24–34

Brown D, Saito K, Spence R, Chenvidyakarn T, Adams B, Mcmillan A, Platt S (2008) Indicators for measuring, monitoring and evaluating post-disaster recovery. In: Sixth international workshop on remote sensing for disaster response for disaster response, University of Pavia, Italy, 11–12 September

Bruneau M, Chang SE, Eguchi RT, Lee GC, O’Rourke TD, Reinhorn AM, Shinozuka M, Tierney K, Wallace WA, von Winterfeldt D (2003) A framework to quantitatively assess and enhance the seismic resilience of communities. Earthq Spectra 19:733–752

Buckland J, Rahman M (1999) Community based disaster management during the 1997 Red River Flood in Canada. Disasters 23:174–191

Burby RJ (ed) (1998) Confronting natural hazards: land-use planning for sustainable communities. National Academy/Joseph Henry Press, Washington, DC

Chang SE (2010) Urban disaster recovery: a measurement framework and its application to the 1995 Kobe earthquake. Disasters 34:303–327

Chang SE, Miles S (2004) The dynamics of recovery: a framework. In: Okuyama Y, Chang SE (eds) Modeling spatial and economic impacts of disasters. Springer, New York, pp 181–204

Chapter   Google Scholar  

Cutter SL, Barns L, Berry M, Burton C, Evans E, Tate E, Webb J (2008) A place-based model for understanding community resilience to natural disasters. Global Environ Change 18:598–606

Dahlhamer JM, D’Souza JM (1997) Determinants of business disaster preparedness in two U.S. metropolitan areas. Int J Mass Emerg Disasters 15:265–281

De Silva DG, Kruse JB, Wang Y (2006) Catastrophe-induced destruction and reconstruction. Nat Hazards Rev 7:19–25

Dynes R (2005) Community social capital as the primary basis of resilience. Preliminary Paper 344, University of Delaware Disaster Research Center

Ewing B, Kruse J, Sutter D (2007) Symposium: hurricanes and economic research: an introduction to the Hurricane Katrina. South Econ J 74:315–325

FEMA (Federal Emergency Management Agency) (2000) Hazards, disasters and the US emergency management system: an introduction, Session 6: fundamentals of US emergency management. Washington, DC: FEMA as cited by Chang SE (2010) Urban disaster recovery: a measurement framework and its application to the 1995 Kobe earthquake. Disasters 34:303–327

FEMA (Federal Emergency Management Agency) (2007) Bay St. Louis ceremony begins multi-million utility infrastructure repair, renovation, Release 1604-592. Downloaded February 22 2013 from http://www.fema.gov/news-release/2007/08/29/bay-st-louis-ceremony-begins-multi-million-utility-infrastructure-repair

Forgette RG, Van Boening MV (2009) Measuring and modeling community resilience: SERP and DyME. http://www.serri.org/publications/Documents/Ole%20Miss%20Project%2080038%20Measuring%20and%20Modeling%20Community%20Resilience%20-%20Global%20Horizons%20Submission%20(Forgette%20and%20Boening).pdf . Accessed February 6, 2011

Guimaraes P, Hefner F, Woodward D (1993) Wealth and income effects of natural disasters: an econometric analysis of Hurricane Hugo. Rev Region Stud 23:97–114

Haddow GD, Bullock JA (2006) Introduction to emergency management, 2nd edn. Elsevier, New York

Hamel G, Välikangas L (2003) The quest for resilience. Harvard Bus Rev 1–14

Haviland WA (2003) Anthropology. Wadsworth, Belmont, CA

Jarmin R, Miranda J (2009) The impact of Hurricanes Katrina, Rita, and Wilma on business establishments. J Bus Valuation Econ Loss Anal 4: Article 7

Jordan E, Javernick-Will A (2013) Indicators of community recovery: content analysis and Delphi approach. Nat Hazards Rev 14:21–28

Kage R (2012) Making reconstruction work: civil society and information after war’s end. Comp Polit Stud 43:163–187

Karatani Y, Hayashi H (2007) Quantitative evaluation of recovery process in disaster-stricken areas using statistical data. J Disaster Res 2:453–464

