Case Study: The Spanish Wine Industry
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Description
This scholarly article assesses the elements of competitive advantage in the Spanish wine industry. Strategy, resources, capability, and managerial ability all affect a firm's competitive advantage.
Abstract
The wine sector in Europe has undergone a major change of trend in recent years, especially in Spain. On the one hand, the surface area has been reduced, but the production has been maintained by restructurings and improvements made in exploitation techniques.
On the other hand, consumption has diminished causing a significant increase in competition. The Spanish wine sector is formed mainly by small and medium-sized firm, which is representative of the size of existing companies in Europe. This article
aims to analyze the relationships between the competitive strategy, resources and capabilities of the firms, analyzing their technological and managerial capabilities, with business performance. 339 companies of the wine sector in Spain have been
studied, differentiating between individual firms, cooperatives and mercantile companies. The results reveal that resources and capabilities along with strategies define competitive advantage, but their relationship and importance is different for
each type of company.
Keywords
Competitive advantage; Resource based view; Strategy; Wine industry
Source: Juan Ramón Ferrer Lorenzo, María Teresa Maza Rubio, and Silvia Abella Garcés, https://www.econstor.eu/bitstream/10419/194554/1/1-s2.0-S2212977418300206-main.pdf
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
Introduction
In recent years, the wine sector has had an evolution marked by an increase in market competition. While wine production in the world was 267 million hectoliters (mhl) in 2016, consumption remained at 241 mhl that year. A more detailed analysis shows
that the difference between production and consumption is especially in countries that traditionally produce. For example, Italy, France and Spain, which together account for 50.0% of the world's wine production, have had a noticeable decline in consumption.
Production in 2016 in these countries was 50.9, 43.5, and 39.3 mhl, respectively, while their consumption, was 22.5, 27.0 and 9.9 mhl. This important difference between production and domestic consumption has changed the market for these countries,
which have started to export in order to sell their products in international markets. As a consequence, sales in the international wine market have grown from 60 mhl in 2000 to 104 mhl in 2016 (3.6% in volume per year) and from 12 to 29 billion (bn)
euros (5.9% in value per year). Spain, due to its greater differential between production and domestic consumption, has become the country with the largest volume of wine exports (22.9 mhl), although in value it ranks third, with 2.6 bn euros, behind
France and Italy, with 8.2 and 5.6 bn euros, respectively.
In this paper, the focus of analysis is centered on the factors that determine the firm's performance, using a sample of Spanish wineries.
Wineries in Spain have undergone an
important process of updating and renewal in recent years. It is estimated that since the year 2000, more than 130,000 ha have been reconverted and restructured, with investments of more than 800 million euros. There are 4052 wineries in Spain, which
are mainly small in size and are family owned businesses. Nevertheless, there are a significant number of agricultural cooperatives, which coexist alongside the large firms with production centers in different areas in order to diversify their supply.
All of them face the challenge of competitiveness. In this study, authors consider a cooperative an autonomous association of persons united to meet common economic, social, and cultural goals. In Spain (Ley 13/2013) cooperatives are considered the
following firms: cooperative societies, second-tier cooperatives, cooperative groups and agrarian transformation societies.
The analysis of the circumstances that allow for a superior performance, and the scope of a dominant position in the
competitive environment, has been studied from the point of view of two different approaches. The first one is centered in the characteristics of the sector, while the second one takes into account the resources of the firm. Several studies show that
these two approaches are complementary and compatible.
The review of the literature has allowed to find out that the majority of studies undertaken for the wine sector are focused on large companies, due to the fact that it is easier to access
information for these firms than for smaller ones, both in terms of objectives and results. The study of competitive advantages becomes difficult when the focus is placed on small and medium-sized enterprises, although they amount for about 99.8%
of the companies in the EU-27 and 99.9% in Spain, as shown in Table 1. In this study, size is determined by the number of employees.
Table 1. Number of companies according to employee stratum and total percentage of firms,
in Spain and the EU27, 2015.
| Micro (1-9)a | Small (10-49)a | Medium (50-249)a | SME (0-249)a | Large (≥250)a | Total | |
|---|---|---|---|---|---|---|
| Spain (Number of firms) | 2,984,727 | 107,784 | 18,011 | 3,110,522 | 3839 | 3,114,361 |
| Spain (% of firms) | 95.8 | 3.5 | 0.6 | 99.9 | 0.1 | 100 |
| UE-27 (% of firms) | 92.4 | 6.4 | 1.0 | 99.8 | 0.2 | 100 |
- a
-
Number of employees.
The main objective of this article is to empirically test how resources, capabilities and strategies modulate the results of companies. For doing so, this study analyzes the technological and managerial capabilities of the firm, its strategic positioning
and the business result in the market, as well as the financial result. The main contribution of this article is to analyze the distinct importance of resources and capabilities and strategy in the wine sector and how these vary according to the type
of company. This study considers three types of companies depending on ownership: 1) Individual companies, formed by a single person firm; 2) cooperatives, formed by cooperative societies, second-tier cooperatives, cooperative groups and agrarian
transformation societies; and 3) mercantile societies, which contemplate limited companies and corporations. The results show that resources capabilities and strategy do not have the same importance in all firms. In individual companies strategy prevails
over resources and capabilities. In cooperatives it is primarily technological capabilities that dominate performance. However, the wineries constituted as mercantile companies explain their performance by a combination of strategies, resources and
capabilities.
The paper is organized as follows: after this introduction, Section 2 presents the theoretical framework. Section 3 offers the theoretical foundation for the proposed hypotheses. In the following section, the methodology used is presented:
sample, variables, and the model to test the hypotheses. Section 5 reports the results of the analysis and the theoretical and practical implication. Section 6 shows the conclusions drawn from the results. And finally, Section 7 presents the limitations
and applicability of the study.
Theoretical framework
One of the objectives of this study is
to demonstrate that the competitive advantage of the company is
explained through two synergistic and compatible issues: the situation
in the environment of the company and its internal characteristics.
Authors have found literature where
the wine sector has been studied from the point of view of two different
approaches: strategy and resources and capabilities. But they have been
studied separately in the wine sector. So the main contribution of this
paper is to study the effect on performance of the two approaches but
applied together. In terms of strategy, research has been found about
the marketing strategy and performance in the French wine sector; in the USA wine industry, the studies are
centered on the relation between differentiation strategies and
performance. And in Spain, on the strategies,
environmental variables, and economic performance and the explanatory factors of performance in the wineries from Castilla-La Mancha. With respect to
the RBV and its link with better business performance, in the wine
sector, authors have found works focused on the internationalization
capacity in the Italian wine sector; on the link between intangible efforts and performance in
the French wine industry); in the Brazilian wine industry
research is focused on cluster resources and performance; and in the USA
wine sector on business performance and
knowledge.
