Does customer satisfaction mediate between strategy and performance?

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Does customer satisfaction mediate between strategy

and performance?

A comparison of international airlines, based on TripAdvisor reviews

J.H.B.A. van Amerongen Dr S.R. Gubbi Supervisor-assessor

January 28th_{, 2019} _{Dr. R.W. de Vries Co-assessor}

Master thesis

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Abstract

International passenger airlines are divided in two strategic value propositions: customized high-quality service or standardized no-frills transportation. Although both strategies are recorded to have equivalent financial performance, differences in service quality are hypothesised to affect customer satisfaction. Therefore, is hypothesized that customer satisfaction mediates between strategic orientations and firm performance. Building on a theoretical contradiction between equal performance of strategic orientations and the satisfaction performance chain. To uncover the contradiction between satisfaction and service standardization becomes increasingly relevant in a time of service commoditization. As both commoditization and the need for customer satisfaction ambivalent.

A sample of international operating passenger airlines (N=100) is used to test the mediating model, whereby TripAdvisor reviews are used as proxy for customer satisfaction. Results do not show a mediating effect of customer satisfaction, while financial performance of standardized services is higher compared to customized services. In addition customization firms had more resources to exploit a scale advantage, as their firm size was on average 80% larger than standardized service. Besides, customization leads to more customer satisfaction than standardization. In turn, the relation of customer satisfaction on firm performance is negative for standardization and positive for customization. Concluding, the that strategic benefits of the sampled airlines focused on customization are inconclusive, as their performance reaps benefits of their size instead of service quality.

Keywords: customer satisfaction, service, performance, strategy, standardization, customization

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1. Introduction

Like products, modern services are faced with commoditization of their function (Reimann, Schilke, & Thomas, 2010), and so experience price pressure and greater competition. To remain profitable in increasingly competitive markets, two strategic directions are available to firms in terms of value proposition: low cost, standardized services to the mass, or high quality customized services to the individual. Standardization and customization achieve operational effectiveness through different paths. For example, airlines who provide customized services such as British Airways have comparable financial performance to airlines with standardized services such a Wizz Air (CAPA, 2017). Standardization enhances margins by reducing cost through economy of scale (Schilke, Reimann, & Thomas, 2009), while customization enhances value by adding ancillary services linked to economy of scope and value differentiation (Wang, Wang, Ma, & Qiu, 2010). Building forth on the generic strategy typologies of Porter (1996) and the goods and service dominant logic of Vargo & Lusch (2004, 2008), both standardization and customization are theorized to have distinctive competitive advantages through fulfilling different types of consumer needs. Standardization caters to consumers with functional needs, while customization caters to consumers with hedonic needs (Ding & Keh, 2016).

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5 Mittal, 2000). Hence, their competitive position and firm performance are strengthened via customer satisfaction. On the other hand, standardization competes over functionality and lowest price. So that, gained customer satisfaction as a result of improving service quality, would have a negative effect on their competitive position and thus their firm performance (Parnell, 2006).

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6 Firms benefit by creating an optimal value proposition towards the needs of consumers. The prior discussion about consumer needs demonstrates that customer satisfaction should not be the goal of every firm. Standardizing firms benefit when the core function of a service fulfils the needs of consumers at the lowest cost. Since lower cost create a competitive advantage on sales price and cost margin. In turn, firms that focus on customization attain higher profit margins through greater levels of satisfaction (Anderson & Mittal, 2000), because satisfaction results in behavioural responses such as greater ascribed value and loyalty, resulting in better profit margins. Shortly, the benefits of customer satisfaction are strategy dependent, because consumption goals conflict with the need for value.

It is the aim of this paper to empirically test the mediating effects of customer satisfaction between service strategies and financial firm performance. To question the current position in literature that customer satisfaction and firm performance are solely positive related. Here for building forth on the two contradictory frameworks, one hand are the benefits of customer satisfaction supported in the performance chain of Anderson and Mittal (2000) and the service Profit chain Homburg et al., (2009). On the other hand do Porter (1996) and Lusch, Vargo, & Brien (2007) argue that a strategy with low service quality can be just as successful as one with high service quality. Based on this contradiction I hypothesize that customer satisfaction mediates between strategy and firm performance. Therefore this paper build forth on the paper of Mellat-Parast, Golmohammadi, Mcfadden and Miller (2015), who’s approach is line with to the hypothesis of this study. Their study tested the strategic dependable effects of service quality on firm performance and concluded that the effect of service failure on performance is strategy dependent in the airline industry.

This study tests the mediating effect of customer satisfaction with a sample of internationally operating airlines in a linear regression. The results show that customer satisfaction does not mediate between strategy and firm performance, although the effect of customer satisfaction on performance is negative for standardization and positive for customization.

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2. Literature review

This paper incorporates two streams of research to attest that the benefits of customer satisfaction are strategy dependent. On the one hand, the satisfaction-profit chain of Anderson and Mittal (2000) and the service-profit chain (Heskett, Jones, Loveman, Sasser, & Schlesinger, 1994; Homburg et al., 2009) argue that strategies that offer greater value have more customer satisfaction, which results in greater firm performance. Opposingly, literature about strategic segmentation theorize that customization and standardization have their own competitive advantage (Porter, 1996; Vargo & Lusch, 2004).

