International Journal of Environmental Research University of Tehran ISSN: 1735-6865 EISSN: 2008-2304 Vol. 4, Num. 3, 2010, pp. 407-414

International Journal of Environmental Research, Vol. 4, No. 3, July-September, 2010, pp. 407-414

Article

Environmental sustainable management of small rural tourist enterprises

Ferrari, G . ¹ , Mondéjar-Jiménez, J. ^2* , Vargas - Vargas, M . ³

¹ Department of Statistics, University of Florence, Italy
² Faculty of Social Sciences, University of Castilla-La Mancha, Spain
³ Faculty of Economics, University of Castilla-La Mancha, Spain

Correspondence Address: *Faculty of Social Sciences, University of Castilla-La Mancha, Spain
Jose.Mondejar@uclm.es

Date of Submission: 12-Nov-2009
Date of Decision: 15-Apr-2010
Date of Acceptance: 25-Apr-2010

Code Number: er10044

Abstract

Keywords: Ecopreneur, Environment, Sustainable Rural Tourism, PLS, FIMIX

Introduction

Rural and nature tourism has experienced high growth over the past 20 years. On one hand, it has become an alternative to other more traditional forms of tourism, driven by increased environmental aware-ness of tourists, especially those from developed coun-tries. After this first phase, the second stage is more complex and the focus is on expansion, differentiation and sustainability (Long & Lane, 2000). One of the pri-mary challenges facing rural tourism management is to establish a profitable and environmentally sustainable industry. Moreover, sustainable tourism is a complex concept and it requires that nature and tourism activity should be studied from an integrated point of view (Farrel & Twinning-Ward, 2005). This is particularly im-portant in the rural tourism context that is highly de-pendent on natural resources.It is increasingly being recognized, that the challenges facing rural tourism man-agement can be more effectively addressed by apply-ing new ways of thinking and doing based on prin-ciples of sustainable development. Planning, manage-ment, integration into local economy, partnership and cooperation, assessment, research and training and edu-cation, are tools that should be implemented for sustainability of the rural tourism.

The earlier investigations of the environmental management were focused on the reduction of costs and effects associated with the environmental protec-tion and their influence on competitiveness. The ben-efits that result from enhanced demand may act as an incentive for voluntary environmental management ac-tivities by tourism enterprises (Huybers & Bennett, 2002). In the supply side, these activities are related to cost saving achieved in certain areas, as water and energy usage, product purchase or waste minimiza-tion. In the demand side, the tourism enterprises can offer enhanced tourism experiences to increasingly environmentally aware tourists (Mihalic, 2000).

In the specialized literature, limited academic in-terest has focused on small firm management and en-vironmental response. The numerical dominance of small tourism enterprises and their central role in hu-man activities suggest that these entities have a rel-evant role on sustainability. However, there is no com-prehensive mechanism to evaluate their contribution (Tzschentke et al., 2008). The research in this area has focused on small tourism enterprises' attitudes (Carlsen et al., 2001), interpretation and their applica-tion of sustainable tourism principles (Revell & Rutherfoord, 2003). But, the adoption, and mainte-nance, of environmentally responsible practices by this group of firms is therefore especially critical. There-fore, there is an apparent disconnect between atti-tudes and action in the small firm context: an owner-manager can have a positive attitude towards the en-vironment in general but, this is frequently not trans-lated into appropriate environmental practices (Tilley, 1999; Vernon, et al., 2003).Environmental concern was initially measured in relation to specific issues and cor-related to socio-demographic and personality variables. Later, some studies identifying a correlation between cognitive, attitudinal and behavioral variables using a multi-dimensional scale (Schlegelmilch et al., 1996).

Environmental business management has focused, traditionally, on why enterprises become sustainable (Gladwin et al., 1995). But on rural tourism, the "green entrepreneur" or "ecopreneur", combining manage-ment with environmentalism, is calling to play an es-sential role. The development of environmental ser-vices provides business opportunities and environ-mentally sustainable options. Ecopreneurs are able to utilize green issues as a competitive advantage through energy and resource maximization, waste reduction, and utilization and respect of ecosystem services.

To explain the motivation and impacts of ecopreneurs, researchers have developed various typologies that explore the interplay between personal motivations and the influence of the economics and social structures within which they operate (Volery, 2002; Walley & Taylor, 2002). But it has been difficult to establish a profile of ecopreneur, their characteris-tics, and the differences with the others entrepreneurs (Weaver & Lawton, 2007).

