Socio-economic effects of tourism : An occupation-based modelling approach from Sweden

• Planners and developers in regions showing touristic activities are typically interested in measuring the economic impact of tourism (Dwyer et al. 2004; Klijs et al. 2012; Kim & Kim 2015). However, even ‘advanced’ economic impact models neglect major societal dimensions, such as income equality or the type and quality of occupations in the various tourism-related sectors (Mazumder et al. 2012; Kronenberg et al. 2018). While neo-classic economics is still representing the dominant paradigm (Dobusch & Kapeller 2009), economic impact models ‘fulfill’ their purpose in incorporating the assumptions of mainstream economics and in focusing on macro-level indicators related to economic growth (Elsner 2017). However, a growing body of literature starts criticizing mainstream economics’ modelling assumptions and its narrow view of ‘monetary reductionism’, thus hampering advanced approaches able to consider socio-economic effects (Söderbaum 2017). In their seminal paper on the Social Region, Moulaert & Nussbaumer (2005) argue that the focus of regional development theories should turn away from market competition towards concepts that effectively incorporate dimensions of a region’s social, political, cultural and community development. By doing so, the authors highlight various forms of inequality that typically impede the path towards the Social Region (ibid, 2005b).Behind this background, the aim of this study is to propose a new approach that allows the measurement of tourism impact from a broader socio-economic perspective. In order to overcome the predominant growth focus, the study of tourism’s socio-economic impact comprises a macro as well as a meso level analysis and utilizes a mixed-method approach (Dopfer et al. 2004). More concretely, the macro level analysis of tourism’s socio-economic impact, first, includes the regionalization of the national Input-Output model to estimate primary and secondary employment and income effects for the Swedish region of Jämtland (Flegg & Tohmo 2011). In contrast to typical economic impact studies in tourism (Mazumder et al. 2012) and in order to estimate employment and income effects for various occupational domains individually and within various tourism-related sub-sectors, we extend the analysis by applying the occupation-based modelling (OBM) approach (Daniels et al. 2004). This approach allows estimating income inequalities and its variations over time (in our case from 2008 to 2015) for major tourism sectors, expressed by Gini coefficients and Lorenz curves, respectively (Lee & Kang 1998). Findings highlight that the incomes in the accommodation & food sector fall below the regional average - the lowest among all tourism-related industries. Interestingly, compared to others sectors (e.g. recreation & entertainment, retail), income inequality within this sector is relatively low (i.e. Gini coefficient = 0.15). However, growing coefficients are pointing at a negative trend over time: Between 2008 and 2013, the income of the top 15% earning occupations increased by 8%, while income of the bottom 15% earning occupations grew only by 1%. The latter occupations comprise seasonal workers, cleaning personal and kitchen assistants. We further analyze and critically discuss occupational developments and related income distributions (i.e. Gini coefficient trends) for major tourism-related sub-sectors of the Swedish region of Jämtland.The second part of the analysis relates to the meso-level (Dopfer et al. 2004). A series of qualitative interviews with major regional industry and policy representatives (e.g. labor unions, hotel association, etc.) helped identifying potential reasons for variations in occupation and income developments in tourism. Findings show that large parts of low income workers stay in their job for only a short time, implying that newly employed workers are continuously hired at low (i.e. entry-level) wages. Furthermore, because of their expected short-term employment, tourism workers consider union memberships as unnecessary (Kjellberg 2017). Interestingly, the interviews helped identify also promising career opportunities showing steadily increasing income levels. These jobs, however, require higher educational profiles. Like in other branches, only higher education levels seem to overcome the low-income situation in tourism. To conclude, the interviewed industry-representatives perceived the proposed approach of occupation-based modelling and its related findings from measuring income inequalities particularly well. This gives reason for hope that in tourism regions new methods of socio-economic impact analysis will be implemented and institutionalized in the future. 

Ämnesord

SAMHÄLLSVETENSKAP  -- Annan samhällsvetenskap (hsv//swe)

SOCIAL SCIENCES  -- Other Social Sciences (hsv//eng)

Nyckelord

Socio-economic impact

input-output modelling

occupation-based modelling

income inequality

Gini coefficients

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