Author
María del Mar Alonso-Almeida – (Universidad Autónoma de Madrid)
Kerstin Bremser – (Pforzheim University)
The paper presents the results of a 2009 survey of 136 Spanish small service businesses. Male and female owners of travel agencies were interviewed to indicate their crisis readiness and measures taken to confront the crisis. Gender based differences in strategic decision-making were detected. Whereas men and women were equally successful to overcome the crisis, their strategies differed. Women were on average significantly younger, employed measures focusing on price, kept social measures intact and employed to a lesser extent drastic measures to reduce costs (layoffs, dismissals). Men used drastic measures most. The differences in strategic choice can be attributed to a gender specific leadership style.
Nowadays, companies face manifold challenges that often involve uncertainty. Thus, to lead an enterprise, it is not sufficient to possess only technical skills in the industry. To demonstrate an effective and efficient leadership style to achieve business excellence, managers also have to develop social and emotional capabilities (Mandell and Pherwani, 2003; Melero, 2011).
Several studies have underlined the changes that have been going on in the labor market, starting with the massive incorporation of women into the workforce. In most developed nations, this tendency started in the 1970s and now women account for approx. 50% of the total workforce (Hopkins et al., 2008). However, research has shown that female capabilities, acquired through education and participation in the workforce, are not reflected in the daily reality in workplaces. Female participation in leadership roles is still very low compared with their education and workforce participation (Alonso-Almeida, 2011; Appelbaum et al., 2003; Broadbridge and Hearn, 2008).
One way of explaining this situation is the idea that men and women define success and subsequently business excellence in private and professional life differently (Mainiero and Sullivan, 2006; O’Connor, 2001; O’Neil and Bilimoria, 2005). According to these studies, men and women use different leadership styles, resulting in different qualitative business decisions (Hackman et al., 1992; Mandell and Pherwani, 2003). These differences lead to the use of different leadership styles between men and women that manifest themselves in the way decisions are made and management is executed. According to the results of prior studies, the female leadership style seems to be less effective when analyzing performance by comparing start-up capital (Alsos et al., 2006; Coleman and Robb, 2009; Fairlie and Robb, 2009; Verheul and Thurik, 2001; Watson, 2002), subsequent financing (Coleman, 2002, 2007; Alsos et al., 2006; Coleman and Robb, 2009) and performance in companies run by men and women (Cooper et al., 1994; Alsos et al., 2006; Fairlie and Robb, 2009). Pioneering cross-sectorial studies obtained mixed results with regard to gender-related capitalization, external financing and performance, but mostly showed that women performed worse. Nevertheless, the latest research did not find any differences in performance. In fact, when longitudinal studies were conducted (Aterido and Hallward-Dreiermeier, 2011; Lafuente and Rabetino, 2011), a significantly higher performance in female-led companies was identified proving a higher business excellence.
Thus, Aterido and Hallward-Dreiermeier (2011) asserted that “decision making is what matters”. However, Zolin and Watson (2012) stated that “most studies, included decision management, have been predominantly of male businesses, more research is needed on women’s business issues, in particular the different ways women strategize their firms”.
Therefore, there is little empirical evidence available about what kinds of decisions female managers make to achieve business excellence. Even though some attempts have been made to identify differences in male and female leadership styles, there remain many unanswered questions (Amagoh, 2009; Appelbaum et al., 2003; Yammarino et al., 1997). The main reason for this is that most prior research was based on a macro-level perspective. Thus, it is necessary to obtain in depth knowledge on female leadership from a micro-level viewpoint, at the level of individual firms, in order to help women overcome those barriers that inhibit them from taking up the positions they deserve.
In addition, to the best of our knowledge, no study has analyzed decision making in companies led by women and contrasted their actions to those taken by men faced with an identical situation. Hence, from a business viewpoint, it is difficult to determine the specific influence of gender on the decision-making process. As a consequence, this investigation could be considered a pioneer study, which aims to fill the void in research about female business behavior in strategic management using a single sector and location.
This work, exploratory in nature, uses two complementary methods to analyze the linkage between gender and strategic management decisions: univariate analysis by means of ANOVA and multivariate regression analysis. In previous empirical research, each study typically used a single method to test relationships. The use of two methods may improve the validity of the results through triangulation. This research should shed light on how women manage their businesses and face critical situations.
