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After the Ground Stopped Shaking: Socioemotional Wealth and Social Capital in Post-Disaster Recovery of Small Family Businesses

Rocky Adiguna
November 21, 2014

After the Ground Stopped Shaking: Socioemotional Wealth and Social Capital in Post-Disaster Recovery of Small Family Businesses

Presented at RENT Conference XXVIII, 21 November 2014

Rocky Adiguna

November 21, 2014
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  1. After the Ground Stopped Shaking: Socioemotional Wealth and Social Capital

    in Post-Disaster Recovery of Small Family Businesses Rocky Adiguna, University of Luxembourg Abshir Sharif, Jönköping International Business School (Alumni) RENT Conference XXVIII, 21 November 2014
  2. Contextual background • 6.3-magnitude earthquake struck the city of Yogyakarta

    (Bantul region), Indonesia in May 27, 2006 • > 5,700 dead, > 38,000 injured, ± 600,000 displaced • Small businesses were severely affected • Local economy was in quagmire 2
  3. Research question Does socioemotional wealth enhance or diminish the role

    of social capital in post-disaster recovery of small family businesses? 5
  4. Small family business • Small business is any business that

    is independently owned and operated, not dominant in its field, and does not engage in any new marketing or innovative practices (Carland, Hoy, Boulton, & Carland, 1984). • 70-80% of small businesses are family-owned firms (Matlay, 2002) • Family business is “a business may be considered as a family business to the extent that its ownership and management are concentrated within a family unit.” (Litz, 1995) • Operationalization: “a business that is operated by the family, is operated for profit, and not dominant in its field” 6
  5. Post-disaster recovery • Post-disaster recovery (Quarantelli, 1999): • Reconstruction: physical

    structure • Restoration: reestablishing physical & social patterns • Rehabilitation: people • Recovery: bringing them up to an acceptable level • Literatures on post-disaster recovery are largely focused in the areas of relief aid management, short- and long-term economic development, hazard and natural disaster risk management, and socioeconomic conditions after a disaster: Portrayal through the lens of small business is scarce. (Galbraith & Stiles, 2006) 7
  6. Social capital • Social capital as a means to achieve

    certain outcomes • While other types of capital—such as human capital, economic capital, and cultural capital—are focused on the quality of individuals, social capital puts emphasis on the network between individuals (Lin, 1999) • Social capital is “the sum of the actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or social unit” (Nahapiet & Goshal, 1998, p. 243) • Paradox: Weak ties are essential for individuals’ opportunities and their integration into the communities, while strong ties will lead to overall fragmentation. (Granovetter, 1973) 8
  7. Community support as manifestations of social capital • The interaction

    between the business and the surrounding community gradually creates bonds that eventually will be a source of recovery in disaster (Paton, 1997) • Case studies in Kobe, Japan and Gujarat, India earthquakes have shown that level of trust, norms, and participation for collective actions in the communities played important roles for disaster recovery (Nakagawa & Shaw, 2004) • Operationalization: “the support received from the surrounding friends and neighbors to the business recovery both financially and non-financially through moral, spiritual, and physical support” 9
  8. Institution support as manifestations of social capital • A study

    on Hurricane Andrew found that household recovery depended on both private funds and federal and state public assistance programs (Dash, Peacock, & Morrow, 2000). • Becker (2005) cited in Aldrich (2012) argues that while aid can obviously help in the immediate response to disaster, the large inflow of aid from rich nations will only assist in the very near term • Operationalization: “the amount of aid, supplies, and experts provided to the area by the government and NGOs” 10
  9. Socioemotional wealth • Socioemotional wealth (SEW): Non-economic aspects or affective

    endowments of family owners (Berrone et al., 2012) • Family firms are willing to be exposed to a significant risk to their performance in favor of preserving their SEW (Gómez-Mejía et al., 2007) • “The value of SEW to the family is more intrinsic, its preservation becomes an end in itself, and it is anchored at a deep psychological level among family owners whose identity is inextricably tied to the organization.” (Berrone et al., 2010, p. 87) 12
  10. Socioemotional wealth • Dimensions of SEW: FIBER (Berrone et al.,