2.1. Strategy

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8 On the other hand, producing services happens in little interplay with consumers and results in little ancillary value. Producing service is focused on the functional delivery of services and can therefore be linked to standardization, while providing services is associated with customization based on the fulfilment of personal needs (Ding & Keh, 2016).

In turn, Porters (1996) generic strategy theory proposes that firms who are dedicated to either pursuing cost-leadership or differentiation, will have successful firm performance. Because these strategies create superior margins and are difficult to mimic for competitors (Parnell, 2006). Empirical findings show that both generic strategies, performed equally well in the Hong Kong’s international banking industry (Chan & Wong, 1999) and various SME in Australia (Leitner & Guldenberg, 2010).

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2.2. Customer satisfaction

Customer satisfaction is considered the result of a consumers appraisal of value (Wang et al., 2010). For intangible products like services, interpretation of value is subjective, therefore customer satisfaction is a useful tool to asses value of services (Lai et al., 2009). According to Olivers (1980) expectancy disconfirmation theory, satisfaction is defined as the differences between expectations and perceived quality. In extension of this view does price affect expectations of service quality (Choi, Cho, Lee, Lee, & Kim, 2004). Additionally is the weight of perceived service quality of greater effect on satisfaction than price (Anderson, 1996; Brady & Cronin, 2001). Thus, cheap low quality services generally induce less satisfaction than expensive high quality service. In line herewith, is the strategic orientation of firms found to affect customer satisfaction (Wang et al., 2010). Standardization leads to less customer satisfaction than customization, because merely utilitarian needs are fulfilled (Simonson, 2005). Consumers with functional needs base their purchase on prices, rather than quality, as functionality of standardized services is perceived similar (Ryans et al., 2003). In turn, service quality forms the primal decision point for consumers with hedonic consumption, as they prefer sensorial and experiential service (Brown, 2018; Ding & Keh, 2016). Thus functional or hedonic preferences affect the way consumers are contented with high quality or low priced service (Ding & Keh, 2016). These preferences result in different levels of satisfaction, reiterating that the unequal effect of price and quality on satisfaction (Cronin et al., 2000). Customers who desire functionality at low price, still expected a minimal standard of service quality, Anderson and Mittal (2000) refer to this as the defection zone. On the other hand service quality needs to surpass the expectations of hedonic customers to reap benefits of service quality, what is referred to as the ‘trust zone’ by Anderson and Mittal (2000). To conclude, it could be argued that consumers of standardized service are less satisfied with functional service of low quality, even if price is down market. However, the competitive position of standardized firms is assured through absence of cheaper alternatives, assuring consumption by consumers with functional needs.

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10 & Cronin, 2001), which lead to lower marketing cost, and greater profit margins (Anderson, Fornell, & Lehmann, 1994; Homburg, Koschate, & Hoyer, 2005). Loyalty also benefits the customer lifetime value, considering that maintaining consumers is cheaper than attracting new consumers (Hassan, 2012). However, benefits of customer satisfaction are foremost based on the condition that firms strives to provide great service quality (Jiang & Wang, 2006). Which means that firms focused on functional quality have lower customer satisfaction and so experience lower firm performance. Therefore this train of thought has been questioned by previous researcher (Steven et al., 2012).

Conversely, standardized service firm benefit of customer satisfaction through a different mechanism. In order for standardized firms to be competitive, low cost through economies of scale is essential (Hill, 1998; Wang et al., 2010). This is done by reducing ancillary quality while maintaining functionality of services. This argument is the inverse to theory that argues that improving quality is exponentially increasing cost (Rust, Zahorik, & Keiningham, 1995). Arguably, standardization benefits when customer satisfaction is low, because low satisfaction, as previously concluded, is the result of functional fulfilment at the lowest cost for the consumer (Schmid & Kotulla, 2011). Accordingly, lower cost lead to competitive pricing and a better competitive position which contribute to more sales (Rust & Chung, 2006). To conclude, the way a strategic value proposition translates in to firm performance is dependent on the perceived value by customers, whose needs are functional or utilitarian in nature.

2.3. Hypothesis and conceptual model

Based on the literature review, customer satisfaction is hypothesised to mediate between firm strategy and financial performance. Performance can be explained through a strategy directly or through customer satisfaction. For

visualization the model is constructed in Figure 1. To test this model is hypothesized that; H1 Customer satisfaction mediates between firm strategy and firm performance.

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11 Additionally, two hypotheses are created, since the effect of customer satisfaction on performance is expected to be strategy dependent.

Customization strives to deliver high quality, resulting in a high perception of value and customer satisfaction. Thus a higher perception of value will strengthen the competitive position of a firm (Mekic & Mekic, 2014). Additionally, in line with the satisfaction profit chain of Anderson & Mittal (2000), customer satisfaction contributes to positive behavioural intentions towards a firm, including a feeling of loyalty and greater ascribed value (Hassan, 2012). These intentions strengthen long term financial performance of customized services. Resulting in the hypothesis that;

H2a Customer satisfaction has a positive effect on performance of customized service firms. Contradictory to customization, in the case of standardized service, customer satisfaction has a negative effect on performance. An increase of customer satisfaction would be the result of additional non-utility value. Which would incur additional cost, that are not recognized by their consumers. Therefore, customer satisfaction as a result of non-utility value will hamper the competitive position of standardized service. Hence customer satisfaction subverts the competitive advantage of standardization. And therefore, stating that;

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3. Methodology

The empirical testing of the hypotheses will be done with a case study of international passenger airlines. The airline industry is considered a favourable sample group for dichotomous strategy research, because the unique strategic division of the industry (Mellat-Parast et al., 2015). In addition, the market is international comparable, because the functional services are equal, so does each airline provides transportation between two destinations. Furthermore, international safety standards assure a minimal level of operations (IATA, 2016). Therefore, this industry allows to compare strategic facets of firms with international service standards.