The remainder of this paper is structured as follows. In section two, the theoretical arguments concerning decision making from a gender-based approach are discussed. In section three, the empirical design of this study is described. In section four, a quantitative analysis is presented, followed by section five, in which the study’s findings are presented. Finally, in section six, this paper is concluded with several major implications drawn from the research.
For many years, most research voiced the opinion that male leadership was most effective in the business world in terms of financial performance (Cooper et al., 1994; Alsos et al., 2006; Fairlie and Robb, 2009). Given that the business world has been created out of a male vision (Dye et al., 2005), the ideal leader is characterized by traits that most men possess (Broadbridge and Hearn, 2008). Schein (2007) called this the “think-manager; think-male” effect, which apparently qualifies men as better leaders. This form of thinking currently prevails in developed countries (Bosakand Sczesny, 2011; Jackson et al., 2007; Rodler et al., 2001).
A number of researchers (Eagly and Carli, 2007; Eagly and Sczesny, 2009; Melero et al., 2011) have summarized the different characteristics in leadership between men and women. Thus, leadership theory has identified two orientations: task-oriented and interpersonally oriented leadership. According to gender roles, female managers would be more prone to lead with an interpersonal orientation, while male managers would be more likely to apply a task-oriented style (Eagly and Karau, 1991; Powell and Graves, 2003). Task-oriented leadership aims to maintain authority as well as hierarchy and to achieve business goals, while interpersonally oriented managers build their leadership on empowering their subordinates, motivating them and showing concern about their development at work as a means of achieving business goals. Eagly and Carli (2007) mentioned that, although some studies found that both men and women have the same task-oriented leadership, women show more interpersonal orientation than men (Melero, 2011).
Another way to describe leadership styles is in the differentiation between democratic and autocratic. Bird and Brush (2002) argued that men have a strategic style of management characterized by centralized decision making (autocratic) and women prefer a participative decision making characterized by high commitment to their employees (democratic). This same concept was identified in a meta-analysis carried out by Eagly and Johnson (1990).
On the other hand, globalization, increased client focus, the search for new markets and other factors like increased care for the environment, corporate social responsibility and the need to relate to different stakeholders of a company put the focus on new capabilities needed to lead companies. The aforementioned factors have led to the development of a new leadership style, called transformational leadership. As Eagly and Carli (2007) asserted, these types of leaders help their employees to develop their full potential and face difficult situations through innovation. It seems that women use a leadership style that is concerned with maintaining the motivation of their employees (Barbuto et al., 2007; Davis et al., 2010). This is consistent with the literature regarding female leadership styles (Bird and Brush, 2002; Hackman et al., 1992; Mandell and Pherwani, 2003; Melero, 2011; Wicker et al., 2012). Thus, female directors prioritize stable employment and their responsibility for their employees (Danes et al., 2007), as well as long-term relationships with clients (Krishnan and Park, 2005; Schaap et al., 2008). For these reasons, previous research suggested that, in transformational leadership, in contrast to transactional leadership focused on the conventional way of managing a company, female capabilities are more important and women are better adapted to understand the changes that take place in the market (Carless, 1998; Eagly and Sczesny, 2009; Konrad et al., 2000; Schein, 2007; Schaap et al., 2008).
Although female leadership has changed over time, some researchers (Eagly and Carli, 2007; Melero, 2011) have suggested that men and women tend to make managerial decisions consistent with their gender-specific leadership styles. Thus, this study proposes the following hypothesis:
H1: Gender is a significant factor in explaining strategic managerial decisions in critical situations, such as a financial crisis, according to gender-specific leadership styles.
Few researchers have analyzed strategic choices from a gender perspective. Since Porter (1982) first stated generic strategies, others have spread these choices but still generally follow those outlined in his work: cost leadership, differentiation and segmentation (Johnson et al., 2006; Poon, 1993).
In business management, Bardasi et al. (2011) argued that men and women take different approaches to lead their business. In line with this, Gaskill et al. (1996) found the development of different market strategies between men and women.
Other researchers (Rosa and Hamilton, 1994; Cliff, 1998; Jennings and McDougald, 2007; Kepler and Shane, 2007; Zolin and Watson, 2012) also found that men prefer to develop growth strategies while women tend to be more cautious or grow slowly by consolidating their customer base.