In this section, the theoretical framework for the
study is presented. Firstly, Porter's frame and secondly, the resource
and capabilities theory, are revised as a proposal for the study of the
strategy.
Strategic advantage
According to Porter, the competitive position of an industry or sector, depends on
five forces and it is their joint action which determines an industry's
potential benefit. These forces are: barriers to entry, supplier power,
buyer power, the threat of substitutes, and the intensity of internal
rivalry. The objective of a company's strategic plan is to find a
position that allows it to better defend itself against these forces or
be able to influence them in its favor. After analyzing the forces and
how they emerge, the company's strengths and weaknesses can be
identified. Next, the company should be positioned to achieve the
competitive advantage by building defenses against the competitive
forces or looking for positions within the industry where these forces
are weaker. The firm can influence the balance of forces through
strategic moves. Two generic strategies allow for the pursuit of a
competitive advantage position: cost leadership or differentiation. But
there is another variable that defines the strategic positioning, and it
is the competitive area. The company must decide whether it serves the
entire market or focuses on a specific segment. Depending on the
decision taken, a third strategic option arises, which consists on using
one of the two generic strategies (costs or differentiation) but in a
given segment. Intermediate positions should not be adopted, as they
lead to a loss of competitiveness. Although Porter's approach has received some criticism, it remains a
reference in scientific papers and empirical studies. Critical
comments focus on the overly static nature of Porter's approach, and on
the fact that a company's real strategies have evolving components not
addressed by the theory. Others suggest that
cost positioning and differentiation are not equally beneficial for the
company, considering that differentiation is better than cost strategy.
Resources and capabilities
Distinctive
competencies, were the
conceptual precursor concept to resources and capabilities, which is to
say, the elements that belong to or are developed by the company and
allow it to generate greater incomes. This approach defines the company
as a set of productive resources that can be physical, intangible or
organizational.
The theory of Resources and
Capabilities, known as RBV (Resource Based View), focuses
on the resources and capabilities controlled by the firm as the
elements that confer competitive advantage.
Resources
are the stock of available factors that the company controls. These
become final products or services, using a wide range of other assets
and mechanisms such as technology, information systems, management
systems, incentive systems and mutual trust between managers and
employees. The term capabilities refers to the possibility of using
resources in combination, implementing organizational processes to
create the desired effect of having information, tangible or intangible
elements, and specific business processes that have been developed over
time, as well as complex interactions among available resources.
Resources and capabilities are not
strategic and fundamental unless they engender superior performance.
Grant refers to three conditions that can be considered
strategic: (1) establishing a competitive advantage, (2) sustaining the
competitive advantage, and (3) appropriating the returns of the
competitive advantage. The advantages achieved by the resources and
capabilities, depend not only on a company's ability to establish a
competitive advantage, but also on how long the company can sustain that
advantage. Durability is conditioned upon the possibility of
imitability. Resources and capabilities are imitable if they are both
transferable and replicable.
Although the RBV has received
criticism for insufficiently explaining business performance, it is indeed a driver of
performance as it enables the development of capabilities.
Hypotheses
Technological capabilities
It is impossible to deny the
importance of technology as an element that improves a company's
productivity. In highly competitive environments managers are required
to use the optimal technology for their company. In order
to determine which optimal technology is best, the company must study
its production processes. Therefore, introducing the most appropriate
technology, it should be able to reduce costs and increase quality. Through technology, the company creates
value, as well as the capacity for
development, specialization, and competitive advantage.
Therefore, technology is a key resource in maintaining the
competitive level of a company. Moreover, in the case of small
businesses and those linked to the land, as it is in the case of
wineries, they do not have the option of changing location easily, as
other kinds of firms do, in order to lower unit costs. Therefore,
wineries must maintain efficiency by investing in technology and
improving operations.
The importance of
technological resources has been linked to business performance and
studied by several authors, finding a positive relationship between
these variables.
According to these arguments the authors propose the following hypothesis:
H1
In the wine sector, the technological capabilities owned by the firm are positively related to the firm's performance.
Managerial capabilities
The importance of managerial
capabilities is based on the manager's vision and leadership. The
success of the firm will depend on its effectiveness, along with the
skills and knowledge of people working in the organization, who establish priorities and belief systems, and guide managers
and employees towards the shaping of business resources and competencies.
As part of the management competencies,
the definition of organizational structure and corporate strategy are
included, both in terms of design and implementation. Management skills
allow for the identification of the basic competences, communication to
the employees and the employees accepting these basic competences.
Managers must provide a high degree of commitment, clear definition of
objectives and adequate financial resources.
The
relationship between management capabilities and competitive advantage
is based on the successful guidance of managers implementing cost
reduction, product differentiation or a combination of both. Other key factors include the strategic vision of the
business and the internal communication: strategic management of human
resources, which includes recruitment, job analysis, development,
training, performance and compensation, and finally in the acquisition,
development and use of organizational resources, the conversion of these
resources into valuable products and services, and the delivery of
value to partners and owners of the company. This set of managerial
capabilities can become a generator of appropriable incomes and a source
of maintenance of competitive advantage. It
also helps explain the relationship between strategic decisions and
business performance.
The study of
managerial capabilities and their relation with the firm's performance
has been analyzed in many studies, finding a positively correlated link. So that
according to this, the authors propose the following hypothesis:
H2
In the wine sector, the management capabilities owned by the firm are positively related to the firm's performance.
Competitive strategies and business performance
Porter,
1980 and Porter and Strategy (1985) argues that the strategic choice of
the firm is the one that will determine its performance, avoiding
intermediate positions, a feeling of "stuck in the middle", that would
lead to a loss of competitive advantage. Cost leadership focuses mainly
on the production of low-cost products to satisfy price-sensitive
customers, specialization in certain
products and services, investment in reducing costs with technology and
equipment and use of distribution channels to reduce their costs. Differentiation focuses more on offering different and
unique products and services in the industry but to a wide range of
relatively price-insensitive customers,
having quality products, broad product lines, consumer service and an
efficient distribution system.