    2012) • [F]amily control and influence, • [i]dentification of family members with the firm, • [b]inding social ties, • [e]motional attachment of family members, and • [r]enewal of family bonds to the firm through dynastic succession 13
  11. Socioemotional wealth • Three assumptions: • The possession of SEW

    is a trade-off between affective endowments and economic gains • Family firms will favor SEW rather than uncertain economic benefits • Extreme events may force family firms to forgo SEW goals to achieve business survival 14
  12. Methods Research design and sample • Quantitative cross-sectional study •

    Purposive sampling: Small family businesses in Bantul region, Yogyakarta, Indonesia • Data collection period: March until May 2013 • 87 responses, 4 no-returns • Final sample with full information: 79 respondents (91% of original sample) 16
  13. Methods Variables and measures (1/2) • Dependent variable: family business

    recovery • Operationalization: The financial performance of the business after disaster, measured by the discrepancy of average monthly turnover between pre- and post- disaster when the research was performed • Three independent variables: • Community support (2 items, Cronbach’s alpha = 0.84) • Institution support (3 items, Cronbach’s alpha = 0.72) • SEW (15 items, Cronbach’s alpha = 0.79) 17
  14. Methods Variables and measures (2/2) • Control variables: • Level

    of damage caused by the disaster • Gender of the owner • Business as main source of income • Level of education 18
  15. Results 19 Variables Mean S.D. 1 2 3 4 5

    Turnover discrepancy 119.620 3.458.364 1 SEW (standardized) 0 0,50 −0.17 1 Community support (standardized) 0 0,93 −0.16 0.17 1 Institution support (standardized) 0 0,80 −0.28* 0.10 0.54*** 1 Education 3,25 1,03 −0.12 −0.15 −0.09 −0.18 1 Damage level 2,67 1,08 −0.08 0.19 −0.38*** −0.20 −0.19 *p < 0.05; ** p < 0.01; *** p < 0.001 (n = 79) Table 1. Means, standard deviations and correlations for quantitative variables
  16. Results Base model Independent Model Contingency model Coefficient t-statistic Coefficient

    t-statistic Coefficient t-statistic Control variables Gender −0.15 −1.11 Education −0.13 −1.08 Business as the main source of income 0.06 0.52 Damage level −0.16 −1.23 Main effect variables Community support −0.08 −0.58 Institution support −0.35** −2.69 SEW −0.14 −1.23 Interaction SEW × Community support 0.26* 2.20 SEW × Institution support 0.27* 2.43 Model R2 0.04 0.21 0.39 Adj. R2 −0.01 0.13* 0.31*** F-statistic 0.86 2.71 4.93 Change in R2 0.17 0.18 Change in F 4.99 10.23 Standardized regression coefficients are displayed in the table. *p < 0.05; ** p < 0.01; *** p < 0.001 (n = 79) Table 2. Independent and contingency models of community support, institution support, socioemotional wealth, and turnover discrepancy 20
  17. Results 21 1 1.5 2 2.5 3 3.5 4 4.5

    5 Low Community Support High Community Support Turnover Discrepancy Low SEW High SEW Figure 1. Interaction plot between community support and SEW
  18. Results 22 Figure 2. Interaction plot between institution support and

    SEW 1 1.5 2 2.5 3 3.5 4 4.5 5 Low Institution Support High Institution Support Turnover Discrepancy Low SEW High SEW
  19. Discussion Community support & SEW on recovery • The embeddedness

    of a business in the community is a source of advantage for family business • In Indonesia where it has a relatively weak institutional system, people rely more on the informal system, especially in the rural area where the collectivism is much higher Institution support & SEW on recovery • The aid given from the institutions has a latent effect that made those who were affected had a ‘victimism’ mentality and became dependent on the aid with no struggle to be proactive 23
  20. Limitations • Recall decay • Simplified questionnaire • Lack of

    (valid) database of small businesses from the local government • Blended nature of recovery and growth • Turnover discrepancy as a generic measurement of recovery • Time and budget constraints—low sample size 24
  21. Conclusion • SEW can be a source for sustainable advantage

    • Our findings contradict the assumption of trade-off between SEW vs. economic benefits: Both can co-exist and amplify each other • In times of post-disaster, the pressure is not only for the business that has to thrive, the family has to survive as well. To favor one at the expense of another is not an option • Future research: • Contextualization: SEW as a strategizing framework within the business and acknowledge business embeddedness in the community where strategy is made jointly between businesses 25