Killian LM (2002) An introduction to methodological problems of field studies in disasters, Chapter 3. In Stallings RA (ed) 2002 Methods of disaster research, International Committee on Disasters. Xlibris

Kimura R (2007) Recovery and reconstruction calendar. J Disaster Res 2:465–474

Kroll CA, Landis JD, Shen Q, Stryker S (1991) Economic impacts of the Loma Prieta earthquake: a focus on small business, working paper no. 91-187. University of California Transportation Center and the Center for Real Estate and Economics, University of California, Berkeley, CA

Lindell M, Perry RW (2000) Household adjustment to earthquake hazard: a review of research. Environ Behav 32:590–630

Maguire B, Cartwright S (2008) Assessing a community’s capacity to manage change: a resilience approach to social assessment. Australian Government Bureau of Rural Sciences. http://adl.brs.gov.au/brsShop/data/dewha_resilience_sa_report_final_4.pdf . Accessed February 4, 2011

Miles SB, Chang SE (2006) Modeling community recovery from earthquakes. Earthq Spectra 22:439–458

Miles SB, Chang SE (2011) ResilUS: a community based disaster resilience model. Cartogr Geogr Inform 38:36–51

Mileti DS (1999) Disasters by design: a reassessment of natural hazards in the United States. Joseph Henry Press, Washington, DC

Nakagawa Y, Shaw R (2004) Social capital: a missing link to disaster recovery. Int J Mass Emerg Disasters 22:5034

Nigg JM (1995) Disaster recovery as a social process. (Preliminary Paper #219). Newark, DE: University of Delaware, Disaster Research Center. http://udspace.udel.edu/bitstream/handle/19716/625/PP219.pdf . Accessed April 7, 2013

Olshansky RB (2005) Toward a theory of community recovery from disaster: a review of existing literature. In: Paper presented at the 1st international conference on urban disaster reduction, 18–20 January. Kobe Japan

Olshansky RB, Chang S (2009) Planning for disaster recovery: emerging research needs and challenges. In: Blanco H, Alberti M (eds) 2009 Shaken, shrinking, hot, impoverished and informal: emerging research agendas in planning. Progr Plan 72:200–209

Olshansky RB, Hopkins LD, Johnson LA (2012) Disaster and recovery: processes compressed in time. Nat Hazards Rev 13:173–178

Peacock WG, Killian CD, Bates FL (1987) The effects of disaster damage and housing aid on household recovery following the 1976 Guatemalan earthquake. Int J Mass Emerg Disasters 5:63–88

Quarantelli E (1999) The disaster recovery process: what we know and do not know from research. University of Delaware Disaster Research Center, Preliminary Paper #286

Rose A, Liao S (2005) Modeling regional economic resilience to disasters: a computable general equilibrium analysis of water service disruptions. J Reg Sci 45:75–112

Rose A, Lim D (2002) Business interruption losses from natural hazards: conceptual and methodological issues in the case of the Northridge earthquake. Environ Hazard 4:1–14

Rose A, Benavides J, Chang S, Szczesniak P, Lim D (1997) The regional economic impact of an earthquake: direct and indirect effects of electricity lifeline disruptions. J Reg Sci 37:437–458

Runyan RC (2006) Small business in the face of crisis: identifying barriers to recovery from a natural disaster. J Contings Crisis Manag 14:12–26

Schiller AR (2011) The impact of a storm surge on business establishments in the Houston MSA. Nat Hazards 56:331–346

Schrank HL, Marshall MI, Hall-Philips A, Wiatt RF, Jones NE (2013) Small business demise and recovery after Katrina: rate of survival and demise. Nat Hazards 65:2353–2374

Singh JV, Lumsden CJ (1990) Theory and research in organizational ecology. Annu Rev Sociol 16:161–195

Smith GP, Wenger D (2007) Sustainable disaster recovery: operationalizing an existing agenda. In: Rodriguez H, Quarantelli EL, Dynes RR (eds) Handbook of disaster research. Springer, New York, NY, pp 234–257

Starr R, Newfrock J, Delurey M (2003) Enterprise resilience: managing risk in the networked economy. Strat + Bus 30

