Linking decision-control and decision-management uses of performance measurement systems

Abstract

Purpose The purpose of this paper is to analyze, for both parties of a distribution channel, to what extent each party perceives the counterpart’s use of performance measurement systems (PMS) and how this perception affects the perceiver’s own use of these systems, for either decision control or decision management. Design/methodology/approach The paper proposes a conceptual model tested at different levels using structural equations models. A case study uses survey data from 107 distributors and 91 manufacturer managers. Findings PMS allow evaluation by the manufacturer and daily management by distributors; both uses of PMS can be simultaneous and complementary. Results show that each party’s perception of the counterpart’s use contributes to its own use, although real uses do not significantly influence these perceptions. Research limitations/implications The results must be interpreted with caution because the sample is small. This study calls for further data collection in real situations with larger samples, and for eliminating the influence of the distribution channel type. Further work is needed to analyze other constructs driving the relationship between real use and perception. Originality/value This study’s originality comes from the conceptual model, data set, and levels of analysis. Decoupling real use and perception, it challenges the prevailing assumption that managers accurately perceive counterpart managers’ use of PMS. Analyzing at both group and individual levels, it extends the more usual dyadic studies by recognizing that any given manager’s perception may be almost wholly formed by his/her interaction with a group of individuals.

Shipping surcharges and LSQ: pricing the last mile

“…any cue that can be used to convey private or unknown information) are interpreted by targets in an attempt to reduce information asymmetry and make assessments on latent or unobservable factors of interest (Connelly et al , 2011). Signaling theory has been applied to a variety of operations and supply chain research contexts such as influencing the perceptions and behaviors of rival firms (Hofer et al , 2012), supply chain partners (Sanchez et al , 2017; Cheng et al , 2020), investors (Chowdhury and Sarkar, 2017) and e-commerce customers (Hossain et al , 2018; Li et al , 2019). Signaling theory is applicable in a prepurchase scenario in which consumers have no experience with the seller and, therefore, higher ambiguity of seller service quality (Hossain et al , 2018).…”

Exploring challenges in dimensioning safety buffers: an empirical study

“…Dimensioning safety buffers inevitably requires decision-making, whether in directly judging the size of safety buffers or in setting the decision parameters for calculation methods. At base, decision management refers to acquiring and processing information necessary for making decisions (Sanchez et al. , 2017) and coordinating processes (Kärkkäinen et al.…”

“…Dimensioning safety buffers inevitably requires decision-making, whether in directly judging the size of safety buffers or in setting the decision parameters for calculation methods. At base, decision management refers to acquiring and processing information necessary for making decisions (Sanchez et al, 2017) and coordinating processes (K€ arkk€ ainen et al, 2007). Past research has shown that, in practice, dimensioning safety buffers is often based on judgemental methods or involves aspects of manual decision-making as part of calculation methods (Jonsson and Mattsson, 2000).…”

Mind the perception gap

“…For decades, significant research interest has focussed on designing KPIs for supply chain performance measurement and the integrated performance management systems (PMS) that incorporate KPIs (Holmberg, 2000; Gunasekaran et al , 2004; Della Bruna et al , 2014; Sanchez et al , 2017). Hazen and Byrd (2012) suggest that integration of the PMS within the information systems of the supply chain partners can enhance performance in various dimensions.…”

“…Kant and Dalvi (2017) provide a detailed list of the supplier evaluation KPIs from 34 automotive industries, while also providing a popularity ranking of these KPIs according to collected survey data. Sanchez et al (2017) analyse how supply chain partners perceive their counterpart’s use of PMS and how this perception affects their own use of similar systems. Maestrini et al (2018) present the lifecycle of a collaborative PMS and suggest incorporating the importance of KPIs into a PMS.…”