Thereby, a growing business strategy usually entails a different strategy than a slow growth. For this reason, Minitti et al. (2005) stated that women develop differentiation strategies based on the quality of products or services. These strategies are in accordance with the goal of achieving a loyal base of customers (Johnson et al., 2006; Poon, 1993; Porter, 1982) or to open new markets with specific requirements (Alonso-Almeida, 2012; Porter, 1982). Nevertheless, the applied strategy could change depending on the environmental conditions (Collins, 2009; Alonso-Almeida and Bremser, 2013).
As such, on the basis of previous research, the following hypothesis is proposed:
H2: Gender is a significant factor in explaining strategic choices in business management.
Nevertheless, no gender-specific strategic choices or decisions have been found to be less effective in financial terms when men and women occupy the same role and position in an organization. Even when women and men are evaluated using other measures of effectiveness to test managers´ tacit knowledge of the business or workers´ productivity, they do not differ in effectiveness (Eagly et al., 1995). In other words, women who develop an adequate strategy and make the right decisions to face critical situations generally succeed in the market just as well as their male counterparts. Thus, although female managers might prefer slower growth, this does not mean that the survival rate of their firms will be any lower than for males, as some research has shown (Robb and Watson, 2012; Sabarwal and Terrell, 2008; Watson, 2003). However, it could restrict expenses in investments (Bardasi et al., 2011).
Davis et al. (2010) reported that gender has a significant indirect effect on growth and profitability, which they attribute to the presence of a market-based approach to business. Aterido and Hallward-Dreimaier (2011) found that women, more than men, focused their business on process or product improvement, to satisfy their customers, and social action and human development, to achieve the commitment of their employees. Krishnan and Park (2005) argued that women increase power sharing with employees and, thus, could increase overall performance. These practices were critical to obtain a significant effect on gross revenue according to Danes et al. (2007). Thus, Krishnan and Park (2005) and Aterido and Hallward-Dreimaier (2011) asserted that the female management style could enrich strategic decision-making and improve business performance. According to Eagly et al. (1995), “Even if female leaders do behave somewhat differently than male leaders, they appear to be equally effective”. In conclusion, a gap in business performance and business excellence should not be a gender gap.
Thus, on the basis of this previous research, the following hypothesis is proposed:
H3: Women and men are likely to be equally effective, although both could select different decisions and strategies.
To analyze the impact of gender on strategic decision-making, 136 tourist companies were surveyed. To ensure the evaluation of appropriate individuals, this study only considered questionnaires when the informant pointed out that he or she was the decision-maker. In total, 64 of the surveyed companies were led by women and 69 by men, which corresponds to 52.2% female-led companies and 47.8% male-led companies. The survey took place between November and December 2009, when the Spanish tourist sector was recovering from the previous economic crisis. Since the beginning of the crisis, tourism declined until the end of 2009 (UNWTO, 2009; UNWTO, 2010) and then rebounded in 2010. This rebound was confirmed in 2011 (UNWTO, 2011) and is predicted to be sustained in 2012.
Travel agencies were chosen for two reasons. First, data from Spanish universities show that women form the majority of those students majoring in tourism (Rodriguez-Anton et al., 2009). However, the sector is not considered to be female-dominated (Williams, 1992). Secondly, there is fierce competition within the sector. In this context, travel agencies need to take innovative decisions to remain competitive and to survive (Alonso-Almeida and Llach, 2013).
Table 1 provides descriptive information about the companies and their respective male and female leaders.