This analysis leads authors to propose the following hypotheses:
H3.1
In the wine sector, the companies that use a differentiation strategy will achieve a superior performance.
H3.2
In the wine sector, the companies with a cost-leadership strategy will achieve a superior performance.
Methodology
Sample
The definition of the sample universe is done through the combination of the following databases: Spain's existing public records in different protected designations of origin (DOP) and the information available in the database Iberian Balance Sheet Analysis
System (SABI), registered in year 2015 with CNAE (National Classification of Economic Activities) code 11.02 "Winery Companies".
The number of independent entities resulting from these databases was 3286. Following Spanos and Lioukas, the authors
dropped from the sampling frame firms with missing data, and the datum that resulted from a duplicate company with different location or brands without a formal structure. The total sample was then reduced to 2413 independent entities.
The
questionnaire was conducted after an extensive review of the literature, and scales validated in previous studies were used. It focuses on the resources and capabilities that have been collected by theoretical studies and on the analysis of the competitive
environment, business strategy and business performance. The questionnaire was also tested by previously sending it to various entities linked to the wine sector in Spain, associations, experts, as well as managers of wineries. The pretest was carried
out in two phases. First a pre-validation was made with four winery managers and four sector experts, and then, a second validation phase took place with nine managers and three sector experts. As a result, some issues were modified in the questionnaire
and the explanation of the different sections was expanded. The objective was to ensure that the questionnaire was understandable and that it reflected the peculiarities of the industry.
The process for collecting the data started in December
2015 and finished in May 2016. After sending the questionnaire via email to the manager of the different firms, the authors allowed for one month to receive an answer and if during that period it was not provided, a phone reminder was made. The final
sample was made up of 339 valid responses, which meant a 14.0% response rate, similar to the amount reported by Baruch and Holtom, for the industrial sector, so that we considered it appropriate for our study.
The sample characteristics are
given in , . Table 2 reports the distribution of the response percentages among the firm's type of ownership. With regard to the number of employees, its distribution percentages and the comparison with the mean of the sector is shown in Table 3.
Therefore, non-response bias does not seem to be a major concern because of the data similarity between responses and sector.
Table 2. Response percentages in reference to the type of ownership of the winery.
| Type of ownership | Individual companies | Cooperatives | Mercantile societies |
|---|---|---|---|
| Percentage | 14.7% | 17,2% | 68,1% |
| Micro (1-9 employees) | Small (10-49 employees) | Medium-sized (50-249 employees) | Large ( 250 and more employees) | |
|---|---|---|---|---|
| Responses | 79.3% | 18.0% | 2.7% | 0% |
| Sector | 83.1% | 14.4% | 2.3% | 0.2% |
The sampling error has been determined from the standard error of the mean, calculating the error committed for the case of finite populations resulting in a confidence level of 95% and
is 4.9%. So this error is acceptable, considering
the results from other studies, such as Camisón and Villar-Lopez (2014) who obtain an error of 7.6%; or Ortega, with an error of 5.7%.Variables
Variables have been grouped into the following
categories, 1) independent: technology, management capabilities,
business strategy, and control variables, 2) dependent: performance.
In
the realm of resources and capabilities, both technological and
managerial capabilities have been analyzed and realized following the
criterion that focuses on both the importance of competitive advantage
and its sustainability.
In the
research process, multi-item five-point Likert scales have been used for
resources and capabilities, strategy and performance.
To measure
resources and capabilities, the scale used is adapted from Ortega
and Spanos and Lioukas. Technological capabilities are evaluated
with four items. Managerial capabilities are analysed using seven
indicators. Both variables are measured with a 5-point Likert scale,
where companies evaluate their position with respect to their
competitors and where the values of the scale are classified from 1
"much weaker than the competitor" to 5 "much stronger than the
competitor". Authors adopted indicators used in other similar studies,
not specific to the wine industry, in order to facilitate the comparison
between sectors, they were previously validated by wine industry
experts.
In strategy, one of the models that has been used to try
to capture the typology of the competitive strategy, is the model
developed by Robinson and Pearce, and it has been used in
different studies. This
model was developed based on previous studies by Dess and Davis,
and aims to expand the generic strategies of Porter, 1980 facilitating
their characterization in empirical business studies.
This
business strategy model consists of 22 indicators assessed with a
5-point Likert scale, where companies evaluate themselves with respect
to different business development efforts, from 1 "is not utilized" to 5
"is primary, constantly utilized".
Following Ortega and
Spanos and Lioukas, the authors have evaluated business
performance with seven indicators grouped into two dimensions: market
position and profitability, in the last three years. The first dimension
shows the external performance of the company, evaluated by its
behavior in the market through four items. The second dimension reflects
the internal performance of the company, the income generated in its
economic activity, through three items. All
the items use a 5-point Likert scale, where companies evaluate their
position with respect to their competitors, and where the values of the
scale are rated from 1 "is much weaker than the competitor" to 5 "is
much stronger than the competitor".
Subjective scales are used
instead of objective scales, due to two reasons. First, the literature
has demonstrated the validity of subjective scales to determine business
performance and their convergent validity with objective scales. Second, accounting data could be
subject to annual variability and may include extraordinary results and
movements outside the main activity of the company. Thus, several studies have used subjective instead of objective
scales to analyze business performance.
Model
In order to determine the relationships between the firm's resources and capabilities, the strategy used, and its performance, this study uses the hierarchical regression method.
In order to adapt the study to the different types of entrepreneurial
property that exist in the wine industry in Spain, this study makes three different analyses for the three types of ownership considered: individual companies, cooperatives and mercantile societies. Table 4 reports the distribution of the sample according
to the classification made and the wine produced by the companies that answer this question in the questionnaire.