3.1. Research setting

The airline industry provides a useful dichotomous setting through its unique strategic development. Since the 1960’s, the airline industry developed from a luxury service with governmentally controlled prices, into a freely regulated market (D’Alfonso, Malighetti, & Redondi, 2010). Early competition was based on quality, while price based competition only became possible international price legislation was lifted (Bitzan & Peoples, 2016). As a result new airlines started to undercut prices (Bitzan & Peoples, 2016), while older airlines maintained their strategy of high quality service because of high switching costs (IATA, 2017). This resulted in two value propositions in international aviation. In addition, price competition and technological development reduced operating costs. This development resulted in further polarization in two distinct airline strategies. Now passengers have the choice between; Full Service Carriers (FSC) who offer high quality customized service for a premium price or Low Cost Carriers (LCC) who offer standardized and cheap service. According to Borenstein (2011), ticket price differ by 50% up to 100% between the strategies. Regardless of price difference both strategies are deemed successful in a highly competitive market (Scotti & Volta, 2017).

3.2. Data collection and sample

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13 < 0,05 where considered acceptable (Bartlett, Kotrlik, & Higgins, 2001). Of the 579 airlines represented on TripAdvisor 183 airlines met the 150 review requirement at the time of collection. Lastly, the collection of financial data was conducted with Reuters Eikon database. Financial data was available for 112 of the 183 airlines, hereafter airlines which lacked more than half of the needed performance measures were omitted. Leaving a sample of 100 airlines, with 665.663 underlying reviews. Based on the strategic typologies the sample was divided in 42 LCC and 58 FSC.

3.2.1. DV Firm performance

In this paper firm performance is based on a combination of financial ratios. Financial ratios are preferred over non-financial measures, since operational differences between standardization and customization are foremost cost depending and therefore closer related to financial performance (Schmid & Kotulla, 2011).

Research on firm performance is divided by single- and multi-measure users, a single measure approach needs thorough theoretical underpinning to affirm correct results (Richard, Devinney, Yip, & Johnson, 2009). However, a multidimensional measure of performance provides a wholesome view on firm performance, and is less susceptible for misinterpretations than a single variable (Jusoh & Parnell, 2008). Hence a multidimensional measure is used in this paper, because it provides a more inclusive perspective on performance (Jusoh & Parnell, 2008).

Financial data was collected over the period 2012 until 2017, the financial ratios of each year were recalculated in five year averages to assure a balanced view on performance. This approach is preferred because it accounts for onetime events, fluctuations in performance data and missing years (Tsikriktsis, 2007).

Through a factor analysis the set of financial ratios was reduced into one variable, to create a multi-faceted view of financial performance ratios. The set of financial ratios is based on frequently used key performance indicators in the airline industry (Mellat-Parast et al., 2015). To avoiding the threat of internal performance focus on specific measures (Richard et al., 2009) and so enhancing the comparability of performance. An overview and expression of the used measures is presented hereunder.

Profit Margin (PM) is the net income / operating revenue. The net income is the

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The Pre-Tax Profit Margin (PTPM) measures the PM before deduction tax expenses

from the net income. By excluding taxes the margin becomes more objective, because international tax differences are eliminated (Schefczyk, 1993). Secondly, tax levels may have risen disproportionately between countries in the sampled period (IATA, 2016). Concluding that PTPM provides a more objective view on value creation than PM. On the other hand, excluding taxes gives an incomplete perspective on available margins to exploit, because firms with high taxes have less fund for future investments than firms with low tax rates. Hence the combined usage of PM and PTPM is justified through their complementary perspective on profitability.

Return on Assets (ROA) is expressed as earnings before interest and taxes (EBIT) / total

assets. The ROA gives expression to how effective a firm transforms its assets into income. It is therefore expected that firms with the ability to create relatively more value have a higher ROA (Sun & Kim, 2013).

Return on Capital Employed (ROCE). ROCE is the EBIT / capital employed. Like the ROA

the ROCE gives expression to the usage of assets. The capital employed are assets minus current liabilities. Satisfied consumers are found to pay their bills faster and so have a positive effect on the ROCE and firm performance (Kaplan & Norton, 2012). Sequential, a low ROCE indicates potential cashflow problems, because the account receivables decrease and the accounts payable increase.

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15 The outcome of the factor analysis with the previously defined ratios is presented in appendix Table 5. The factor analysis provided one dimension with an eigenvalue >1.0, and satisfactory Cronbach’s alpha (>0,70). The selected variables surpass the component loading requirement >0,50, failing variables would have been omitted. The output of the factor analysis is similar to the one by Devinney, Yip, and Johnson (2010), where ROCE, ROA and PM also loaded on one factor with component loading of >0,40.