Sullivan M (2003) Integrated recovery management: a new way of looking at a delicate process. Aust J Emerg Manage 18:4–27

Sullivan A, Sheffrin SM (2003) Economics: principles in action. Pearson Prentice Hall, Upper Saddle River, NJ

Swanson DA, McKibben JN, Wombold L, Forgette RG, Van Boening MV (2009) The demographic effects of Katrina: an impact analysis perspective. Open Demogr 2:36–46

Tainer PB, Bolin R, Ramos R (1977) Reestablishing homes and jobs: families. In: Haas JE, Kates RW, Bowden MJ (eds) Reconstruction following disaster. MIT Press, Cambridge, MA

Takashima S, Hayashi H (1999) Quantitative grasping method for recovery status using electricity consumption time series data: application to the great Hanshin-Awaji earthquake. Jpn Society Nat Disaster Sci 18:355–367 (in Japanese), as cited by Karatani Y, Hayashi H (2007) Quantitative evaluation of recovery process in disaster-stricken areas using statistical data. J Disaster Res 2:453–464

Tanaka S, Hayashi H, Shigekawa K (1999) Behavior of disaster victims along the course of disaster process. J Jpn Society Natl Disaster Sci 18:21–29 (in Japanese) cited by Kimura R (2007) Recovery and reconstruction calendar. J Disaster Res 2:465–474

Tatsuki S (2007) Long-term life recovery processes among survivors of the 1995 Kobe earthquake: 1999, 2001, 2003, and 2005 life recovery social survey results. J Disaster Res 2:484–501

Thompson MA (2009) Hurricane Katrina and economic loss: an alternative measure of economic activity. J Bus Valuat Econ Loss Anal 4: Article 5

Tierney KJ (2007) Businesses and disasters: vulnerability, impacts, and recovery. In: Rodriguez H, Quarantelli EL, Dynes RR (eds) Handbook of disaster research. Springer, New York, NY, 275–296

Tierney KJ, Dahlhamer JM (1997) Business disruption, preparedness and recovery: lessons from the Northridge earthquake (Preliminary Paper #257). University of Delaware, Disaster Research Center, Newark, DE. http://udspace.udel.edu/handle/19716/657 . Accessed August 28. 2007

United States Bureau of Census (2011) www.census.gov/newsroom/releases/archives/business_ownership/cb11-110.html . Accessed April 9, 2013

Webb GR, Tierney KJ, Dahlhamer JM (2000) Business and disasters: empirical patterns and unanswered questions. Nat Hazards Rev 1:83–90

Webb GR, Tierney KJ, Dahlhamer JM (2002) Predicting long-term business recovery from disaster: a comparison of the Loma Prieta Earthquake and Hurricane Andrew. Global Environ Chang Part B Environ Hazards 4:45–58

Weil F (2010) The rise of community engagement after Katrina. In: The New Orleans Index at five. Brookings Institution and Greater New Orleans Community Data Center, Washington, DC, pp 1–20

Winter M, Danes SM, Koh S, Fredericks K, Paul JJ (2004) Tracking family businesses and their owners over time: panel attrition, manager departure and business demise. J Bus Ventur 19:535–559

Xiao Y, Van Zandt X (2011) Building community resiliency: spatial links between household and business post-disaster return. Urban Stud 11:2532–2542

Zhang Y, Lindell MK, Prater CS (2009) Vulnerability of community businesses to environmental disasters. Disasters 33:38–57

Download references

Author information

Authors and affiliations.

Department of Agricultural Economics, Purdue University, 403 West State Street, West Lafayette, IN, 47907, USA

Maria I. Marshall & Holly L. Schrank

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Maria I. Marshall .

Rights and permissions

Reprints and permissions

About this article

Marshall, M.I., Schrank, H.L. Small business disaster recovery: a research framework. Nat Hazards 72 , 597–616 (2014). https://doi.org/10.1007/s11069-013-1025-z

Download citation

Received : 17 July 2013

Accepted : 27 December 2013

Published : 16 January 2014

Issue Date : June 2014

DOI : https://doi.org/10.1007/s11069-013-1025-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Recovery process
• Recovery models
• Small business
• Find a journal
• Publish with us
• Track your research