Building manufacturing flexibility with strategic suppliers and contingent effect of product dynamism on customer satisfaction

Highlights

• Applies SEM and MGCFA to a sample of 155 companies.

• Demonstrates the important role of upstream relationships for flexibility.

• Inter-organizational learning fully mediates collaboration on flexibility.

• Flexibility positively impacts downstream in customer satisfaction.

• Impact of flexibility on performance increases with higher product dynamism.

Abstract

A critical capability sought by an increasing number of firms is manufacturing flexibility, because it allows to effectively respond to dynamic markets. Grounded upon a supply chain perspective, this paper aims to assess antecedents of manufacturing flexibility that stem from the upstream relationships with strategic suppliers. Additionally, it is one of the first to analyze the contingent effect of product dynamism on the impact of manufacturing flexibility on downstream customer satisfaction. We apply structural equation modeling to a sample of 155 companies in order to analyze our hypotheses. Results strongly indicate that buyer-supplier collaboration facilitates inter-organizational learning that in turn allows organizations to develop manufacturing flexibility and increase customer satisfaction. Approaching manufacturing flexibility from a broader supply chain view thus pays off. Moreover, we apply multi-group confirmatory factor analysis to explore the contingent effect of product dynamism on the relationship between manufacturing flexibility and customer satisfaction. Results suggest a stronger impact of manufacturing flexibility on performance in the context of higher product dynamism in companies’ customer markets, confirming the importance of a contingency view to flexibility.

Introduction

Manufacturing flexibility is seen as a key characteristic of successful firms (Scherrer-Rathje et al., 2014). Several factors help explain the increasing importance of manufacturing flexibility, such as product proliferation, massive customization strategies, or the enormous increase in online retail. Currently, we face a move to an “on demand” economy based on shorter lead times, exemplified in extremis by new initiatives such as Amazon's “one-hour delivery” (Wired, 2015), and shorter development periods, exemplified by Apple´s recent launch of the iPhone 6 (Reuters, 2015).

Although the concept of manufacturing flexibility is not new, we have recently seen an increasing number of empirical studies on this issue (Mendes and Machado, 2015; Mishra et al., 2014; Ojha et al., 2015; Pérez Pérez et al., 2016; Tamayo-Torres et al., 2014; Urtasun-Alonso et al., 2014). Nevertheless, antecedents that could hinder or leverage manufacturing flexibility remain underdeveloped in the literature, for example antecedents related to upstream relationships with selected suppliers (Mishra et al., 2014; Pérez Pérez et al., 2016). Critical resources may span firm boundaries and be embedded in buyer-supplier relationships (Dyer and Singh, 1998). Inter-organizational learning in that regard allows an organization to identify external knowledge and convert it into value for the customer (Lane et al., 2006). In other words, inter-organizational learning allows a buyer to identify relevant suppliers´ knowledge and convert that into an adapted offer to downstream customers (Sáenz et al., 2014). However, previous studies lack empirical evidence measuring the extent to which inter-organization learning contributes to manufacturing flexibility (Mishra et al., 2014).

A second research gap is the influence of buyer-supplier collaboration on manufacturing flexibility. Although integration with suppliers has been often mentioned as contributing to manufacturing flexibility, empirical studies on this issue are rare (Mishra et al., 2014; Zhang et al., 2003). For example, the contrast between relational and arm's length approaches to suppliers, although largely discussed in the supply chain management literature (Mahapatra et al., 2012), has received much less attention in flexibility studies. This is relevant, because flexibility strategies do not exist on a vacuum: instead, they interact with supply policies. The firm can work in concert with strategic suppliers to deliver value to the market (Cousins and Spekman, 2003). But, it is not clear how and to what extent buyer-supplier collaboration facilitates the development of manufacturing flexibility.

A supply chain perspective on manufacturing flexibility involves not only the appreciation of the impact of upstream relationships with strategic suppliers but also the effect of flexibility on downstream outcomes. A key outcome in that regard is customer satisfaction (Zhang et al., 2003). With rare exceptions (e.g. Camisón and Villar Lopez, 2010), current literature on flexibility has neglected the impact on customer satisfaction and rather focused on broader performance measures (Pérez Pérez et al., 2016). This is a critical issue, since the combination of customers´ and other stakeholders´ actions and decisions ultimately drive a firm's financial performance.

A final research gap concerns the relationship between product characteristics and flexibility. Although flexibility is often associated with innovative products (Fisher, 1997) or dynamic environments (Fine, 1998), there is scarce empirical evidence (Gligor et al., 2015, et al., 2014). Actually, recent studies suggest that flexibility may also be important to less dynamic products (Blome et al., 2013). Many sectors traditionally associated with functional products (e.g., the chemical industry) are facing pressures to increase their flexibility (ICIS, 2015).

Summarizing, this paper aims to empirically analyze the key antecedents of manufacturing flexibility that stem from upstream relationships with suppliers. In addition, we aim at providing empirical evidence on the effect of flexibility on downstream customer satisfaction, as well as the moderating role of product dynamism in such relationship.

The paper is structured as follows. In the next section we review briefly the existing literature on manufacturing flexibility, the expected impact on customer satisfaction, the expected moderating impact of product dynamism, and the nature of the selected antecedents. This analysis allows us to develop a theoretical framework and corresponding hypotheses. The research methodology is subsequently explained, including the sample characteristics, data collection and measurement scales, and the structural equations method used to analyze the data. We then present and discuss the main results derived from the empirical analysis. Finally, we suggest managerial implications as well as future research directions.