Supply Chain Disruption Performance Construct

Supply chain management, observed Seferlis, Vlachos, Iakovou et al. (2008), involves a number of decisions to be taken at every time period to meet end-customer requirements. The overall supply chain performance is multi-dimensional and directly or indirectly affected by several factors, such as service quality and overall operating costs. Provided that these factors are generally battling with each other, trade-off and compromise choices are necessary to achieve the best performance. Inventories at the nodes of the network serve as safety stock to handle the stochastic variation of demand, anticipate for lead time in ordered quantities, and compensate for abrupt shocks (e.g., damaged products during transportation, bad storage conditions, and delays in lead times) that would otherwise disrupt the smooth supply of products. However, making disruption response decisions that give either a positive or sub optimal performance are ‘of the moment’ unless the managers and organisations can learn from that performance (Peck, 2006). As highlighted by Daft and Weick (1984), overlapping with extant organisational information processing models, gathering, processing, and acting on data from the environment is a firm's main task. Taking an information processing perspective, it is critical to supply chain success (Bowersox, Closs and Stank, 1999, Busse, Meinlschmidt and Foerstl, 2017).

The supply chain disruption performance construct has its grounding in the information processing perspective, as did Bode et al. (2011), in developing the organisational response framework, as shown in Figure 14, but also draws on the organisational learning research, as discussed in the literature review. Two assumptions underpin much research on learning in the organisational context; that learning is intended, conscious, or purposeful and that ‘successful’ learning leads to better performance. To influence employees, as noted by Sims and Lorenzi (1992), successful managers require an understanding of a contingency of reinforcements, also called the behavioural contingency. The link between learning and performance is explicitly addressed in several reviews. Many organisational learning researchers assume a link between learning and performance (Huysman, 1999, Crossan, Lane, White et al.,

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1995, Dodgson, 1993). As noted, however, by Huysman (1999), is the learning just a new rather than old routine, or is it an ‘active’ agency. Huber (1991) p1001, defined

learning: “an entity learns if, through its processing of information, the range of

potential behaviours is changed”. Also as per reinforcement theory noted by Robbins,

Judge and Campbell (2010), any consequences that, when immediately following responses, increase the chances that the behaviour will be repeated. The results of Bode et al. (2011) points towards the moderating effect of prior experience making a strong case for organisational learning from supply chain disruptions. Hedberg (1981) also raised the question of whether firms forget what they have learned from prior supply chain disruptions. In encapsulating the literature, Huber (1991) identified four key learning elements: knowledge acquisition, information distribution, information interpretation, and organisational memory. In a strategic supply chain, memory encourages more acquisition knowledge (Hult, Ketchen and Slater, 2004).

Members of chains that possess significant memory are aware that knowledge coordination across nodes reduces duplication, waste, and redundancy (Handfield and Nichols, 2002). To make effective response decisions to disruptions which lead to, for example, stock-out situations, outcome performance information needs a feedback loop mechanism. In this way, management making strategic response decisions can make informed response choices, with dynamic capabilities drawing a response dependence perspective (Pfeffer and Salancik, 1978, Daft and Weick, 1984). Actors making independent response decisions may hold diverse views whose interpretation may overlap without reaching consensus on meaning (Gioia and Thomas, 1996). But diverse interpretations are often a hindrance in the supply chain context (Hult, Ketchen and Slater, 2004). Diverse views of concepts can be resolved so that effort can be focused on necessary activities. By including the assistance of empirical performance data from prior response decisions, strategic supply chains can benefit and individual participants learn to think alike. There is a distinction, as discussed in the literature review between managerial ‘work’ as a set of actual behaviours and as a set of desired (either by managers or others) outcomes (Hales, 1986). The following proposition is developed to fill the gap left by previous research by considering the role of feedback and supply chain disruption:

Proposition 2e. There is a positive relationship between the performance feedback given after a supply chain disruption event and higher performance in shortage management.

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The analysis of buffering and bridging strategies in response to supply chain disruptions requires further investigation, leading on from the initial works by Bode et al. (2011). An examination of the interplay of buffering and bridging is needed. Buffering involves trying to keep the environment from interfering with internal operations and trying to influence the external environment (for example, building safety stock). Bridging occurs as firms seek to adapt organisational activities so that they conform to external expectations (for example, developing new supply sources). This response could be a response strategy due to a supply factor risk, for example, as a result of having too small a supply base, supplier dependency, inflexibility, or single sourcing (Wagner and Neshat, 2010, Ho, Zheng, Yildiz et al., 2015, Tummala and Schoenherr, 2011). However, as identified by previous research (Meznar and Nigh, 1995, Bode, Wagner, Petersen et al., 2011), the interaction of the different strategies are still not fully understood. In particular, there exists a research gap for deeper analysis of their comparative efficiency and effectiveness. Buffering and bridging choices are not mutually exclusive, as shown in prior work (Meznar and Nigh, 1995, Fennell and Alexander, 1987, Bode, Wagner, Petersen et al., 2011). Although the Bode et al. (2011) study (based on integrating perspectives; information processing and resource dependency theory) did not find significant correlation between the two strategies, they did find that there may be a temporal ordering wherein a focal firm progresses from less to more intense responses. This dynamic nature of organisational responses to supply chain disruptions and their relative efficiency and effectiveness will be tested by the following proposition:

Proposition 2f. Pursuing an initial buffering strategy followed by a bridging strategy enhances performance in shortage management

The dynamic and evolving nature of supply chain risks means that no supply chain strategy is ever likely to be risk-free, and no system, however well managed, is invulnerable. Therefore, as noted by Peck (2005), it seems that there is slack in the system, whether in the form of inventory, capacity, capability, and even time. Mitigating strategies and buffering and bridging have been positively related in risk management research to consider risk reduction and its relation to improved downstream supply chain performance overall, by Mishra, Sharma, Kumar et al. (2016) based on the Miles, Snow, Meyer et al. (1978) four firm typology, although constant awareness and vigilance are needed if supply chains are to become, and remain, truly resilient. The previous two propositions consider whether the use of a combined strategic approach of buffering and bridging will deliver improved shortage management performance in

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response to a disruption. According to resource dependency theory, responses can be different on the basis of whether they are internal or external to a current relationship (Carroll, 1993). Buffering actions are predominately internal (for example, controlling stock an organisation already has on hand or ordered), whereas bridging actions are predominately external (for example, sourcing new suppliers or a new organisational network). The last proposition to examine supply chain disruption performance is:

Proposition 2g. Buffering actions in response to supply chain disruption are more effective than bridging actions in shortage management performance

The third construct, following on from supply chain disruption performance, is organisational response.