The use of modelling in purchasing/supply management research

The purpose of this research to explore the use of modelling in the field of Purchasing and Supply Management (P/SM). We are particularly interested in identifying the specific areas of P/SM where there are opportunities for the use of modelling based methods. The paper starts with an overview of main types of modelling and also provides a categorisation of the main P/SM research themes. Our research shows that there are many opportunities for using descriptive, predictive and prescriptive modelling approaches in all areas of P/SM research from the ones with a focus on the actual function from a purely operational and execution perspective (e.g. purchasing processes and behaviour) to the ones with a focus on the organisational level from a more strategic perspective (e.g. strategy and policy). We conclude that future P/SM research needs to explore the value of modelling not just at the functional or operational level, but also at the organisation and strategic level respectively. We also acknowledge that while using empirical results to inform and improve models has advantages, there are also drawbacks, which relate to the value, the practical relevance and the generalisability of the modelling based approaches

Using Digital Nudges on Analytics Dashboards to Reduce Anchoring Bias

This study investigates the effectiveness of digital nudging on reducing the anchoring bias observed in the use of supply chain management (SCM) software. A between-subjects experiment with 61 participants was conducted comparing a control group with two types of digital nudges implemented on an SCM analytics dashboard. Findings show that digital nudging can help mitigate an anchoring bias in several use conditions. Theoretical and practical contributions are discussed, which include that in addition to individual-level outcomes, digital nudging can also be applied in business environments to improve organizational-level performance

Austrian and Post-Marshallian EconomicsThe Bridging Work of George Richardson

Austrian and post-Marshallian economics share a number of concerns, such as a basic subjecticist stance and an emphasis on the importance of inquiry into the disequilibrium market process. This paper details similarities and differences between these two bodies of thought, and argue that a closer liaison is possible. George Richardson's work is presented as a possible bridge, since his work incorporates both Austrian and post-Marshallian elements. The paper ends by sketching a combined Austrian and post-Marshallian approach to the firm.Austrian economics, post-Marshallian economics, George Richardson, the theory of the firm

The anchoring heuristic and overconfidence bias among frontline employees in supply chain organizations

This study assesses the extent the anchoring heuristic and overconfidence bias leads to inaccurate judgments among frontline employees in complex multi-stakeholder supply chain organizations. Data is obtained from an experiment-based questionnaire in a United Kingdom based freight forward and materials handling company. Analysis is undertaken using descriptive and inferential statistics. Results suggest that frontline employees within consistently overestimate probabilities when framed in a conjunctive manner. They also consistently underestimate probabilities when framed in a disjunctive manner and also exhibit considerable overconfidence in their judgements. Mixed evidence was found regarding susceptibility to anchoring and overconfidence in terms of level of expertise and geographical location. Findings highlight the critical role of communication in establishing reflective monitoring of, and improvements to, heuristics usage in daily supply chain decisions

Modelling and managing Supply Chain forecast uncertainty in the presence of the Bullwhip Effect

The Bullwhip Effect, defined as the upstream amplification of demand variability, has received considerable interest in the field of Supply Chain Management in recent years. This phenomenon has been detected in various industries and sectors, and manifests itself with multiple inefficiencies and higher costs at upper echelons in the supply chain. As a result, this topic is of great importance for academics and practitioners alike. One root cause of the Bullwhip Effect is the need for firms to forecast demand in order to place their orders and base their inventory decisions. Despite the multitude of studies that have emerged tackling this issue, the impact of the quality of forecasts on the Bullwhip Effect has received limited coverage in the literature. Modelling and forecasting the demand can be challenging, resulting in increased forecast uncertainty that contributes to the Bullwhip Effect. This thesis aims at bridging this gap by investigating three main research questions: (i) How can supply chain forecast uncertainty be captured at a firm level? (ii) How can the upstream propagation of forecast uncertainty from the Bullwhip Effect be measured? and (iii) What customer demand information sharing strategy is the most effective in reducing upstream the forecast uncertainty and inventory costs resulting from the Bullwhip Effect? We first propose an empirical approximation for measuring forecast uncertainty at a local level, which we show to outperform commonly used approximations for inventory purposes. We then propose a novel metric to capture the propagation of forecast uncertainty at higher echelons in the Supply Chain, which correlates strongly with upstream inventory costs, more so than the conventional Bullwhip measure. Using this, we evaluate alternative information sharing strategies that have appeared in the literature, but have not been assessed comparatively. We find that relying solely on point of sales data results in the best forecasting accuracy and inventory cost performance for upstream members. The findings obtained are actionable and simple to implement, making them of great use and relevance for supply chain practitioners and managers

Economic Order Quantity (EOQ) Inventory Management - Essays in Experimental Economics

This thesis consists of six chapters to experimentally study aspects of how levels of individuals’ cognitive stress, cognitive ability and self-regulatory resource affect their decision making under the Economics Order Quantity (EOQ) inventory management environment. In Chapter 3 we use laboratory experiments to evaluate the effects of cognitive stress on inventory management decisions in a finite horizon economic order quantity model. We manipulate two sources of cognitive stress. First, we vary participants’ participation in a pin memorisation task. This exogenously increases cognitive load. Second, we introduce an intervention to reduce cognitive stress by only allowing participants to order when inventory is depleted. This intervention restricts the policy choice set. Increases in cognitive load negatively impact earnings with and without the intervention, with these impacts occurring in the first year. Participants’ in all treatments tend to adopt near optimal policies. However, only in the intervention and low cognitive load treatment do the majority of choices reach the optimal policy. Our results suggest that higher levels of multitasking lead to lower initial performance when taking on new product lines, and that the benefits of providing support and task simplicity are greatest when the task is first assigned. In Chapter 4 we use laboratory experiments to evaluate the effects of individuals’ cognitive abilities on their behaviour in a finite horizon economic order quantity model. Participants’ abilities to balance intuitive judgement with cognitive deliberations are measured by the Cognitive Reflection Test (CRT). Participants then complete a sequence of five “annual” inventory management tasks with monthly ordering decisions. Our results show that participants with higher CRT scores on average earn greater profit and choose more effective inventory management policies. However these gaps are transitory as participants with lower CRT scores exhibit faster learning. We also find a significant gender effect on CRT scores. This suggests hiring practices incorporating CRT type of instruments can lead to an unjustified bias. In Chapter 5 we use laboratory experiments to evaluate the effects of individuals’ ability to self- regulate on inventory management decisions in a finite horizon economic order quantity model. An ego depletion task is implemented aiming to diminish one’s self-regulatory resources. From a psychological point of view, self-control is impaired when the mental resource has been used up over effortful control of responses. In our experiment, participants complete an ego depletion task followed by a sequence of five “annual” inventory management tasks with monthly ordering decisions. Our results show there is no obvious treatment effect on participants’ self-regulation ability