When co-production fails: The role of customer’s internal attributions and impression management concerns
Introduction
Co-production is defined as customers’ applying operant resources such as effort, skill, and knowledge to involvement in the creation of products and services (Prahalad and Ramaswamy, 2004, Vargo and Lusch, 2004, Vargo and Lusch, 2008). Co-production has been considered the next frontier in terms of firms gaining competitive advantages because it can enable them to benefit from utilizing a diverse and invaluable set of customer resources (Madhavaram & Hunt, 2008). Therefore, research efforts across several disciplines have sought to improve the understanding and management of co-production processes (Bendapudi and Leone, 2003, Galvagno and Dalli, 2014, Gamble and Gilmore, 2013, Kull and Heath, 2016, Voorberg et al., 2014). However, this body of research has remained skewed towards positive and successful co-production endeavors, and has paid limited attention to co-production failures (Dong et al., 2008, Heidenreich et al., 2015). It is critical to rectify this imbalance in order to ensure that the adoption of co-production in practice is well-informed (Palmisano, 2010, Schaefer and VanTine, 2010).
Recent studies on failure of co-produced products and services have examined customer’s attributions, satisfaction levels, and equity evaluations (Dong et al., 2008, Heidenreich et al., 2015, Zhu et al., 2013). In contrast to the dominant expectation of the self-serving bias and the fundamental attribution error, which attributes failures of co-production to the firm, Heidenreich et al. (2015) and (Sugathan et al., 2017a, Sugathan et al., 2017b) found that failures of co-production result in internal attributions because co-producers might partially put the blame for the failures on themselves. Further research into this process will help advancing an understanding of the different types of attributions that characterize co-production failures, boundary conditions (key moderators and contingencies), and the prediction of other key customer outcomes (adaptive versus maladaptive behavior). To achieve these goals, we: (1) apply a more nuanced view of how attribution theory relates to failures of co-production, (2) assess the post-failure behaviors of co-producers across two critical behavioral operant resources – consumers’ efforts and abilities, (3) examine these behavioral operant resources from the theoretical perspectives of entity theory and incremental theory, and (4) study social presence during co-production as a mechanism to alter post-failure behaviors and thereby check possible adverse implications for the firm (as described by impression management theory).
Thus, we build our research on failures of co-production in three ways (see conceptual framework, Fig. 1). First, we provide a detailed examination of how different types of internal attributions for these failures will influence consumers’ intentions towards future co-production. Therein, we show how an individual’s attribution to effort and abilities during the co-production task influences her or his subsequent intention to increase effort, seek assistance, and avoid similar failures. Second, an analysis of ability to perform the co-production task provides novel insights into the design of co-production tasks. Customers are hesitant to co-produce after failing at a task they perceive requires an ability that is difficult to learn. Third, we detail a mechanism that results in shift in internal attribution during the co-production process due to the effect of social presence that can restrain the consumer hesitation and encourage them to participate in co-production. Therein, we show that social presence may reverse the influence that ability attribution to a failed co-production task may have on future intentions to co-produce.
Section snippets
Theory
Attribution theory offers insights into the causal explanations by individuals for their life events including products or service failure. Attributions have been classified as internal/external and stable/unstable. We specifically focus on the dimension of internal attribution in light of recent research which suggests that customers attribute failures of co-production internally to themselves (Sugathan et al., 2017a) In the event of failure, customers tend to attribute the failure to the
Hypothesis development
In normal situations of product or service failures, consumers usually have a self-serving bias and make the fundamental attribution error, which leads them to attribute the failures to external sources (including the firm or the brand) as an ego-defense (Miller & Ross, 1975). However, when customers are involved in product creation, the reason for failure becomes more accessible to them, mitigating the fundamental attribution error. Thus, customers might internally attribute failure to
Methodology
The hypotheses were tested across two independent studies. Consumers’ beliefs in relation to entity or incremental theory were manipulated through contextual features in the experimental vignettes that stimulated the salience of one belief over another (Butler, 2000, Dweck et al., 1995). As entity theory explains individual characteristics such as intelligence and creativity, whereas incremental theory explains effort or physical ability, we designed two different studies to manipulate the two
Discussion
It is now important to reconsider two questions that were posed at the beginning of this study. The first question asked how customers’ internal attributions influence future behavioral intentions subsequent to a failure of co-produced products. We try to answer this by studying the influence of the two major classifications of internal attribution: internal-stable and internal-unstable. Co-production requires customers’ operant resources, such as effort, ability, and knowledge. We consider the
Future research
The main drawback associated with scenario-based experiments is the greater likelihood of the demand effect and participants’ inability to respond as they actually would in a real situation. While strict contextual and experimental setting enables ‘understanding’ of causal relationships by minimizing ‘possible contingencies’ (Lewin and Sager 2007, p. 1220) and allow control of confounding effects (Singh, Goolsby, and Rhoads 1994), it limits generalizability as well as external validity.
Praveen Sugathan is an Assistant Professor in Marketing at Indian Institute of Management (IIM) Kozhikode, India. He focuses on research in services marketing and online consumer groups. He has published his works in Journal of Business Research, Journal of Interactive Marketing, Journal of Services Marketing, and European Journal of Marketing. He has presented his works in conferences of American Marketing Association, Academy of Consumer Research, Academy of Management, Academy of
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Praveen Sugathan is an Assistant Professor in Marketing at Indian Institute of Management (IIM) Kozhikode, India. He focuses on research in services marketing and online consumer groups. He has published his works in Journal of Business Research, Journal of Interactive Marketing, Journal of Services Marketing, and European Journal of Marketing. He has presented his works in conferences of American Marketing Association, Academy of Consumer Research, Academy of Management, Academy of International Business.
Kumar Rakesh Ranjan is an Senior Lecturer in Marketing at Business School, University of Queensland. His research investigations include social media and electronic word-of-mouth, co-creation, service interaction quality, and performance issues in sales channels. He has published at the Journal of the Academy of Marketing Science, Journal of Business Research, Journal of Interactive Marketing, and European Journal of Marketing.