Chain member perception of chain performance: the role of relationship quality

Abstract

The purpose of the paper is to measure perceived performance of bilateral relationships in the chain. Therefore, quantitative data were collected from 270 chain members from 3 EU countries in 6 traditional food product categories. First, perceived performance of bilateral relationships was analysed which revealed a generally high perceived contribution of each chain member to its partners' performance. Second, cluster analysis was conducted resulting in 4 clusters: 1) Low performing chains; 2) Low perceived food manufacturer's (FM) performance by supplier (S) and customer (C); 3) High perceived FM performance by S and C; 4) High performing chains. Third, binary logistic regression was used to identify 7 relationship constructs that significantly predict cluster membership: trust, economic satisfaction, social satisfaction, dependency, coercive power, reputation, conflict and integration.

Role of power in supply chain performance: evidence from agribusiness SMEs in Uganda

“…1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 In departure from previous studies, this paper makes three additional contributions to 1 the SCM literature. Firstly, past studies on power in supply chains have focused on its 2 influence on resource allocation (Pulles et al, 2014); power asymmetry (Nyaga et al, 2013); 3 commitment (Zhao et al, 2008); relationship strength (Maloni and Benton, 2000); and 4 performance (Crook and Combs, 2007;Molnár et al, 2010). With a few exceptions such as 5 Molnár et al (2010) and Kühne et al (2013), the majority of these studies collect and analyze 6 data from one side of a relationship dyad using a focal firm approach.…”

“…Firstly, past studies on power in supply chains have focused on its 2 influence on resource allocation (Pulles et al, 2014); power asymmetry (Nyaga et al, 2013); 3 commitment (Zhao et al, 2008); relationship strength (Maloni and Benton, 2000); and 4 performance (Crook and Combs, 2007;Molnár et al, 2010). With a few exceptions such as 5 Molnár et al (2010) and Kühne et al (2013), the majority of these studies collect and analyze 6 data from one side of a relationship dyad using a focal firm approach. Analyzing a supply 7 chain at firm or dyadic levels limits understanding the underlying dynamics of the entire 8 supply chain relationships (Molnár et al, 2010;Wu et al, 2010;Kühne et al, 2013;9 Touboulic et al, 2014).…”

“…Secondly, relationships are by nature bi-directional, as such, there will be differences 12 in perceptions and expectations amongst supply members (Molnár et al, 2010;Wu et al, 13 2010; Nyaga et al, 2013;Pulles et al, 2014;Odongo et al, 2016). Positive outcomes for the 14 whole supply chain will contribute to an individual member's success (Medlin, 2006; 15 Gagalyuk et al, 2013;Petrick et al, 2016).…”

“…With a few exceptions such as 5 Molnár et al (2010) and Kühne et al (2013), the majority of these studies collect and analyze 6 data from one side of a relationship dyad using a focal firm approach. Analyzing a supply 7 chain at firm or dyadic levels limits understanding the underlying dynamics of the entire 8 supply chain relationships (Molnár et al, 2010;Wu et al, 2010;Kühne et al, 2013;9 Touboulic et al, 2014). Consequently, there is a need to look beyond the dyad and into the 10 triad as a unit of analysis.…”

“…This implies that supply chain members are 1 interdependent in a complex supply chain structure (Cai et al, 2013;Chicksand, 2015; 2 Odongo et al, 2016). Supply chain management (SCM) literature demonstrates that power is 3 a vital predictor of supply chain performance (SCP) (Molnár et al, 2010;Nyaga et al, 2013), 4 adoption (Liu et al, 2015), innovation capacity (Kühne et al, 2013), and customer 5 integration (Zhao et al, 2008). However, the role of power relations in supply chains is evolving as firms become 7 more complex and multifaceted.…”