| Company type | |||
| % Total | % Male | % Female | |
| Retail | 61.1 | 65.1 | 64.9 |
| Wholesale | 30.5 | 25.4 | 28.4 |
| Tour-operator | 8.2 | 9.5 | 6.8 |
| Other characteristics of the company | |||
| Mean | Mean Male | Mean Female | |
| Size (number of employees) | 3 | 3.55 | 2.54 |
| Age of company (years) | 15 | 17.4 | 12.6 |
| Age of the male and female leaders | |||
| % Total | % Male | % Female | |
| Less than 30 years | 36.6 | 26.6 | 45.7 |
| Between 30 and 45 years | 42.1 | 45.3 | 41.4 |
| Between 45 and 60 years | 19.7 | 25.0 | 12.9 |
| Over 60 years | 1.5 | 3.1 | 0 |
| Professional experience of the male and female leaders | |||
| % Total | % Men | % Women | |
| Less than 5 years | 50.4 | 40.3 | 59.4 |
| Between 5 and 10 years | 31.3 | 33.5 | 29.0 |
| More than 10 years | 18.3 | 26.2 | 11.6 |
Table 1. Demographic characteristics of the companies surveyed
As can be seen in Table 1, most of these companies focus on retail, regardless of whether they are male-led (65.1%) or female-led (64.9%). There are slightly more male-led retail agencies. Women lead most of the wholesale agencies, whereas men dominate the tour-operators, even though this type represents only a small percentage of the total (8.2%). In this study, as in previous research (Appelbaum et al., 2003; Schein, 2007; Rosener, 1990; Aterido and Hallward-Dreimaier, 2011; Bardasi et al., 2011), female-led companies are younger and smaller, in terms of the number of employees. Moreover, the surveyed women have less professional experience than men: 59.4% of the women interviewed have less than five years of work experience, in contrast to 40.3% of the men. However, this is reasonable since, in the sample, 45.7% of the female-led companies had owners younger than 30 years old.
The data could be interpreted in different ways. On the one hand, they could mean that women in this specific subsector have rapid access to management positions given their educational background and the glass ceiling does not exist or is easier to break than in other sectors. They could also imply that there are fewer barriers to reaching top management positions in this kind of company than in other sectors. In fact, this is supported by the literature because previous research has shown that, around the world, tourism companies have more diversified and more gender-balanced boards of directors and administrative councils than companies operating in other sectors (Alonso-Almeida, 2011). Therefore, this sector presents a good starting point for research management from a gender perspective. On the other hand, this fact could underline what some researchers have discovered (Ndemo and Maina, 2007), namely, that women are “pushed” to create their own jobs since they cannot find adequate ones in the labor market. Thus, one could find young women leading companies in this sector despite them having less experience than men on average. Although it was found that this could be a critical factor for a firm’s performance, manager experience was not always significant (Aterido and Hallward-Driemeier, 2011).
The analysis of this specific situation in the tourism sector exceeds the limits of the current study, but will be included in future research.
In order to analyze the leadership styles of men and women and the subsequent differences in the companies they lead, three different aspects of decision making were studied: the strategy developed by the company, the measures taken to confront the economic crisis that started in 2008 and, finally, the impact on performance.
The literature regarding strategies undertaken in times of crisis was considered and from it possible measures to confront the crisis were identified. In total, 22 measures were chosen (see Annex 1). The surveyed managers were asked if they applied these measures and to what extent. The measures taken to confront the crisis were classified using a five-point Likert scale, with 1 indicating that the measure was not used and 5 that the measure was applied fully.
Likewise, to identify the strategies employed by the companies, Porter’s (Porter, 1982) classification, which was later extended by other researchers (Johnson et al., 2006; Poon, 1993), was used. Thus, six dichotomous variables defined the different strategies that companies can adopt: Low prices, Balance, High quality, Image, Segmentation and Others. The manager selects one of the strategies chosen by the company. This strategy is classified with 1 whereas the rest is codified with 0.
Finally, previous research has shown that companies confronting a crisis suffer a decline in sales and have to lower prices in order to cover the costs of their business (Enz et al., 2011; Kimes, 2009; Okumus and Karamustafa, 2005; Okumus et al., 2005). In addition, in earlier economic crises, incomes in the tourism sector fell drastically (Sausmarez, 2004; Kimes, 2009). Given that the intensity of the income decline depends upon the company’s strategy and the decisions made at the moment of crisis, it seems possible to analyze what happened with performance. For this purpose, a dichotomous variable, Performance, was created. It takes a value of 1 when incomes have been maintained or increased, and 0 otherwise.
Control variables were also included: size in terms of number of employees and age.
Table 2 shows all the variables used in this analysis.