3.2.2. IV firm strategy

Porters strategic typologies have previously used to segment airlines (Tiernan, Rhoades, & Waguespack, 2008). For this paper LCC, are associated with cost leadership and FSC to differentiation based on strategic and operational differences (Cento, 2009). On overview of strategic characteristics made by Mellat-Parast et al., (2015, p.17) is presented in appendix Table 6. Segmentation of the sample is based on prior research (Kos Koklic, Kukar-Kinney, & Vegelj, 2017; Mellat-Parast et al., 2015; Steven et al., 2012), this approach is combined with an overview of the International Civil Aviation Organization, who provide a detailed overview of LCCs (ICAO, 2017). Strategies are used as dummy variable with LCC as (0) and FSC as (1). Strategies are considered unchanged during the sampled period, since strategy specific assets make switching extremely costly (IATA, 2017) and complicated to communicate to consumers (Ellickson, Misra, & Nair, 2012).

3.2.3. Mediator Customer satisfaction

Levels of customer satisfaction of each airline are collected from the online review website TripAdvisor. The usage of online review platforms like TripAdvisor for data collection is emergent and provides new plausibility’s for research but also has limitations. For example, data on TripAdvisor is freely accessible, but the amount of variables are limited and origin of the reviews is opaque.

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16 TripAdvisor has multiple procedures in place, such as algorithms to assure legitimacy of reviews.

Online reviews websites such as TripAdvisor are a repository for a large amount of international customer reviews. But the number of variables freely available is limited. Although averages for satisfaction are provided, variables like demographics of each respondents are unavailable or require technical collection methods. The international scope of operations, covering multiple years of written and numerical reviews, and the potential to collect individual data make TripAdvisor a valuable source for data. Alternatively, the usage of self-administrated surveys allows for the collection of more diverse variables. But this approach is limited through cost and time and has a bounding effect on the sample size (Kos Koklic et al., 2017). Lastly, researchers could exploit governmental databases as proxy for service quality, however national collection are opaque and methods for collection may differ, hampering comparability (Anderson, Fornell, & Rust, 1997).

An example of how a survey is presented to a reviewee to in the case of an airline is shown in Figure 4. The survey asks the reviewee for an overall rating, followed by travel information. Secondly consumers can rate eight aspects of their service experience. These variables can be linked to Brady and Cronin (2001) dimensions of customer satisfaction; so do Legroom, Seat comfort and Inflight entertainment link to service environment; Customer service to employee interaction; Cleanliness, Food and Beverage, Check-in and Boarding to service quality. Lastly value for money, is not included in Brady & Cronin's (2001) work, but Messner (2018) links value for money to perceived value and customer satisfaction. Satisfaction is calculated for as the sum average of all variables. This approach provides data with two decimals, rather than the average provided by TripAdvisor, which are accurate to a half point. The weight of each variable on customer satisfaction is considered equal in this paper for two reasons. First the variables on TripAdvisor lack an underlying definition, and therefore hampering interpretation for weighting. Secondly, no study has been found to weight Brady and Cronin's (2001) or any other set of dimensions to customer satisfaction.

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17 method representative and consistent over time. Based on this condition the average satisfaction ratings of the eight American airlines were tested for correlation with 5 year average of the ACSI (2017). Pearson’s test showed a correlation of ,951 (P<0,01) as can be seen in appendix Table 10. Indicating that TripAdvisor reviews are a representative indicator of customer satisfaction for these American airliners.

3.2.4. Control variables

For this paper five control variables are used, which are believed to improve and clarify the relation between strategy, customer satisfaction and firm performance. All control variables are point in time observations collected in 2017, to assure the most recent and complete data. The sources and calculations of all variables can be found in appendix Table 4.

Alliance membership is believed to brings scale advantage to airlines (Kuzminykh & Zufan,

2014). More specifically the advantages come in the form of code sharing (Kuzminykh & Zufan, 2014), shared loyalty programs (Cento, 2009) and knowledge transferral. Code sharing entails that passengers of multiple airlines with similar service levels are transported by one operator. Thence create additional destinations and higher occupancy than a singular airliner could achieve. In turn, more destinations are considered a dimension of service quality, in addition higher occupancy results in higher profit margins. Membership in general was found more relevant to performance than membership to a specific alliance (Kuzminykh & Zufan, 2014). Therefore, alliance membership is presented as dummy with membership (1) or non-membership (0).

Founding year, is defined as the year an airline made its first flight under its current operating

name. With age firm experience increases, leading to better performance (Ismail & Jenatabadi, 2014). Meaning that older firms are more likely to have positive performance over time, including the capability to accounting for external events (Ismail & Jenatabadi, 2014). Instead newer firms are more likely to give up profit for market share (Devinney et al., 2010).

Fleet size represent the number of planes in use by an airline. The fleet size is used to give

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Fleet age average is an expression for the average age all planes in used by an airliner. Usage

of older planes is has a negative effect on profit margins (Zou, Yu, & Dresner, 2012), since older planes incur higher maintenance cost and are less fuel efficient (Waguespack & Rhoades, 2014). Thus, a younger average fleet creates a cost advantage.

