Does competitive aggressiveness negatively moderate the relationship between coopetition and customer satisfaction performance?

ABSTRACT

Although the existing marketing literature suggests that coopetition (simultaneous cooperation and competition) drives customer satisfaction performance, it is unclear whether hostile relations between industry rivals distorts this link. Thus, under resource-based theory and the relational view, this current paper examines the coopetition – customer satisfaction performance relationship under different degrees of competitive aggressiveness. Survey responses were obtained from a sample of 101 small wine producers in New Zealand, with such data passing all major reliability and validity checks (and common method bias). The results indicated that while coopetition has a positive association with customer satisfaction performance, this link is negatively moderated by competitive aggressiveness. These findings emphasise that on its own, coopetition is comprised of balanced levels of cooperativeness and competitiveness. Yet, competitively aggressive behaviours serve as firm-wide actions that can unhinge the coopetition paradox and prevent businesses from satisfying their customers’ wants and needs.

KEYWORDS:

• Coopetition
• customer satisfaction performance
• competitive aggressiveness
• resource-based theory
• relational view

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. There are various ways to measure performance (Katsikeas et al., 2016). In this current study, customer satisfaction performance was chosen as the outcome variable (Hooley et al., 2005; Vorhies & Morgan, 2005). In turn, this allowed the evaluation of whether coopetition activities help organisations to satisfy the wants and needs of their target markets (O’Dwyer & Gilmore, 2018; O’Dwyer et al., 2011). Customer satisfaction performance is different to customer value creation (Ho et al., 2006). Customer value refers to the total benefits that customers receive for a good or service, minus the costs that must be incurred to experience such an offering (Crick, 2021; Kumar & Reinartz, 2016). Hence, customer satisfaction is only one facet of customer value, meaning that the latter construct is not conceptualised, measured, or tested within this investigation. The author thanks an anonymous reviewer for requesting clarity on this matter.

2. As an important point, earlier work has found that coopetition is likely to positively impact various assessments of company performance (Bengtsson & Raza-Ullah, 2016; Czakon et al., 2020). Far less research has accounted for the moderating factors that might be at play (Crick, 2019; Hoffmann et al., 2018; Shu et al., 2017). Thus, this current article focuses on the moderating role of competitive aggressiveness as a rivalrous force that could distort the interplay between cooperation and competition. Yet, to evaluate this moderator, the main (direct) path needed to be conceptualised and tested. Consequently, the core contribution surrounds the potential interaction effect from competitive aggressiveness, as opposed to the somewhat basic (non-contingent) coopetition – customer satisfaction performance relationship. The author is grateful for an anonymous reviewer for suggesting that this point should be clarified.

3. Other studies have tested relatively complex models (i.e., with more parameters than this current investigation’s conceptual framework) with fewer than one-hundred participants (e.g., Keinanen & Kuivalainen, 2015; Moorman, 1995). Henceforth, the 101 responses were deemed to be sufficient. For extra assurance, later sections of this paper highlight that certain statistical tests were undertaken to check whether enough survey data had been collected – revealing no concerns. The author offers thanks to an anonymous reviewer for suggesting that more detail should be provided on the respectability of the final sample size.

4. Before any statistical techniques were undertaken, a missing value analysis was conducted to treat the small amount of missing data – using expectation maximisation (via SPSS 23). This involved replacing these missing values with the averages for each column of data (Kim & Lee, 2011). This ensured that the final dataset was complete. In addition, while this current study makes a unique contribution to the marketing literature (through the constructs being evaluated), this dataset has been utilised in other papers in different capacities. The author thanks an anonymous reviewer for requesting more information on this matter.

5. As a supplementary test, a ‘spotlight analysis’ was conducted on the interaction effect (Irwin & McClelland, 2001). Through SPSS 23, the moderator (competitive aggressiveness) was assessed at low-levels and high-levels, namely, one standard deviation (1.04) below and above the mean (2.01) (Guo, 2013). Next, this information was inputted into a software package (Microsoft Excel) that calculated the moderating effect at these different degrees (Dawson & Richter, 2006). Then, a graph was plotted that showed the values of the slopes of the interaction effect (Cadogan et al., 2012). Importantly, there is not a single-agreed way to use a ‘spotlight analysis’ (Spiller et al., 2013). Hence, this technique was used as a statistical reinforcement, with more emphasis being placed in the hierarchical regression model (Morgan et al., 2009). The author expresses gratitude to an anonymous reviewer for recommending that a ‘spotlight analysis’ should be undertaken.