Variable description | Type and Measurement |
Gender | Dichotomous variable: 0=man, 1=woman |
Decisions to face the crisis | Discrete scale of agreement on a five-point Likert scale: 1, when the measure was not used, to 5, when the measure was applied fully |
Strategy | 6 dichotomous variables |
Performance | Dichotomous variable: 0=decreased income, 1=maintained or increased income |
Company type | 3 dichotomous variables |
Employees | Continuous variable |
Company age | Continuous variable |
Age of decision-maker | 4 dichotomous variables |
Professional experience of decision-maker | 3 dichotomous variables |
Table 2. Explanatory variables
In order to test the first hypothesis, a factorial analysis was undertaken, which enabled the named measures to be grouped. First, a reliability analysis of all 22 items was conducted. The coefficient obtained for Cronbach’s alpha was 0.836, which can be considered as very good. Moreover, no significant benefits were accrued with regard to Cronbach’s alpha if some of the observed elements were eliminated (Malhotra, 1981). Thus, the unidimensionality of the scale can be accepted.
Subsequently, in order to group the measures taken, a factor analysis was undertaken using the maximum likelihood method. The Kaiser, Meyer, Olkin (KMO) test result, with a value of 0.770, is compatible with a good level of adjustment. Bartlett’s test of sphericity provided a statistical value of 937.278 and a critical value of 0.000, which leads to the rejection of the null hypothesis that the correlation matrix is equal to the identity. The study of the communalities after extraction and the anti-image matrix showed the suitability of all items. Moreover, convergence was achieved in a few iterations.
For the extracted factors, only those with an eigenvalue of 1 or more were taken into account. Then, a varimax rotation using Kaiser’s normalization was carried out for the business decisions whose values are shown in Table 3. Here, only factor loads over 0.4 were considered, which explain 63.997 of the total variance. Table 3 displays the seven resulting factors.
The first factor is related to reactive measures concerning growth strategies undertaken in situations of uncertainty. Companies that face a situation where declining sales can be expected stop planned growth initiatives and planned investments and wait to see the actual evolution of the market (Pearce and Michael, 1997). Moreover, owing to the possibility of a decline in sales and a lack of liquidity, they search for solutions to avoid insolvency.
The second factor includes measures favoring the development of added value for the customer in order to tackle the crisis. These measures aim to increase client loyalty with the intention of stopping the decline in sales that accompanies an economic crisis (Williams and Naumann, 2011).
The third factor groups proactive measures. According to the literature (Alonso-Almeida and Bremser, 2013; Sausmarez, 2004; Enz et al., 2011; Kimes, 2009; Okumus et al., 2005), companies have to undertake these actions to overcome a crisis. The researchers mentioned above found that, during previous economic crises, strengthening of the commercial area and increasing marketing spending were crucial to reach new market segments, raise the profile of the company among existing and potential customers and win clients from companies that closed down and thus needed new service providers.
| Factorial Load | Total Mean | Men Mean | Women Mean | ANOVA |
Factor 1 REACTIVE MEASURES |
| 2.12 | 2.29 | 1.95 | .142 |
We canceled expansion plans | .869 | 2.21 | 2.31 | 2.11 |
|
We canceled investments | .856 | 2.24 | 2.59 | 1.93 |
|
We reduced management levels | .618 | 1.96 | 2.28 | 1.71 |
|
We renegotiated bank credit | .595 | 2.02 | 1.98 | 2.09 |
|
Factor 2 ADDED VALUE |
| 2.96 | 3.13 | 2.80 | .090 |
We created awards for employees’ ideas to reduce costs or increase sales | .740 | 2.70 | 2.80 | 2.69 |
|
We introduced employee empowerment | .671 | 2.83 | 2.80 | 2.87 |
|
We introduced new IT systems | .666 | 2.99 | 3.27 | 2.53 |
|
We created or improved our loyalty program | .586 | 3.42 | 3.66 | 3.19 |
|
Factor 3 PROACTIVE MEASURES |
| 3.18 | 3.36 | 3.01 | .041* |
We increased spending on advertising | .766 | 2.52 | 2.63 | 2.47 |
|
We strengthened the commercial area | .604 | 3.38 | 3.55 | 3.19 |
|
We looked for new business channels | .590 | 3.70 | 3.91 | 3.52 |
|
We improved processes to save operating costs | .416 | 3.11 | 3.37 | 2.87 |