Number of types represents the number of different airplanes a firm possess. Airlines with few

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4. Data analysis & results

In this chapter, the hypotheses derived from the literature review will be tested with the collected sample. With the usage of multiple linear regressions a mediating model will be constructed in accordance to the work of Baron and Kenny (1986). The interpretation of the results will be discussed in the following chapter.

4.1. Testing for assumptions

Prior to conducting linear regressions the data is tested for linearity, multicollinearity, normality and homoscedasticity. SPSS outputs for each test are provided in the appendixes.

Fist multicollinearity is tested to account for possible interrelation between the variables. The results are presented in appendix Table 7. The corresponding variance inflation factor (VIF) for all variables remained below the <5 threshold, which is considered acceptable (Hair, Black, Babin, & Anderson, 2010).

To test the data for normality, the Kolmogorov-Smirnov test is chosen to test this assumption rather than the Shapiro-Wilk test. This is because of the relatively small range of values, since the latter relies on a large range of values within the data. The results for firm performance and customer satisfaction in Table 8 fail to reject the null hypothesis, therefore the data is considered normally distributed.

To test homoscedasticity, Levene’s test is used to test whether the relation between customer satisfaction and performance have homoscedastic variance. The data is considered homoscedastic since the null hypothesis is not violated, see Table 9.

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4.2. Descriptive statistics

In Table 1, a snapshot of the descriptive statistics per strategy is provided. As expected, the average level of customer satisfaction for Low Cost Carriers (LCC) (3.547) is lower than for Full Service Carriers (FSC) (3.721). On average FSC are 39 years older and have a fleet that is almost double in size compared to LCC. In addition, FSC have a more diverse collection of airplanes than LCC, indicating more cost efficiency and less flexibility of the latter. Lastly, the performance factor indicates better performance for LCC, on average scoring 0,233 while FSC score -0,169. In return the standard deviation of performance is greater for LCC than for FSC, indicating more variation among LCC.

Table 1, Descriptive statistics per strategy

N Minimum Maximum Mean Std. Deviation

LCC FSC LCC FSC LCC FSC LCC FSC LCC FSC

Firm Performance 42 58 -2,72 -2,87 2,17 1,96 ,233 -,169 1,078 0,883 Customer satisfaction 42 58 2,62 2,90 4,39 4,36 3,547 3,721 ,495 0,429

Alliance dummy 42 58 0 0 1 1 ,023 ,689 ,154 0,467

Founding Year 42 58 1965 1919 2013 2005 1996 1958 11,9 25,6 Fleet age Average 37 58 2,80 4,10 22,4 20,4 8,53 9,95 4,50 3,58

Number of Types 38 55 1 1 6 12 2,42 5,47 1,348 2,364

Fleet size 40 58 2 9 717 950 96,47 173,9 126,1 208,3

4.3. Correlation

The correlation presented in Table 2 matrix includes both strategies. In addition, the correlation matrix for each strategy is presented in Appendix Table 11 and Table 12. Missing variables have been removed pairwise, rather than replaced with the mean due to technical limitations. With respect to the entire sample, some characteristics of strategic orientation become apparent in the correlation matrix. So is alliance membership predominant among FSC, furthermore are FSC significantly older and have a more diverse set of planes. Lastly, fleet size has a strong correlation with firm performance.

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Table 2, Correlation matrix

1 2 3 4 5 6 7 8 1 Strategy 1 -,203* _,186 _,668**_-,686** _,210* _,198 _,602** 2 Firm Performance -,203* ₁ _-,025 _-,159 _{,005 ,331}** _,002 _,014 3 Customer satisfaction ,186 -,025 1 ,183 -,215* _,031 _-,015 _,131 4 Alliance Dummy ,668** _-,159 _,183 _{1 -,447}**_,315** _-,023 _,635** 5 Founding Year -,686** _{,005 -,215}*_-,447** _{1 -,240}*_-,313**_-,531** 6 Fleet size ,210*_,331** _,031 _,315** _-,240* ₁ _,034 _,552**

7 Fleet age Average ,198 ,002 -,015 -,023 -,313** _,034 ₁ _,124 8 Number of Types ,602** _,014 _,131 _,635**_-,531**_,552** _,124 ₁ *. Correlation is significant at the 0,05 level (2-tailed).

**. Correlation is significant at the 0,01 level (2-tailed).

4.4. Results

The usage of a linear relation is common in satisfaction research (Mellat-Parast et al., 2015), although Anderson and Mittal (2000) argue for a non-linear relation, as the effects of customer satisfaction are not infinite. Despite a linear regression model will be used to test the results, in accordance to the test for linearity between de mediator and dependent variable. To account for operational differences control variables will be added. Herewith controlling for performance that is not related to firm strategy. Mediation will be tested in line with the method of Baron and Kenny (1986). There is chosen to conduct an additional test between customer satisfaction on performance, as preliminary test in regard to hypotheses 2a and 2b. The models in Table 3 correspond to the formulas 1 until 4 to test for mediation. Wherein

Y

represents firm performance,

M

customer satisfaction and

X

firm strategy.

Formula 1 Y=b

0

+b

1

X+e

Formula 2 M=b

0

+b

1

X+e

Formula 3 Y= b

0

+b

1

M+e

Formula 4 Y=b

0

+b

1

X+b

2

M+e

The following results are deducted from Table 3, Linear regression model.