Table 4. Distribution of the different types of ownership studied and the total amount of wine produced by them.
| Type of winery | Question: Wine production of the company in hectoliters | |
|---|---|---|
| Responses | Total hectoliters | |
| Individual Companies | 44 | 44,365 |
| Cooperatives | 52 | 4,629,623 |
| Mercantile Societies | 205 | 1,882,687 |
| Total | 301 | 6,556,675 |
| Spanish wine production in 2015 (OIV, 2016) | 37,300,000 | |
| Percentage of wine produced by the companies included in the survey over total Spanish wine production | 17.6% | |
Dependent variable
In this paper model the dependent variable is the business performance. This study works under the hypothesis that performance is determined by technological and managerial capabilities, and strategic positioning. The authors have studied the business performance from two approaches, market and finance. , show the answers to the different questions and their frequency.| Market | Much Below | Below | Average | Above | Far above | Total | |
|---|---|---|---|---|---|---|---|
| Sales volume €. | n | 40 | 83 | 129 | 71 | 10 | 333 |
| % | 12.0 | 24.9 | 38.7 | 21.3 | 3.0 | 100.0 | |
| Growth in sales volume €. | n | 26 | 58 | 131 | 103 | 15 | 333 |
| % | 7.8 | 17.4 | 39.3 | 30.9 | 4.5 | 100.0 | |
| Market share, % over sales €. | n | 41 | 75 | 142 | 67 | 8 | 333 |
| % | 12.3 | 22.5 | 42.6 | 20.1 | 2.4 | 100.0 | |
| Growth in market share, over sales €. | n | 24 | 59 | 152 | 83 | 13 | 331 |
| % | 7.3 | 17.8 | 45.9 | 25.1 | 3.9 | 100.0 |
| Financial | Much Below | Below | Average | Above | Far above | Total | |
|---|---|---|---|---|---|---|---|
| Profit margin. | n | 18 | 90 | 147 | 68 | 11 | 334 |
| % | 5.4 | 26.9 | 44.0 | 20.4 | 3.3 | 100.0 | |
| Return on own capital. | n | 28 | 85 | 147 | 62 | 10 | 332 |
| % | 8.4 | 25.6 | 44.3 | 18.7 | 3.0 | 100.0 | |
| Net profits. | n | 23 | 103 | 130 | 67 | 10 | 333 |
| % | 6.9 | 30.9 | 39.0 | 20.1 | 3.0 | 100.0 |
In order to get a nicely compact representation of the dataset, instead of the original with many variables, this study develops a principal component analysis (PCA), and then the study uses the new component to develop a hierarchical regression.
The principal component analysis is made with the selection of one component, that determines the concept of performance in the firm. The extracted factor explains 66.78% variance, with a KMO = 0.84, Cronbach's alpha = 0.917 (Table 7).
| Variables | Alpha without item | Component | Communality |
|---|---|---|---|
| Profitability. Net profits | .902 | .836 | .698 |
| Market position. Sales volume € | .903 | .828 | .686 |
| Market position. Market share % | .904 | .820 | .672 |
| Market position. Growth in market share | .903 | .820 | .672 |
| Market position. Growth in sales volume € | .905 | .813 | .661 |
| Profitability. Profit margin | .906 | .807 | .652 |
| Profitability. Return on own capital | .908 | .796 | .634 |
| Cronbach alpha of the whole scale | .917 | ||
| % Total explained variance | 66.783 | ||
| K.M.O. | .840 | ||
| Barlett Test: | x2 | 2020.509 | |
| gl | 21 | ||
| sig | 0.000 |
Independent variables
Technological capabilities
The four indicators used for technological capabilities, their distribution and values are shown in Table 8.| Much weaker | Weaker | Equal | Stronger | Much stronger | Total | ||
|---|---|---|---|---|---|---|---|
| Technological capabilities and equipment | n | 44 | 75 | 128 | 73 | 17 | 337 |
| % | 13.1 | 22.3 | 38.0 | 21.7 | 5.0 | 100.0 | |
| Efficient and effective production department | n | 18 | 72 | 139 | 91 | 16 | 336 |
| % | 5.4 | 21.4 | 41.4 | 27.1 | 4.8 | 100.0 | |
| Economies of scale | n | 59 | 105 | 100 | 59 | 12 | 335 |
| % | 17.6 | 31.3 | 29.9 | 17.6 | 3.6 | 100.0 | |
| Technical experience | n | 12 | 43 | 127 | 122 | 32 | 336 |
| % | 3.6 | 12.8 | 37.8 | 36.3 | 9.5 | 100.0 |
In order to introduce the variable in the linear regression model and to avoid multicollinearity, this paper performed the technique of principal component analysis. One extracted factor explains 57.9% of variance, KMO = 0.71, and Cronbach's alpha = 0.751 (Table 9). The component has been called "technological capability".
| Variables | Alpha without item | Component | Communality |
|---|---|---|---|
| Efficient and effective production department. | .613 | .864 | .746 |
| Technological capabilities and equipment. | .709 | .741 | .549 |
| Economies of scales. | .715 | .725 | .525 |
| Technical experience. | .728 | .704 | .496 |
| Cronbach alpha of the whole scale | .751 | ||
| % Total explained variance | 57.914 | ||
| K.M.O. | .713 | ||
| Barlett Test: | x2 | 339.887 | |
| gl | 6 | ||
| sig | .000 |
Managerial capabilities
The seven indicators used for managerial capabilities, their distribution and values are shown in Table 10.| Much weaker | Weaker | Equal | Stronger | Much stronger | Total | ||
|---|---|---|---|---|---|---|---|
| Managerial competencies. | n | 11 | 48 | 188 | 73 | 16 | 336 |
| % | 3.3 | 14.3 | 56.0 | 21.7 | 4.8 | 100.0 | |
| Knowledge and skills of employees. | n | 6 | 23 | 172 | 108 | 24 | 333 |
| % | 1.8 | 6.9 | 51.7 | 32.4 | 7.2 | 100.0 | |
| Work climate. | n | 6 | 9 | 133 | 142 | 41 | 331 |
| % | 1.8 | 2.7 | 40.2 | 42.9 | 12.4 | 100.0 | |
| Efficient organizational structure. | n | 9 | 30 | 177 | 95 | 21 | 332 |
| % | 2.7 | 9.0 | 53.3 | 28.6 | 6.3 | 100.0 | |
| Coordination. | n | 9 | 31 | 167 | 106 | 19 | 332 |
The seven indicators have been reduced following the principal component analysis. Then the new component has been used to develop a hierarchical regression. Resulting one factor that explains 61.6% of the variance with KMO = 0.87, and Cronbach's alpha = 0.895 (Table 11). The component is called "managerial capability".