|
We entered into strategic alliances with other companies to offer joint services | .474 | 2.61 | 2.78 | 2.46 |
|
Factor 4 SOCIAL VALUE |
| 2.49 | 2.71 | 2.28 | .042* |
We decreased or eliminated our training budget | .804 | 2.49 | 2.73 | 2.26 |
|
We decreased or eliminated our budget for internal and external social spending | .662 | 2.40 | 2.63 | 2.16 |
|
Factor 5 SPECIALIZATION |
| 3.72 | 3.80 | 3.66 | .244 |
Products or services in high demand from clients were not changed, but those with less demand were omitted to reduce costs | .853 | 2.85 | 2.89 | 2.84 |
|
Costly products or services were replaced by cheaper ones | .734 | 2.95 | 3.19 | 2.82 |
|
We asked clients more about what would increase value | .550 | 3.13 | 3.30 | 3.00 |
|
Factor 6 DRASTIC MEASURES |
| 2.59 | 2.86 | 2.36 | .016*** |
We renegotiated prices or payment conditions with suppliers | .639 | 2.71 | 2.67 | 2.79 |
|
We reduced personnel in all departments | .523 | 2.80 | 2.84 | 2.76 |
|
Factor 7 SURVIVAL |
| 2.82 | 2.95 | 2.71 | .202 |
Competitors’ practices and services were imitated | .645 | 2.68 | 2.67 | 2.69 |
|
We reduced our sales forecast for the year | .639 | 2.96 | 3.22 | 2.73 |
|
*=Statistically significant, ***= Statistically highly significant
Table 3. Factorial analysis of the business decisions taken during the crisis
The fourth factor includes activities that companies eliminate in order to reduce costs before employing other cost-cutting measures. It comprises measures like personnel development and corporate social responsibility. From an internal viewpoint, these factors motivate employees and promote professional career development through educational measures. On the other hand, from an external viewpoint, these factors are important for small companies since actions undertaken in this domain increase their visibility and strengthen their market positioning (Tullberg, 2005). These activities are also important since they enable firms to maintain a high degree of service quality towards the final customer, despite the changes that might be caused by the crisis.
The fifth factor contains some measures to reduce costs without eliminating services or products demanded by customers. These measures help the company to specialize in particular products or services and close customers, thereby reducing costs (Okumus and Karamustafa, 2005) and gaining in flexibility (Kamoche, 2003; Anderson, 2006).
The sixth factor groups the most drastic cost-cutting measures, for instance, lay-offs and renegotiation of corporate debt. In the case of service industries, the lay-offs would be accompanied by a reduction in the level of service and thus might lead to lower levels of client satisfaction or the loss of clients (Alonso-Almeida and Bremser, 2013; Pearce and Michael, 2006). As these measures are easy to undertake, they are more often used by companies than desired and they carry a high social cost.
Finally, the seventh factor contains all survival practices related to the specific environment. This includes the imitation of actions of those competitors that seem to be successful or the reduction of sales objectives according to the status of the economy (Laitinen, 2000; Kimes, 2009).
An ANOVA analysis was conducted in order to determine differences between the decisions taken to face the crisis in male- and female-led companies. The results are shown in Table 3. As can be seen, significant differences were found in three of the seven factors. Robust statistics from ANOVA found the same results.
Significant differences were found in male and female decision making in the following categories: factor three, which groups measures that the literature calls proactive (F=4.241; squared mean=4.072; these actions help to maintain or increase the business activity in times of crisis); factor four, which describes measures that concern responsibilities towards the employee (F=4.524; squared mean=6.260); and factor five, which combines all drastic measures of cost reduction that companies can undertake in times of crisis (F=6.007; squared mean=7.193).
For the other factors, no significant differences were detected.
To test hypothesis 2, logistic regression analysis was carried out. The model identifies the main decisions and strategies for business that women apply. The specification of the model is as follows:
GENDER = DECISIONSi +STRATEGYi + PERFORMANCEi + MANAGER_CHARACTERISTICSi + FIRM_CHARACTERISTICSi + i.
