INTRODUCTION

Intensified competition puts pressure on organizations to outperform their competitors by addressing customer needs in superior ways. To increase their ability to fulfill customer demands, firms are becoming more and more aware of the need for overarching change, converting to decentralized structures and abandoning hierarchical organizational forms in favor of flattened hierarchies and massive use of self-managing teams. This has resulted in several organizations moving from traditional, planning-intensive and linear development approaches to more iterative and self-organized approaches inspired by Agile methodologies (e.g., Martin, 2003).

The popularity of Agile methods has grown, especially in relation to technology projects, which are designed to address high volatility in the market environment (Lindvall et al., 2002). They are able to cope with the different types of changes that occur in projects, in relation to: (i) goals; (ii) materials, resources, tools, and techniques; and (iii) relationships with other projects, services, or products (Collyer et al., 2010). Consistent with this, Williams and Cockbum (2003, p. 39) define Agile software development as being “about feedback and change,” and argue that Agile methodologies have been conceived to “embrace, rather than reject, higher rates of change.”

Despite the increased adoption of Agile by companies, clear and detailed recommendations about how to drive autonomous teams towards successful high innovative performance are lacking. The attention in research on Agile methodologies focuses on the introduction and adoption phases of Agile (Dyba & Dingsoyr, 2008), rather than on the long-term effects of Agile implementation and the impact on innovation (Abrahams- son et al., 2009).

Agile methods are appropriate to foster innovation and creativity and to explore new fields (Highsmith, 2002). The autonomy and self-organization among team members provides conditions conducive to the development of learning capabilities and solving problems through creativity (Imai et al., 1984), and renders team members more open to novel ideas (Lyytinen and Rose, 2006). In addition, creativity and innovation are favored by the fact that Agile creates a balanced but not fully structured context (Highsmith, 2002).

However, in such a context, the social aspect is fundamental. Agile software development methods emphasize teamwork (Nerur and Balij- epally, 2007) in contrast to the plan-driven development approach which foresees individual role assignment (Nerur et al., 2005).

Integrating individual knowledge is not sufficient to generate innovative ideas if the team environment does not provide the proper conditions to allow team members to develop the ability and motivation to use their potential (Aalbers et al., 2013; Shin et al., 2012). The generation of team- level knowledge is derived from the joint effect of members’ individual personal characteristics and their belonging to a social context (Shalley et al., 2004). In order to create and act on teams’ internal knowledge and individual innovative ideas, team members need to share their thoughts with their peers, and to sense and seize other members’ insights to create proper associations which potentially could result in the creation of workable solutions (Baer et al., 2010; Harrison and Rouse, 2014). Consequently, we argue that a relevant part of a team’s self-regulated innovation activities stems from established social interaction processes and norms which act as source of influence that guides the behavior of team members.

A team’s social behavior is influenced heavily by the team norms to the extent that team members adopt a relevant group identity (Cialdini and Trost, 1998). Team identification is responsible for the development of injunctive characteristics based on the perceived sanctions associated with conformity to or violation of these norms (Cialdini and Trost, 1998). Specifically, using the theoretical lens of self theories (Dweck, 2000; Dweck and Molden, 2005), it is seen that injunctive norms constitute self-standards that identify whom people ideally would like to be or whom they ought to be (Higgins, 1987; Moretti and Higgins, 1999; Schwartz, 1977; Schwartz and Fleishman, 1978). However, in contrast to the explicit sanctions imposed by injunctive norms, descriptive norms provide insights into the group’s typical conduct: they provide information on what team members are really doing allowing identification of group adaptive behaviors (Cialdini et al., 1991). Descriptive norms may not reflect the favored identity, with the result that the process guiding the impact of descriptive norms may differ from that guiding the team’s injunctive norms. Consequently, both types of norms are salient for identifying the group’s behavior and predicting any kind of committed team action.

Based on this reasoning, this chapter analyzes the roles of two types of norms, descriptive and injunctive, to predict team innovation activity. It examines the nature of the stimuli likely to lead to the formation and activation of these norms, and determining the conditions in which a unique effect of Agile work routines and managerial practices will emerge. This chapter also emphasizes the influence of the source of these norms— whether they are promoted in-group (i.e., the group to which the individual belongs) or out-group (i.e., in another group than that to which the individual belongs but which forms part of the surrounding social environment such as team stakeholders and manager). This differentiation might explain why individuals might respond differently to injunctive and descriptive norms as a function of whether the norms are in-group or outgroup. This also highlights the roles of the team’s executives and leaders, and allow us to propose a new approach to managerial organizational controls as crucial determinants of the functioning of organizational units and firm performance (Loughry and Tosi, 2008; De Jong et al., 2014), which can replace the close monitoring and supervision imposed by social-ideological modes of control.

Additionally, the chapter analyzes the relationships between descriptive and injunctive norms, underlining their interactive effect on team behavior, demonstrating the importance of injunctive norms, and identifying the environmental conditions that make injunctive norms more important in an Agile context.

The chapter builds on the results of a four-year study of hundreds of teams in several organizational units dealing with product development. Initially, we ran a pilot study in a small research and development (R&D) organization; we then conducted 17 group interviews and an exploratory survey, plus three follow up meetings in three bigger R&D organizations to discuss the relevant findings. This allowed us to scale up the analysis to involve an entire product development unit comprising four large R&D departments and a total of 1,700 employees. We interviewed 44 individuals selected from different hierarchical levels and functions. Finally, we launched a global, multilevel and multisource survey involving participation of 20 different R&D organizations in 11 countries, including the members of 97 teams and their team managers, plus their higher-level managers in the related organizations. Our main research methods used grounded theory, cross-case analysis, triangulation, and linear and hierarchical linear regression models. We collected organizational documentation from each organization involved which constituted a valid source of secondary data.

The remainder of this chapter is structured as follows. We outline the general concept of team innovation, and accompanying team norms and peer pressure (sections Teams and innovation and Team norms). We discuss complementarity among control mechanisms, and describe Agile methodologies to provide the research setting for this research (section Agile Software Development). We integrate and apply the theoretical logics of social identity and stakeholder theory with control mechanisms to explain how combinations of controls operate to affect a team’s selfregulated learning process. On this basis, we develop a conceptual model that captures how combinations of norms and peer pressure affect team’s self-regulated learning strategies, and ultimately, team innovation performance (sections Team descriptive norms’ influence over individual social conduct for innovation and Influence of Team injunctive norms on individual social conduct for innovation).

 
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