| Variables | Alpha without item | Component | Communality |
|---|---|---|---|
| Strategic planning | .873 | .832 | .692 |
| Efficient organizational structure. | .875 | .824 | .678 |
| Coordination. | .876 | .818 | .669 |
| Ability to attract creative employees. | .883 | .773 | .597 |
| Work climate. | .883 | .766 | .586 |
| Knowledge and skills of employees. | .882 | .765 | .585 |
| Managerial competencies. | .889 | .717 | .514 |
| Cronbach alpha of the whole scale | .895 | ||
| % Total explained variance | 61.650 | ||
| K.M.O. | .870 | ||
| Barlett Test: | x2 | 1243.602 | |
| gl | 21 | ||
| sig | .000 |
Business strategy
In order to manage the main indicators of the firm's strategy, principal component analysis has been used. In Table 12 the components obtained from the analysis can be seen.| Variables | Alpha without item | Comp. 1 | Comp. 2 | Comp. 3 | Comp. 4 | Comp. 5 | Communality |
|---|---|---|---|---|---|---|---|
| Extremely strict product quality control procedures. | .870 | .704 | .059 | .100 | -.243 | .136 | .587 |
| Specific efforts to insure a pool of highly trained, experienced personnel. | .866 | .665 | .278 | .207 | -.023 | -.005 | .562 |
| Continuing, overriding concern for lowest cost per unit. | .871 | .649 | .062 | .132 | .323 | -.048 | .549 |
| Major effort to ensure availability of raw materials. | .870 | .643 | .254 | -.071 | .113 | .025 | .496 |
| Extensive customer service capabilities. | .871 | .565 | .015 | .368 | -.149 | -.043 | .479 |
| Maintaining high inventory levels (disregard the derivative of the aging of the product). | .870 | .535 | .189 | .007 | .250 | .260 | .452 |
| Concerted effort to build reputation within industry. | .865 | .518 | .240 | .384 | -.269 | .293 | .632 |
| Building brand identification. | .867 | .489 | .400 | .236 | -.233 | .106 | .521 |
| Developing and refining existing products. | .867 | .474 | .207 | .322 | -.210 | .306 | .510 |
| Promotion/advertising expenditures above the industry average. | .869 | -.012 | .826 | .148 | .158 | .043 | .732 |
| Major expenditure on production process oriented R&D. | .865 | .281 | .766 | .063 | .092 | .130 | .695 |
| Innovation in marketing techniques and methods. | .866 | .204 | .742 | .226 | -.058 | .015 | .647 |
| Strong influence over distribution channels. | .865 | .299 | .659 | .223 | .129 | .057 | .593 |
| Innovation in manufacturing process. | .864 | .385 | .443 | .341 | .005 | .253 | .525 |
| New product development. | .868 | .164 | .241 | .790 | .127 | -.093 | .733 |
| Broad product range. | .870 | .207 | .240 | .727 | .262 | -.273 | .772 |
| Emphasis on the manufacturing of speciality products. | .869 | .139 | .200 | .680 | -.209 | .247 | .627 |
| Products in higher priced market segments. | .872 | .143 | .196 | .471 | -.438 | .404 | .635 |
| Pricing below competitors. | .882 | -.075 | .105 | .060 | .796 | .129 | .670 |
| Products in lower priced market segments. | .879 | .072 | .125 | -.023 | .786 | .086 | .647 |
| Small limited range of products. | .879 | .203 | .027 | -.249 | .056 | .773 | .705 |
| Only serve specific geographic markets. | .876 | -.009 | .106 | .158 | .177 | .715 | .579 |
| Eigen value | 6.767 | 2.275 | 1.783 | 1.419 | 1.103 | ||
| % Explained variance | 30.758 | 10.339 | 8.107 | 6.448 | 5.013 | ||
| Cronbach's alpha of whole scale: | .875 | ||||||
| % Total explained variance | 60.663 | ||||||
| Average K.M.O. | .862 | ||||||
| Bartlett Test | |||||||
| x2 | 2557.814 | ||||||
| gl | 231 | ||||||
| Significance | 0.000 |
In this case, five components have been extracted, 1) Efficiency, 2) Marketing, 3) Innovation, 4) Low Price, and 5) Small Market and Product. The set explains 60.66% of the variance. The results of the different statistical reliability have values within the limits of acceptability, Cronbach's alpha = 0.875 and KMO = 0.862.
Efficiency strategy: Nine issues out of the twenty defined by Robinson and Pearce, are part of this first extracted component, accounting for 30.8% of the variance. Efficiency Strategy contains concepts that lead the company to the extreme care of the products offered to the customer and ensure the realization of an efficient process including: strict quality control, trained and experienced staff, encourage available raw materials, improve cost per unit, high level of inventory, customer service, promote reputation in the industry, brand identification and development of existing products. It is important to state that in this sector, the high level of inventory is relevant, as the development of aged products through aging and reserves generate higher added value.
Marketing strategy: In this second component five questions explain 10.3% of the variance. They are: advertising spending above sector average, investment in R&D oriented to efficiency process, innovations in marketing, strong influence over distribution and innovation in productive process. In this area business managers are concerned about trends and about controlling their various marketing techniques as a strategy to achieving their success.
Innovation strategy: The variance explained by the extracted component is 8.1% and its four questions are: development of new products, wide range of products, emphasis on special products and high-price segment. In innovation strategy what prevails is the obtaining of new items and the ability to offer the market a new and special range of products with a certain orientation towards a greater perceived benefit by customers.
Low price strategy: Two variables characterize this factor and explain 6.4% of the variance they point in a clear direction for offering products with less perceived benefit, a price below competitors and focusing on the low price products segment.
Small market and product strategy: This component refers to those companies that choose to compete through a strategy of limited or specialized products, more oriented to high rather than low prices and to a very specific segment. The total variance explained in this case is 5.0%.
Cost strategy and differentiation strategy. Porter's generic strategies: In the design of the hypothesis for the theoretical analysis of the strategic options, authors have adopted Porter's model (1980 and 1985), and its two generic strategies: cost or differentiation. However, our factor analysis reveals five different strategies: efficiency, marketing, innovation, low prices, small market and product strategy. The efficiency strategy refers to the maximum control of resources and is part of Porter's overall strategy of costs. The innovation strategy contemplates offering better products with greater added value to the customers and is part of the differentiation strategy. The marketing strategy is a strategy that is used by both generic strategies and contemplates the sensitivity to the market and its adaptation to changes, brand image and control of distribution. The low-price strategy has been assigned to a cost strategy and a small market and product strategy, which refer to Porter's third focus strategy. Table 13 shows the relation between the extracted strategies and Porter's generic strategies.