The sub-index irefers to each travel agency. DECISIONS and STRATEGY comprise the set of variables that explain what strategic decisions women have made during the period studied. The DECISIONS variable is composed of the seven factors calculated previously. The PERFORMANCE variable is used as a proxy for firm performance as explained above. The variables MANAGER_CHARACTERISTICS and FIRM_CHARACTERISTICS describe the characteristics of each manager and travel agency. Control variables have also been included. The results are presented in Table 4. The R square of Nagelkerke presented a value of 0.239, which can be considered to indicate a good fit.
| B | E.T. | Wald | Sig. | Exp(B) | C.I. 95% for EXP(B) |
| |||||||||
Lower | Upper |
| ||||||||||||||
| AGE LESS THAN 30 | 1.282 | .482 | 7.089 | .008 | 3.605 | 1.403 | 9.267 | ||||||||
PROACTIVE M. | -.752 | .263 | 8.159 | .004 | .471 | .281 | .790 | |||||||||
LOW-PRICE STRAT | .610 | .214 | 8.094 | .004 | 1.840 | 1.209 | 2.800 | |||||||||
Constant | -.318 | .914 | .121 | .728 | .727 |
|
| |||||||||
Table 4. Logistic regression
As it can be seen in Table 4, multivariate analysis clearly showed differences in the strategic decisions made by men and women. Regarding STRATEGY, women more often deploy low-price strategies, contrary to the findings of previous research. In the case of DECISIONS to face the crisis, the multivariate analysis found that only PROACTIVE MEASURES are negatively significant (-0.752) in the behavior among men and women. Nonetheless, there are no differences in performance. However, the most significant variable was age. Female managers are characterized by being younger than 30 years old, which corroborates previous research. This variable is the most significant in MANAGER_CHARACTERISTICS (1.282). In the case of FIRM_CHARACTERISTICS, no differences were found. The statistical results validated most of the proposed hypotheses. Now, the hypotheses will be contrasted and the findings explained below.
The findings obtained in this study shed light on women’s strategic decisions in companies and how they lead.
The study has found mixed results from an analysis of the decisions taken with respect to the measures employed in times of crisis. On the one hand, four of the seven factors that group together specific types of measures taken by companies in times of crisis show no significant differences in the leadership behavior of men and women. Thus, both develop, in this order, added value, specialization, survival and reactive measures in order to face the crisis. This is in line with the work of Eagly and Carli (2007). These researchers asserted that women and men who are in the same role and market environment, in terms of sector, location and macroeconomic situation, should lead in similar ways. As such, according to the literature, the measures that add value and promote specialization are the best to maintain a company in the market in a time of financial crisis (Alonso-Almeida and Bremser, 2013; Laitinen, 2000; Okumus et al., 2000; Pearce and Michael, 1997; Williams and Naumann, 2011). In the case of reactive measures, which men as well as women applied the least, it can be stated that this is an adequate decision for survival during times of crisis (Alonso-Almeida and Bremser, 2013). Moreover, the selection of these decisions to face a crisis is an indicator of good quality management in both women and men. On the other hand, for three of the factors in which men and women took different decisions, women received lower values. This implies that women used these measures to a lesser extent than men. Therefore, it is shown than women apply less proactive measures in times of crisis than men. Proactive measures are necessary to optimize and evaluate all the resources of the company and to strengthen inter-company relationships that the firm had developed before the crisis (Pearce and Michael, 1997). These findings could be related to the fact that women choose to take fewer risks than men (Bardasi et al., 2011). However, they could also indicate that women use other measures of risk and, based on them, make different decisions (Eagly and Carli, 2007). There is a need to shed more light on this issue by using qualitative data.
According to the leadership style attributed to women, they keep social measures intact and use drastic measures to reduce costs to a lesser extent than men. Thus, they might not be able to reduce costs as much as men. The biggest difference between men and women has been found in this third factor: male-led companies are those that use drastic measures most. However, since this study is focused on a service industry, the results suggest that, in male-led companies, staff are dismissed and more pressure is put on the remaining personnel, whereas female-led companies follow a more responsible and sustainable business model (Thompson et al., 2010). Therefore, hypothesis 1 is accepted because some similarities in terms of decision-making in times of crisis have been found, but some differences have also been revealed. These differences in leadership style are associated with gender despite the fact that, in the last two decades, both female and male managers have changed and adopted a balance between task- and person-oriented strategic decisions (Rodler et al., 2001).