In this context, this paper aims, firstly, to analyze how it integrates environmental perceptions of entre-preneurs in business management. This objective is studied through the construct and estimation of sev-eral latent factors related to various aspects of busi-ness management. In a second phase, it addresses the segmentation of entrepreneurs according to the struc-ture of relationships obtained, which may allow identi-fication of which factors are more related to an "ecopreneurial management".

Materials & Methods

To capture the environmental perceptions of rural tourism entrepreneurs and how it affect their manage-ment strategy, we use a questionnaire that identifies five latent variables: the perceived environmental im-pacts of activities, the importance of "green attitudes" of customers, the water saving goals, the efficient use of energy, and the management strategy [Table - 1].

The main purpose of this paper is to analyze the relationships between these latent variables to answer how the rural tourism entrepreneurs include the envi-ronmental concern in the business management strat-egy. For this aim, we propose four basic hypotheses:

H1: The environmental factor has a position influence on the customer factor.

H2: The water saving factor is influenced by the envi-ronmental variable (H2.1) and the customer factor (H2.2).

H3: The energy saving factor is influenced by the en-vironmental variable (H3.1) and the customer factor (H3.2).

H4: The managerial factor is influenced by the envi-ronmental factors (H4.1), the customer variable (H4.2), the water saving factor (H4.3) and the energy saving (H4.4).

To confirm these hypotheses we estimated a struc-tural model using partial least squares (PLS), as no initial assumption of normality in the variables is re-quired, there is no firmly established theory and this is a predictive research model of the effects of some vari-ables on others (Anderson & Gerbing, 1988; Barclay et al., 1995; Chin et al., 2003).

Our working assumptions were empirically tested on the basis of responses to the questionnaire given by rural tourism entrepreneurs in the Spanish region of Castilla-La Mancha. The choice of this geographic framework was based on the importance of rural tour-ism in the region as against more traditional tourism models (Gomez et al., 2007), and also on its close rela-tionship with its natural resources and landscapes (Mondejar et al., 2008).The entrepreneurs were se-lected at random, seeking to cover the widest possible spectrum as regards place of origin, age, sex, etc. The final number of questionnaires deemed valid once in-complete ones had been ruled out was 210.

In structural equation modelling with latent vari-ables is easy distinguishing between measurement and structural models and explicitly taking measurement error into account. The partial least squares (PLS) path modelling is a variance-based technique recommended in an early stage of theoretical development in order to test and validate exploratory models (Henseler et al., 2009). According to Barclay et al. (1995), using this covariance structure model allows the researcher to:

-Deal with the measurement errors. This is funda-mental when the variables of interest are latent and must be put into operation through others measurable variables.

- Model relations between multiple variables, both measurable and latent, and estimate direct and indirect effects.

- Combine a priori theoretical knowledge and hypotheses with empirical data. This facilitates the statistical confirmation of theories (so the models are more confirmatory than exploratory).

The PLS focuses on analyzing the relationships between the latent variables (inner model); however, latent variables are measured by means of a set of ob-served variables or indicators. In a reflective measure-ment model, the relationships between latent variables and its indicators (outer model) involve paths from the first one to the last ones. This technique is useful when concepts are abstract or when the current knowledge or data allows only imperfect empirical representations of them.

Results & Discussion

Accordingly, with the aim of carrying out a confir-matory factorial analysis, this study undertook an es-timation of a structural equation model showing the conformation of the covariance matrix, using the PLS method with the program SmartPLS 2.0.M3 (Ringle et al., 2005). For the measurement sub model we used the study's factorial structure, which allows us to decide which items are used as indicators of each latent vari-able (factor), as shown in [Figure - 1]. For the structural sub model, following the theoretical framework set out in the previous section, we establish the relationships indicated by the four hypotheses.The results obtained for the sub model bear out the choice of indicators. This outcome also constitutes a measure of the valid-ity of the questionnaire used to capture the five latent dimensions. The usual goodness of fit measure, pro-posed in Tenenhaus et al. (2005), is the geometric mean of the average communality (outer model) and the av-erage R2 (inner model), with a value of [0.4112].As to the reliability of the instrument of measurement, the Cronbach's alpha value for all the latent variables is acceptable (Nunnally & Berstein, 1994), as shown in [Table - 2]. The composite reliability indices are also greater than 0.5 in all cases.

As regards convergent validity (AVE), the values of all dependent constructs are greater than 0.25, (Fornell & Larcker, 1981). Likewise, the cross-loads are always greater for the latent variables on which the respective items are loaded. The discriminate validity criterion (Fornell & Larcker, 1981) is met, as for the five latent variables; the corresponding AVE is greater than the square of the estimated correlation between them: [Table - 3].