| Strategies extracted | Porter's generic strategies |
|---|---|
| Efficiency Strategy | Cost Strategy |
| Low Price Strategy | |
| Innovation Strategy | Differentiation Strategy |
| Small Market and Product Strategy | Focus Strategy |
| Marketing Strategy | No assignation, the study maintains as Marketing Strategy |
Control variables
The purpose of the study is to determine the relationship between business performance and the set of independent variables that have been defined. However, numerous studies refer to the influence on performance of elements such as company size and the degree of rivalry. In the Italian wine industry Sellers and Alampi-Sottini have found a positive correlation with the influence of size in a winery's performance by studying the size of the company, with the number of employees, total turnover and volume of assets. Therefore, most of the studies include control variables that help to better understand the business result. In this study authors will take the size of the company and level of rivalry within the sector as control variables. The size of the company will be measured in terms of its assets, divided into seven categories, ranging from less than 400 thousand euros to more than 20 million euros. Other studies take the number of employees or its logarithm. In this case, authors have opted for assets due to the extremely seasonal nature of wine production and the resulting distortion figures produced. Table 14 reports the distribution of the assets in the sample.| Type of winery studied and volume of assets in millions of euros. | Individual companies | Cooperatives | Mercantile companies | Total | ||||
|---|---|---|---|---|---|---|---|---|
| n | % | n | % | n | % | n | % | |
| < 0.4 million | 30 | 63.8% | 6 | 11.5% | 62 | 29.8% | 98 | 31.9% |
| 0.4 - 1 million | 6 | 12.8% | 12 | 23.1% | 51 | 24.5% | 69 | 22.5% |
| 1-5 million | 11 | 23.4% | 21 | 40.4% | 65 | 31.3% | 97 | 31.6% |
| 5-10 million | 0 | 0.0% | 10 | 19.2% | 15 | 7.2% | 25 | 8.1% |
| 10-20 million | 0 | 0.0% | 0 | 0.0% | 8 | 3.8% | 8 | 2.6% |
| 20-40 million | 0 | 0.0% | 2 | 3.8% | 4 | 1.9% | 6 | 2.0% |
| > 40 million | 0 | 0.0% | 1 | 1.9% | 3 | 1.4% | 4 | 1.3% |
| Total | 47 | 100.0% | 52 | 100.0% | 208 | 100.0% | 307 | 100.0% |
| No responses | 32 | |||||||
The degree of intensity of rivalry has been measured with the scale used by Ortega and Spanos and Lioukas. The manager of the firm evaluates the level of competition with a 5-point Likert scale which evaluates the characteristics of the product, promotion strategies, access to distribution channels and customer service strategy. The extracted factor explains 69.2% of variance, KMO=0.80, and Cronbach's alpha=0.85 (Table 15). The component has been called "internal rivalry".
| Variables | Alpha with out item | Component | Communality |
|---|---|---|---|
| Promotional strategies among rivals. | .785 | .874 | .768 |
| Service strategies to customers. | .808 | .843 | .711 |
| Access to distribution channels. | .812 | .839 | .709 |
| Product characteristics. | .846 | .769 | .599 |
| Cronbach alpha of the whole scale | .850 | ||
| % Total explained variance | 69.266 | ||
| K.M.O. | .805 | ||
| Barlett Test: | Chi-squared | 574.787 | |
| gl | 6 | ||
| sig | .000 |
Proposed model
The proposed model of analysis is as follows:
Where,
is the performance value for the company "
";
is the constant; 
, and 
, the coefficients of the control variables: internal rivalry and assets; 
, 
, 
, 
, 
, the coefficients of the variables efficiency, marketing, innovation, low price and small
market and product. 
and 
, are the coefficients for the resources and capabilities of the firm: technology and managerial capabilities. And ej is the error or the residual of the proposed model.The variables chosen to build the multivariable linear correlation, the mean values, standard deviation, Cronbach's alpha without item and correlation matrix, are shown in Table 16. The Cronbach alpha of the whole scale is 0.635. The study evaluates the possible multicollinearity between the variables through FIV and conditioning index, in both cases the values are lower than ten, as recommended by the literature.
| Mean | SD | Cronbach's Alpha Without Item | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| (1) Internal Rivalry | 0 | 1.00 | .637 | 1 | |||||||||
| (2) Assets | 2.38 | 1.30 | .582 | .100 | 1 | ||||||||
| (3) Efficiency Strategy | 0 | 1.00 | .620 | .190** | .133* | 1 | |||||||
| (4) Marketing Strategy | 0 | 1.00 | .601 | .072 | .300** | .000 | 1 | ||||||
| (5) Innovation Strategy | 0 | 1.00 | .640 | .143* | .133* | .000 | .000 | 1 | |||||
| (6) Low Price Strategy | 0 | 1.00 | .655 | -.087 | .187** | .000 | .000 | .000 | 1 | ||||
| (7) Small Market and Product Strategy | 0 | 1.00 | .671 | .017 | -.026 | .000 | .000 | .000 | .000 | 1 | |||
| (8) Technological Capability | 0 | 1.00 | .541 | .120* | .434** | .306** | .448** | .074 | -.014 | .036 | 1 | ||
| (9) Managerial Capability | 0 | 1.00 | .572 | .164** | .204** | .308** | .347** | .185** | -.148* | .103 | .482** | 1 | |
| (10) Performance | 0 | 1.00 | .549 | .037 | .360** | .251** | .449** | .226** | .048 | .025 | .550** | .412** | 1 |
- ** The correlation is significant at the 0.01 level (bilateral).
- * The correlation is significant at the 0.05 level (bilateral).
The model has been run with SSPS v20 program with the introduction hierarchical method.
Results
The
values, or the adjusted coefficient of regression, are different for
each of the three studies and they vary from 0.260 for cooperatives (
), the lowest value, to 0.435 for individual wineries (
), and
0.462 for mercantile wineries (
). These values were also found in
other comparable studies, for example, 0.390; 0.279, and suggest that the model provides
sufficient information to draw conclusions.
Results for individual companies
The results of the regression for individual companies are shown in Table 17, in order to establish conclusions the significance level is set at 0.05. The adjusted has a value of 0.435 in the full model and shows the overall significance. Thus,
the study infers that the winery's strategies have greater impact on performance than its resources and capabilities. The marketing strategy appears as the first fundamental strategy with a beta value of 0.435, followed by the efficiency strategy
with a beta value of 0.336. Authors find that neither resources and capabilities nor the control variables explain performance. With regard to hypotheses 1 and 2, they both have to be rejected for individual companies. Both strategies, marketing and
efficiency, allow individual companies to perform well. Marketing is neutral relative to cost positioning or differentiation, while efficiency is a cost strategy. The other strategies have no statistical significance. These results lead us to reject
hypothesis 3.1 and confirm 3.2 for individual companies.