With regard to strategic choices, contrary to expectations and previous research that stated that women usually choose differentiation strategies (Minitti et al., 2005), women do deploy strategies based on low prices to maintain income. One possible explanation for this is related to a particular characteristic of female managers: their age. Female managers are predominantly younger than 30 years old and previous research showed that younger manager are less risk-averse and more aggressive in their strategic choices to enter or maintain their place in the market in difficult times (Yasuda, 2005; Calvo, 2006; Goedhuys and Sleuwaegen, 2010). Another explanation could be that women adapted their business to a critical situation using a market-based approach, where customers only buy products based on price (Papatheodorou et al., 2010). As Krishan and Park (2005) stated, women are more likely to follow a learning approach and change their business strategies according to environmental characteristics. Thus, there is some evidence that younger managers are more likely to alter their strategies in response to changing environmental conditions (Grimm and Smith, 1991). These changes of strategies to face the environment’s uncertainty and hostility ensure the company´s survival (Collins, 2009).
In this study, performance was found to be similar in companies managed by women to that in those run by men, as a result of women’s greater tendency to adopt a market-based approach to conducting business. Therefore, hypothesis 2 is accepted. However, given that perception data have been used, this finding should be considered cautiously.
Finally, hypothesis 3 has also been supported given that performance variables do not show significant differences. This means that both women and men achieve similar levels of performance, but use different approaches to attain their goals. The overall results suggest that, even though there seem to be some differences in decision-making and strategic choice between men and women, there are also many similarities, as previous research has reported in recent years (Rodler et al., 2001; Eagly and Carli, 2007). Thus, this study corroborates previous research and confirms that women are not less effective than men in financial terms but, socially, women contribute more to maintain employment. Consequently, women promote employees’ job security, increase morale and ensure a high level of organizational commitment, which could improve the company’s situation in the long term.
The findings of this study allow a series of conclusions about successful management to be drawn. A study by Barsh et al. (2008) for the McKinsey Leadership Project stated that, at present, there are no differences between men and women regarding academic education, dedication and professional preparation. Given the need for more leaders that can manage companies successfully, it is hoped that more women make it to the top in the future.
First, the studied companies, including those led both by women and by men, seem to have chosen the right measures to confront the crisis and survive. On the one hand, companies led by men decided to use new distribution channels via new technologies and networking, while at the same time taking drastic measures to reduce costs and lay off staff. On the other hand, companies led by women strengthened their relationships with their clients and added value to their products and services, while at the same time keeping employment and employment benefits (social value) as stable as possible. In the current economic situation, managers who develop leadership based on a transformational style are more ready to understand the changes that take place in the market and, therefore, more possibilities to achieve business excellence.
Secondly, regarding the strategies employed, significant differences between men and women were found. Given that previous research contradicts this finding, it is necessary to undertake more intensive research regarding strategies of male- and female-led companies by analyzing more complex constructs than the one used here in order to capture the existing differences better. Nevertheless, these findings suggest a different quality on decisions.
Thirdly, this finding suggests that there should not be marked differences in the company’s financial results. Thus, the hypothesis of underperformance postulated by previous studies is not supported by this research. However, more intensive research on this issue has to be undertaken regarding the financial results of companies in order to detect if gender is a factor that influences financial results.
Finally, as shown by the results and on the basis of a statement made by Krishnan and Park (2005), both women and men are qualified to respond to the environment’s difficulties and to take the best decisions to maintain a company in the market. Companies should overcome their reluctance to have female leaders and strike down the barriers that impede women from climbing to the top management positions, given that the prevailing ‘wisdom’ regarding underperformance and real results does not correspond to reality. On the contrary, companies might lose valuable opportunities to add to their human resources, in that women bring with them an innovative and fresh vision regarding business decisions. The current crisis has underlined that companies cannot continue to waste talent, but instead have to break with previous values and reinvent the way they operate and react in the market. In order to do this, they need well-qualified and experienced women as well as men.
This article does not attempt to explain differences in performance, but only to verify that managerial decisions are affected by gender to achieve business excellence. As such, performance in female-led companies should be a subject of expanded future study in order to overcome this limitation. In such future study, it could be useful to employ hard financial figures and in-depth analyses of business cases.
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