Model 1 shows that strategy has a negative significant (P<,10) effect on firm performance. Providing that FSC have lower performance than LCC, when controlling for non-strategic factors that influence performance.

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22 In model 3 no effect of customer satisfaction on firm performance is found, although firm size and alliance membership do have a significant effect. In model 3a and 3b both strategies were tested independently. Results show a positive significant (P<,05) effect between customer satisfaction and firm performance for FSC and a negative significant (P<,10) effect for LCC.

In model 4 the mediating effect of customer satisfaction is tested between firm strategy and firm performance. The outcome shows no mediated effect by customer satisfaction, since the effect of strategy on performance remains unchanged with the introduction of customer satisfaction in to the regression.

Table 3, Linear regression model

Model 1 Model 2 Model 3 Model 3a Model 3b Model 4 Dependent variable Firm

performance

Customer satisfaction

Firm

performance

Firm performance Firm

performance LCC FSC Firm strategy -,275* ,186* -,275* -(1,789) 1,875 -(1,780) Customer satisfaction ,009 -,283* 0,278** ,010 (,091) -(1,787) (2,239) (,106) Control variables Alliance membership -,149 -0,267** -,161 -,129 -,150 -(1,087) -(2,172) -(1,002) -(,936) -(1,086) Founding year -,180 -,065 -,166 -,131 -,178 -(1,374) -(,545) -(,870) -(1,044) -(1,338) Fleet size ,420*** ,452*** ,348** ,664*** ,421*** (3,772) (4,036) (1,893) (4,100) (3,754)

Fleet age Average -,009 -,026 ,082 ,089 -,008

-(,088) -(,261) (,541) (,660) -(,081) Number of Types -,060 -,103 ,090 -,235 -,060 -(,423) -(,723) (,563) -(1,334) -(,419) N 100 100 100 42 58 100 Model F statistic 4,257*** 3,517* 3,016** 1,758* 4,240** 3,611** Model R2 _,215 _,035 _,189 _,232 _,333 _,216 Adjusted R2 _,165 _,025 _,136 _,100 _,254 _,156 *** P<,01 ** P<,05 * P<,10 (two-tailed)

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5. Discussion

The aim of this paper is to empirically test the mediating effect of customer satisfaction between firm strategy and firm performance. The literature review of this paper argues that economy of scale, the strategic benefit of standardization, is conflicting with the general notion that value enhancements improves firm performance. The argument for the negative effect of customer satisfaction is built on the concept that consumers differ in needs and preferences (Ding & Keh, 2016; Jiang & Wang, 2006). Presuming consumers with functional needs prefer utility services for the lowest price. As a result, standardized firm who offer cheap functional quality have less satisfaction consumer, but also a competitive position because of their low pricing. In contrast customization serves needs of hedonic consumers, these consumers desire satisfaction and service quality, therefore the competitive position of customization is high when customer satisfaction is high.

Previously, customer satisfaction is considered to affect performance. Therefore customer satisfaction is frequently used as indicator for performance (Behn & Riley, 1999), with the assumption of an unconditional positive effect. However, understanding in what way customer satisfaction affects performance is even more relevant for managers, investors and academics to optimize levels of satisfaction of make assumptions accordingly. This paper provides improved understanding for assumptions about satisfaction.

In addition, testing the effects of a value propositions in the service industry is relevant because of the subjective perception of value. The different perceptions of consumers make measuring service quality more difficult compared to tangible products.

5.1. Theoretical contribution

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24 Model 1 shows that performance between strategic orientations differs. Standardization is found to perform better than customization in a sample of international passenger airlines, contrasting with Porter’s argument for equivalent performance. Low Cost Carriers (LCC) have better performance than Full Service Carriers (FSC) with moderate significance (P<0,10). This result is contradicting to Porters (1996) theorization of equal performance of both generic strategies. Differences in performance could be explained through the control variable firm size. The correlation matrix shows that fleet size, is significantly (p<0,10) larger for FSC than for LCC. In addition, does firm size positively (P<0,05) related to firm performance. Hence FSC do not benefit of their scale advantage. Presumably a strategy of value creation has become less effective, as the aviation market is commoditizing (Curry & Gao, 2012). Thus, the benefits of customization, associated with economy of scope, are less successful in the sample. On the other hand, these results support the benefits of standardization in service, as it achieved better financial performance with less resources.

In accordance to general view on the development of customer satisfaction, model 2 confirms that customized service leads to higher levels of customer satisfaction, with moderate significance. Concurring with general research (Choi et al., 2004), that greater service quality leads to more satisfaction, despite higher prices. This finding is in line with the service profit chain (Homburg et al., 2009), that greater service quality results in more satisfaction, through higher perceived value. Greater value allows firms to charge higher prices for their services (Homburg et al., 2005) and to move away from commoditization (Reimann et al., 2010). Higher perceived value could be considered a win-win for consumers and firms, if satisfaction is worth the costs for consumers.

Model 3 shows a non-significant effect of customer satisfaction on firm performance, while control variables fleet size and alliance membership have a significant effect. Potentially the effects of customer satisfaction of both strategies cancel out. An explanation could be sought in the outcomes of the additional test.