Table 17. Regression analysis for individual companies.
| Variables | Base model | Base model + strategy | Full model | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| β | t | sig | sd | β | t | sig | sd | β | t | sig | sd | |
| (1) Internal Rivalry | 0.005 | 0.032 | 0.975 | 0.135 | -.107 | -.697 | .491 | .132 | -.184 | -1.191 | .244 | .137 |
| (2) Assets | 0.200 | 1.272 | 0.211 | 0.173 | .111 | .861 | .396 | .149 | -.005 | -.033 | .974 | .160 |
| (3) Efficiency Strategy | .440 | 2.895 | .007 | .133 | .336 | 2.112 | .044 | .138 | ||||
| (4) Marketing Strategy | .551 | 4.166 | .000 | .125 | .435 | 2.936 | .007 | .142 | ||||
| (5) Innovation Strategy | .211 | 1.613 | .117 | .111 | .196 | 1.542 | .134 | .110 | ||||
| (6) Low Price Strategy | -.041 | -.307 | .761 | .124 | .029 | .208 | .837 | .131 | ||||
| (7) Small Market and Product Strategy | .061 | .448 | .657 | .146 | .040 | .302 | .765 | .144 | ||||
| (8) Technological Capability | .153 | .729 | .472 | .182 | ||||||||
| (9) Managerial Capability | .241 | 1.239 | .226 | .148 | ||||||||
| R2 | 0.040 | 0.511 | 0.572 | |||||||||
| Adjusted R2 | -0.009 | 0.401 | 0.435 | |||||||||
| Change in R2 | 0.410 | 0.034 | ||||||||||
Results for cooperatives
In Table 18 the study reports the regression values for cooperatives. To establish conclusions the significance level is set at 0.05. The adjusted has a value of 0.260 in the full model and shows the overall significance. The results show that
the control variable "internal rivalry" has the highest beta value (0.502) and a high significance level (0.012). With regard to strategies, there are none that explain performance, however the authors find a negative value for the innovation strategy,
with a significance level of 0.049. In terms of resources and capabilities in relation to performance, technological capabilities has a beta value of 0.414 and a statistical significance of 0.022, the managerial capabilities variable is not statistically
significant. Thus, for cooperatives, the study confirms hypothesis 1 but rejects hypothesis 2, 3.1 and 3.2.
Table 18. Regression analysis for cooperative wineries.
| Variables | Base model | Base model + strategy | Full model | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| β | t | sig | sd | β | t- | sig | sd | β | t- | sig | sd | |
| (1) Internal Rivalry | .173 | 1.200 | .237 | .109 | .345 | 1.732 | .092 | .152 | .502 | 2.662 | .012 | .143 |
| (2) Assets | .284 | 1.967 | .056 | .092 | .207 | 1.252 | .219 | .104 | .171 | 1.084 | .286 | .115 |
| (3) Efficiency Strategy | .099 | .589 | .559 | .108 | -.176 | -1.007 | .321 | .112 | ||||
| (4) Marketing Strategy | .053 | .298 | .768 | .153 | .047 | .318 | .753 | .150 | ||||
| (5) Innovation Strategy | -.121 | -.663 | .512 | .148 | -.400 | -2.051 | .049 | .159 | ||||
| (6) Low Price Strategy | .104 | .624 | .537 | .158 | -.005 | -.030 | .977 | .146 | ||||
| (7) Small Market and Product Strategy | .233 | 1.455 | .155 | .148 | .228 | 1.497 | .144 | .141 | ||||
| (8) Technological Capability | .414 | 2.402 | .022 | .169 | ||||||||
| (9) Managerial Capability | .200 | 1.231 | .227 | .148 | ||||||||
| R2 | 0.126 | 0.238 | 0.423 | |||||||||
| Adjusted R2 | 0.086 | 0.086 | 0.260 | |||||||||
| Change in R2 | 0 | 0.174 | ||||||||||
Results for mercantile companies
The results for mercantile companies are reported in Table 19, in order to establish conclusions the significance level is set at 0.05. The adjusted has a value of 0.462. The most important element to explain performance in this type of winery,
is technological capabilities, with the highest beta value of the study (0.460), followed by the strategy with a beta value of 0.273 for marketing strategy, and 0.229 for innovation strategy. The other strategies and resources have a low beta value
and have no statistical significance. With regard to our hypotheses, it is possible to confirm H1 and reject H2. As authors have explained, marketing strategy is useful and it does not depend on how the firm behaves in terms of cost or differentiation.
On the other hand, the innovation strategy is linked with the differentiation strategy. Thus, it is possible to confirm H3.1 and reject H3.2. Assets as a control variable has statistical significance in the two first models (Base Model and Base Model
+ Strategy).
Table 19. Regression analysis for mercantile companies.
| Variables | Base Model | Base Model + Strategy | Full Model | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| β | t | sig | sd | β | t | sig | sd | β | t | sig | sd | |
| (1) Internal Rivalry | -.034 | -.498 | .619 | .075 | -.074 | -1.141 | .256 | .073 | -.094 | -1.596 | .113 | .066 |
| (2) Assets | .386 | 5.649 | .000 | .054 | .157 | 2.201 | .029 | .057 | .023 | .336 | .737 | .054 |
| (3) Efficiency Strategy | .173 | 2.651 | .009 | .081 | .077 | 1.238 | .217 | .077 | ||||
| (4) Marketing Strategy | .455 | 6.544 | .000 | .077 | .273 | 3.717 | .000 | .082 | ||||
| (5) Innovation Strategy | .236 | 3.576 | .000 | .074 | .229 | 3.741 | .000 | .069 | ||||
| (6) Low Price Strategy | -.012 | -.182 | .856 | .078 | .030 | .489 | .626 | .074 | ||||
| (7) Small Market and Product Strategy | .013 | .199 | .842 | .066 | .002 | .033 | .973 | .060 | ||||
| (8) Technological Capability | .460 | 5.804 | .000 | .083 | ||||||||
| (9) Managerial Capability | -.003 | -.040 | .968 | .091 | ||||||||
| R2 | .148 | .363 | .493 | |||||||||
| Adjusted R2 | .139 | .334 | .462 | |||||||||
| Change in R2 | .195 | .128 | ||||||||||
Global results
The results of the model, try to explain
business performance for the three types of companies studied for the
Spanish wine sector, present differentiated elements. The relationship
between resources and capabilities is evident, along with the strategy
with the business result, but this varies depending on the type of
company.