AVE_i > P_i²j

AVE_j > P_i²j

Regarding the structural sub model, as shown in [Table - 2], the R ² coefficients associated with latent vari-able regressions are significant, with values greater than 0.1 all cases (the acceptable value cited in Falk & Miller, 1992). An analysis of direct and overall effects, shown in [Table - 4]. highlights the dependence existing between the latent variables and tends to confirm the initial hypotheses for the model.To confirm the theo-retical assumptions, [Table - 5] shows the regression co-efficients between latent factors, estimated by PLS, their t-statistics and p-values. The eleven proposed relations have significant values, confirming the three basic hypotheses in its various concretions.

The assumption that all the entrepreneurs are single homogeneous population is often unrealistic. Identification of different groups in connection with estimates in the inner path model constitutes a critical issue for applying the path modelling methodology.To try to identify groups of entrepreneurs with similar

behaviour (that is, ecopreneurs segments) we use the FIMIX-PLS algorithm (Hahn et al., 2002), that com-bines a finite mixture procedure with an EM-algorithm (Jedidi et al., 1997). This approach permits reliable iden-tification of different tourists segments with their char-acteristic estimates for relationships of latent variables in the structural model.For choosing the appropriate number of segments, is usual to repeat, sequentially, the FIMIX-PLS procedure with consecutive numbers of latent classes, that are compared for criteria such as the lnLK , the Akaike Information Criterion (AIC), the AIC Controlled (CAIC), the Bayesian Information Cri-terion (BIC) or the normed entropy statistic (EN). The last criterion is a critical one for analyzing segment specific results (Ramaswamy et al., 1993).

In this paper, we applied the FIMIX-PLS module of SmartPLs 2.0 to segmentation. A comparison of the class-specific computations for heuristic evaluation criteria [Table - 6] reveals that the choice of three groups is appropriate.This result shows that there are three groups of entrepreneurs with different co-variance structure in the inner model. To explore this heterogeneity, firstly, we re-estimate the model for each group.As shown in [Table - 7]. the model is better adjusted for the three segments, especially in the sec-ond and third ones, with high values for the compos-ite reliability indices and the convergent validity (AVE).

The R ² coefficients associated with latent vari-able regressions are high in all cases except for the customer. An analysis of direct effects, shown in [Table - 8], highlights the dependence existing between the latent variables and allows answers why the groups differ.

Conclusion

This paper aims to analyze the integration of environment in management of rural tourism entrepreneurs. Through a questionnaire, we have put into operation five latent factors related to the environmental perception of the entrepreneurs, and we have estimated, by PLS, a model that reproduce the relationships between its. Eight of the nine proposed hypothesis has been confirmed by the empirical evidence, showing the importance of the environmental issues on business management in rural tourism. But the entrepreneurial response to these issues isn't the same. To identification the differences that characterize the three uncovered entrepreneurs segments, we conducted an ex post analysis and we reviewed several potential explanatory variables (Ramaswamy et al., 1993).

The first segment (48.25%) is composed mostly by entrepreneurs whose environmental concern primarily influences both saving factors, whereas it directs effect on management and customer factor is moderate. It is a type of entrepreneur whose environmental sensitivity leads to saving decisions and whose business management strategy is focused on an efficient use of the resources, especially the energy ones. For him, the environmental sustainability of your firm is to manage resources efficiently and minimize both their costs and their environmental impact. It is the "environmentally conscious entrepreneur".

The entrepreneurs of the second segment (33%) show an environmental awareness that pervades their entire management strategy. Not only saving factors, but the customer variable and the managerial factor (R ² = 0.947) are highly dependent on environmental concern. These entrepreneurs focus their activities on customers seeking environmentally sustainable tourism and value the entrepreneurial efforts to achieve that goal. Like the first group, they manage energy resources efficiently but, also, they design their business management from an ecological standpoint. For them, the environmental approach is a business opportunity and a source of competitiveness. They are the "green entrepreneurs" or "ecopreneurs".

Finally, the last segment (18.75%) is composed by entrepreneurs whose environmental concern influences solely on energy saving variable. Its environmental motivations unrelated to their customers ones and the management strategy isn't sensible to them: their actions aren't related with the environmental sustainability, but with the acquisition of customers and short term profits. They are the "environmental reactive entrepreneurs".

In summary, the entrepreneurial response to environmental issues is different. While environmental awareness is present in all rural tourism entrepreneurs, the degree of integration into the management is different: entrepreneurs that only responding to customer demands, other that only included the efficient management resources to minimize the environmental impact of their business, and ecopreneurs, that planning the entire management to achieving the environmental sustainability of their economic activities.^[28]

References

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