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25 These results contradict with recommended from previous research to incorporate customer satisfaction in analysis of firm performance (Behn & Riley, 1999). Since low levels of customer satisfaction would be the result of service failure and complaints and so reduce performance. However, the results support hypothesis 2a and 2b, that customer satisfaction has a negative effect on firm performance of standardized service and positive effect for customized service. Therefore, this paper suggests future research to reconsider the unconditional benefits of customer satisfaction.

Contrary, Mellat-Parast et al., (2015) find that indicators for dissatisfaction such as service failure and complaints, have a more negative effect on the firm performance of LCC than of FSC. They explain this through the flexibility of FSC, who are more capable to absorb operational problems comparted to LCC, who run a thigh operating scheme. The contradiction in results could be explained by the objective quality measures used. Most likely does service failure have a more negative effect on the satisfaction of FSC customer, because they expect higher quality than customer of LCC. That service failure, hence low customer satisfaction has negative effect on the performance of FSC, is congruent with this research.

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26 benefited from economies of scope or benefits of customization are supported by economies of scale. To deduct from this discussion, economies of scale are more relevant for performance, as opposed to economy of scope in a commoditized service industry. A focus on value creation and customer satisfaction is less successful in this sample.

5.2. Managerial implications

The results provide a complementary view to current knowledge for theorist and managers, by showing that customer satisfaction does not explain the relation between strategic orientations and financial firm performance. Benefits of customer satisfaction seem to cancel out through their contradicting effect. As is shown in the strategic dependent effect of customer satisfaction on firm performance. Therefore, understanding the strategic orientation of a firm is vital before interpretations are made to optimize satisfaction levels. Hence without clear strategic understanding any interpretations made regarding levels of customer satisfaction will have a random effect. In addition, the benefits of customization are unclear, as they do not exploit their size difference, while also the benefits of additional value do not add to superior firm performance.

Implications for aviation are based on two aspects, strategy and customer satisfaction in a commoditized service industry. First, regarding strategy, standardization achieved moderately better firm performance than customization. Even though standardization could not exploit the same size benefits as customization. Therefore, concluding that the value creation strategy of FSC is supported by a scale advantage. One the other hand, the efficiency of operations is more important for LCC than for FSC. Seemingly does a strategy of standardization create larger margins with less resources. The performance of FSC could be explained in two ways, either FSC benefit solely of customization or customization is supported by economies of scale.

Secondly, despite signs of commoditization, some consumers desire to be satisfied, rather than merely have their needs fulfilled. The effect of customer satisfaction on financial firm performance is positive for customization, while customer satisfaction works against the benefits of standardization. Based on different consumer needs both strategies have their own reason of existence. Therefore, managers in the airline industry are advised to optimize operations to their strategic orientation.

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27 strategic orientations in the general service industry are not so clear-cut as in aviation. Though appraisal of value happens post consumption with each service. Herewith customer satisfaction remains a useful tool to measure the effect of a value proposition. Maintaining that firms can optimize their operations to a strategy.

Lastly, I expect the results to have limited extendibility in to tangible consumer products, because the perception of value is objective. As such consumers are more capable to compare products prior to consumption. Therefore, the development of value will happen prior to consumption rather than after. Which is a fundamental difference in the effect of customer satisfaction.

5.3. Limitations and future research

The following notions are considered regarding the empirical tests. In the first place the source for customer satisfaction, reviews on TripAdvisor have thus far rarely been used as proxy for customer satisfaction. The following drawbacks for TripAdvisor are encountered; first the set of variables available provided is limited information on demographics. Secondly there is limited prove for the reliability of online reviews. Lastly the weight of each variable to measure customer satisfaction is unknown. Solution to counter these issues have been provided in this paper.

The usage of the international airline industry as sample has some limitations, despite the highly competitive industry, a few major players compete with many smaller firms. The difference in size hampers the comparability between airlines, therefore fleet size is used as proxy to control for firm size. The results show that firm size is of high explanatory value in each tested model.

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28 deviations in strategic orientation would improve the generalizability of this research, as most service industries do not have as distinctive strategic orientations. Besides this approach would require a formal model to determine deviation of strategies.

Future research could test the mediation effect of customer satisfaction on performance with a scaled version of strategic orientations. Therefore, is proposed to create strategic scales with a factor analysis, this approach would be similar in fashion to the approach of Wang et al (2010). Preferably, the developed method is applicable to multiple industries, this would allow managers to determine the strategic orientation of their firm. So optimal levels of customer satisfaction can be set accordingly.

Secondly, the effects of customer satisfaction are found to be strategy depend. The effects would be readily observed in a moderating model. Contrary to the mediated approach used in this paper, as the effects of customer satisfaction cancel out in a mediating model. Therefore individual test were used to expose this difference in this paper.

Third, the relation of strategy and satisfaction on firm performance could be extended to tangible consumer products in future research. As the results are expected to differ compared to intangible products. Since the appraisal of product quality can generally be determined in an objective way (Ding & Keh, 2016).

In addition, TripAdvisor or other online review platforms could be a valuable source of data for future research. As online review platforms provide an easily accessible and extensive collection of reviews. However, the current lack of proven reliability seems to withhold its usage. This issue would be solved by testing online reviews for reliability with existing data sets.