Regarding the influence of resources and capabilities
(technological and managerial capabilities), only the technological one
shows its importance in the explanation of the company's performance,
but only for cooperatives and mercantile companies. Several authors have
highlighted the importance of resources or technology to explain the
best organizational performance capabilities. However, our results show that
technological capabilities have no influence on the performance of
individual companies, nor are management capabilities relevant in any of
the types of the companies analyzed. It is important to highlight that
the fact that a resource does not give an explanation of the business
result, does not mean that it is not important in the industry, it only
means that it is not an explanatory variable of the competitive
advantage, the resources must be scarce, relevant, durable,
non-transferable and non-replicable.
In relation to
strategy, the results show that it explains the business result for the
individual companies and for the mercantile companies, not being
related to the performance as in the case of cooperatives. Of the five
types of strategies analyzed and extracted by the technique of principal
components, from the scale of Robinson and Pearce, only three
are significant with business performance: in the case of the individual
companies marketing strategy and efficiency strategy; and for the
mercantile companies marketing strategy and innovation strategy, are the
drivers of the performance.
With regard to the joint effect of
resources and capabilities, and the strategy, and its synergistic effect
to explain business performance, the results
show that only in mercantile companies has this effect appeared, being
the combination of technological capabilities, and marketing and
innovation strategies, the elements that correlate with the best
business results. This synergic factor does not appear in individual
companies, where it is only the strategy that is seen as the driver of
the performance and neither is it seen in cooperatives where the
technological capabilities are the explanation of their better
performance.
The relationship between resources and capabilities,
and strategy, can be observed in the values of the correlation matrix,
without distinguishing according to the type of company. Thus, among the
strategies related to the best performance (efficiency, marketing and
innovation), and the resources and capabilities studied, it presents the
following values. The efficiency strategy has a correlation of 0.306
with technological capabilities and 0.308 with management capabilities.
Marketing strategy 0.448 with technological capabilities and 0.347 with
management. And the innovation strategy does not have a significant
correlation with technological capabilities and 0.185 with management
capabilities.
Conclusions
The purpose of this document is to assess the
factors on which business success is based within the wine industry in
Spain. For this analysis, the authors combined the theories of resources
and capabilities and strategic positioning, following previous studies. The basic hypothesis is that both
theories are not contradictory, but coexist within the business reality,
and that both can at least partially explain the defining factors of
business success. Analysis has focused the study on the Spanish wine
sector, a sector characterized by the presence of a large number of
small and medium-sized companies, which faithfully reflects the reality
of businesses in Spain, Europe and the global world. To adapt the study
to the Spanish wine industry, the authors have differentiated between
three types of wineries: individual, cooperative and mercantile, and the
authors evaluate the importance of resources, capabilities and
strategy.
In this document, the authors analyze technological
capabilities and managerial capabilities as two of the resources and
capabilities that business literature identifies as key resources. This
study has evaluated the strategic positioning with the scale developed
by Robinson and Pearce.
The first conclusion that can be
drawn from the results obtained shows that the existence of the synergic
effect of resources and capabilities with strategies, has only been
corroborated in mercantile companies. This effect has not been found in
individual companies (where strategies explain their business
performance), nor in cooperatives (where the resources explain their
business performance). On the other hand, the general values of
significant correlation found between the explanatory strategies of
performance (efficiency, marketing and innovation) with the resources
and capabilities studied (technology and management), prove that
resources and capabilities affect the strategies, or that strategies are chosen depending on the resources
the company controls. These results are in line
with the concept of strategy formation defined by Barney et al.,
considering that the ability to implement the strategy is in itself a
resource capable of providing a sustainable strategic advantage.
The
second conclusion in the field of resources and capabilities is that
technological capabilities are much more important than management
capabilities, although this element has not been proven for individual
companies, where resources and capabilities do not explain their
business performance.
With respect to strategic positioning, the
results present a more complex configuration. For individual companies,
strategy is the key element in the explanation of business success,
first marketing strategy and then efficiency strategy. From the analysis
of Porter's generic strategies, Table 13, individual companies
achieve better business performance with generic cost strategy. However,
in mercantile companies, they are the marketing and innovation
strategies that explain their performance, and from the perspective of
Porter's analysis, mercantile companies achieve better business
performance in a generic differentiation strategy, Table 13.
In
the case of the cooperatives, no strategic positioning directly related
to performance has been detected, however, a control variable has
appeared, the internal competence of the sector, as an explanatory
element for a better performance. This analysis is in line with Porter's
theories on competitive advantage, where he defends that a high
level of competition in a sector is a driver of a better behavior on the
part of the companies.
Limitations of the study and its applicability
The objective of this article was to determine empirically the factors influencing a company's competitiveness, within the Spanish wine sector. Two approaches, RBV and strategic positioning, have been introduced and evaluated in previous studies that
support their mutual compatibility. The results demonstrate this fact: resources and capabilities and strategy explain a company's performance, confirming previous studies. In the present
study, resources and capabilities have emerged as being equally relevant relative to strategy. It remains to be studied whether in other sectors it is the same, or if changes in the environment can change this prevalence. It is important to state that
the general and financial crisis that has shaken Western Europe has particularly placed serious constraints on the ability to finance companies, stressing the importance of business performance to resources and capabilities. One limitation of the study
is the size of the sample, although it reflects the reality of the sector, a larger sample would perhaps have allowed for better statistical parameters, especially in relation to individual companies and cooperatives. As to the applicability of the study,
authors suggest that technology is essential, as well as market orientation, innovation and efficiency, in terms of key drivers of business performance. Another limitation could be the type of survey, 1) the authors adopted scales used in similar studies
to evaluate resources and capabilities and strategies, this facilitates the comparison between sectors although it may lose inter-sectorial specificity; 2) in terms of performance, the manager of the company was asked to subjectively report the relative
strength of his or her winery compared to their competitors, this may seem less solid than the accounting data. However, it is necessary to point out that subjective scales are a common method in studies like this and furthermore, subjective scales have
been demonstrated to converge with objective scales in business evaluation being used in numerous empirical studies.