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30

6. Conclusion

With this thesis I want to attest a contradiction in current literature, that customer satisfaction has a positive effect on firm performance regardless of a strategic orientation. To do so, the literature review of this paper provides an argument why the effect of customer satisfaction on firm performance should be considered to mediate between strategic value propositions. The underlying benefits of each strategic value proposition are linked to functional and hedonic consumer needs. Arguing that standardized services have a successful competitive position when only functional needs of consumers are fulfilled, at the lowest cost. In turn customization benefits from greater satisfaction through price and quality enhancement The mediating effect of customer satisfaction was tested with multiple linear regressions. Although no mediation effect is found, airlines with standardized service have moderate significant better long term financial performance than customized providers, despite a scale advantage of the latter. The result provides a new perspective on the benefits of strategic orientations for both academics and managers. Contradictory to theory, results show that commoditization is unable to exploit scope benefits despite size advantages, while standardization has better performance with less resources. Additional tests show that customer satisfaction affects firm performance of a strategic orientation. Future research is needed to find optimal levels of customer satisfaction in relation to firm performance for standardization and customization. To conclude, the discussion and outcomes of this paper provide a first step towards future research, to test the value of customer satisfaction for strategies in the service industry.

Acknowledgments

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8. Appendix

Table 4, Sources of variables

Variable Description Source

Independent Strategy ICAO, list of LCC carriers (2017)

IATA, is airline competion a myth (2017)

Mediator Satisfaction TripAdvisor

(collection 5 and 5 April 2018) https://www.tripadvisor.com/Airlines

Dependent variable Profit margin EIKON Database

(collection between 11 May 2018) Pre-tax profit margin EIKON Database

(collection between 11 May 2018) Return on capital employed EIKON Database

(collection between 11 May 2018) Return on assets EIKON Database

(collection between 11 May 2018)

Control variables Alliance dummy IATA

(Kuzminykh & Zufan, 2014) Amount of reviews TripAdvisor

Founding year Annual report

www.planespotters.net (accessed on 4-4-2018) Fleet size* (2017) www.planespotters.net (accessed on 4-4-2018) Average fleet age (2017) www.planespotters.net (accessed on 4-4-2018)

Planespotter.net is a free-to-use website that collects data from official government agencies and secondary news sources.

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Table 5, Factor analysis, firm performance

Component Matrix _Component _{Cronbach's alpha}

Factor 1

Pre-tax profit margin ,815 0,811 Return on Assets ,812

ROCE ,544

Profit Margin ,519

Extraction Method: Principal Component Analysis >.50

Table 6, Airline strategy characteristics

Characteristic LCC FSC

Route structure Point-to-point Hub and spoke

Customer base Economy Personalized convenience International coverage Low High

Strategic alliances Low High

Size Medium Large

Table 7, Multicollinearity regression, dependent variable

Tolerance VIF

Strategy ,459 2,179

Customer Satisfaction ,919 1,089 Founding Year ,474 2,109

Fleet size ,426 2,347

Fleet Average age ,895 1,117 Number of Types ,453 2,206 a. Dependent Variable: Firm Performance

Table 8, Tests of Normality, Kolmogorov-Smirnov

Statistica _dfa _Sigicance a

Customer Satisfaction ,069 100 ,200*

Firm Performance ,086 100 ,067 *. This is a lower bound of the true significance. a. Lilliefors Significance Correction

Table 9, Levene's Test of Equality

Levene Statistic P Customer Satisfaction ,879 ,351

Firm Performance 1,845 ,177

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Table 10, Correlation ACSI, TripAdvisor

ACSI 5 year average TripAdvisor JetBlue 4,1 4,2 Southwest 4,0 4,4 Alaska 3,8 4,3 American 3,5 3,3 Delta 3,6 3,9 United 3,2 3,2 Frontier 3,1 2,7 Spirit 3,0 2,6 Pearson Correlation 0.951** ** Correlation significant at 0.01 level (2-tailied)

Table 11, LCC Correlation matrix

1 2 3 4 5 6 7 1 Firm Performance _{1 -,147 -,054} _-,303 _,369*_{,030 ,063} 2 Customer satisfaction -,147 1 -,210 -,050 ,227 ,156 ,058 3 Alliance Dummy -,054 -,210 1 -,288 .a _.a _.a 4 Founding Year -,303 -,050 -,288 1 -,516**_{,026 -,229} 5 Fleet size ,369*_,227 _.a_-,516** _{1 ,010 -,113}

6 Fleet age Average ,030 ,156 .a _,026 _,010 _{1 -,118}

7 Number of Types ,063 ,058 .a _-,229 _{-,113 -,118} ₁

*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).

a. Cannot be computed because at least one of the variables is constant.

Table 12, FSC Correlation matrix

1 2 3 4 5 6 7 1 Firm Performance _{1 ,176 -,032 -,205 ,444}** _,065 _,239 2 Customer satisfaction _,176 ₁ _{,174 -,139 -,117 -,256 -,007} 3 Alliance Dummy -,032 ,174 1 ,043 ,269*_-,320*_,421** 4 Founding Year -,205 -,139 ,043 1 -,080 -,286*_-,207 5 Fleet size ,444**_{-,117 ,269}*_-,080 _{1 -,015 ,696}**

6 Fleet age Average ,065 -,256 -,320*_-,286*_-,015 ₁ _,091

7 Number of Types ,239 -,007 ,421**_{-,207 ,696}** _,091 ₁

Does customer satisfaction mediate between strategy and performance?