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PurposeDrawing on information processing theory, the linkage between buffering and bridging and the ability on the part of procurement to resolve demand–supply imbalances is investigated, as well as contexts in which these strategies may be particularly useful or detrimental. Buffering may be achieved through demand change or redundancy, while bridging may be achieved by the means of collaboration or monitoring.Design/methodology/approachThis study employs a hierarchical regression analysis of a survey of 150 Finnish and Swedish procurement and sales and operations planning professionals, each responding from the perspective of their own area of supply responsibility.FindingsBoth the demand change and redundancy varieties of buffering are associated with procurement's ability to resolve demand–supply imbalances without delivery disruptions, but not with cost-efficient resolution. Bridging is associated with the cost-efficient resolution of imbalances: while collaboration offers benefits, monitoring seems to make things worse. Dynamism diminishes, while the co-management of procurement in S&OP improves procurement's ability to resolve demand–supply imbalances. The most potent strategy for tackling problematic contexts appears to be buffering via demand change.Practical implicationsThe results highlight the importance of procurement in the S&OP process and suggest tactical measures that can be taken to resolve and reduce the effects of supply and demand imbalances.Originality/valueThe results contribute to the procurement and S&OP literature by increasing knowledge regarding the role and integration of procurement to the crucial process of balancing demand and supply operations.

PurposeIn the context of the COVID-19 pandemic, this study investigates a variety of approaches to supply disruption risk management for achieving effective responses for resilience at the supply management subunit level (e.g. category of items). Drawing on the attention-based view of the firm, the authors model the attentional antecedents of supply resilience as (1) attentional perspectives and (2) attentional selection. Attentional perspectives focus on either supply risk sources or supply network recoverability, and both are hypothesised to have a direct positive association with supply resilience. Attentional selection is top down or bottom up when it comes to disruption detection, and these are hypothesised to moderate the association between disruption risk management perspectives and resilience.Design/methodology/approachConducted at the early phases of the COVID-19 pandemic, this study employs a hierarchical regression analysis on a multicountry survey of 190 procurement professionals, each responding from the perspective of their own subunit area of supply responsibility.FindingsBoth attentional disruption risk management perspectives are needed to achieve supply resilience, and neither is superior in terms of achieving supply resilience. Both the efficiency of the top down and exposure to the unexpected with the bottom up are needed – to a balanced degree – for improved supply resilience.Practical implicationsThe results encourage firms to purposefully develop their supply risk management practices, first, to include both perspectives and, second, to avoid biases in attentional selection for disruption detection. Ensuring a more balanced approach may allow firms to improve their supply resilience.Originality/valueThe results contribute to the understanding of the microfoundations that underpin firms' operational capabilities for supply risk and disruption management and possible attentional biases.

PurposeThis study aims to investigate the extent to which psychological factors and the agency of decision-makers drive outsourcing decisions. Arguments based on transaction cost economics, the core competence approach and the theory of planned behavior are used to explain logistics outsourcing.Design/methodology/approachThe literature was reviewed to identify constructs that are antecedents of logistics outsourcing intentions, and corresponding measures were developed. The data were gathered through a survey of supply chain professionals in Finnish manufacturing companies. A measurement model was reviewed to ensure reliability and validity and converted into a structural model for analysis. The analysis was based on partial least squares (PLS) structural equation modeling.FindingsSupply chain managers objectively consider the characteristics of their organization's logistics identified in previous research as requiring assessment during the outsourcing process. However, and surprisingly, they also tend to rely on behavioral subjective factors such as positive attitudes, encouraging subjective norms and competence. Moreover, it seems that firms do not outsource logistics activities despite the high strategic importance of the function, but because of it.Research limitations/implicationsThe constructed model is limited to the constructs chosen to represent drivers of logistics outsourcing. Further application with more samples would improve its reliability.Practical implicationsThe factors proposed here with respect to assets and the capabilities of third-party partners could facilitate decision-making related to logistics outsourcing.Originality/valueThe findings emphasize the role of behavioral factors in the procurement function and therefore enhance the understanding of behavioral supply chain management.

PurposeThe size of the logistics market is typically estimated from the national accounting and market data. However, this data does not take certain in-house logistics services into account and most likely underestimates the true size of the market. The purpose of this paper is to develop a method for estimating the potential size of the logistics market in terms of overall logistics expenditure and to also account for in-house services.Design/methodology/approachThe research approach involves combining longitudinal industry- and firm-level turnover data, incorporating survey data from Finland on logistics outsourcing and costs, and calculating yearly logistics expenditure and the market demand for logistics services. Descriptive statistics, weighted arithmetic means and analyses of variance are employed in the estimations.FindingsThe research suggests and demonstrates a rigorous method for estimating the size of the logistics market, including both market-based demand and in-house services.Research limitations/implicationsThe empirical data used to illustrate the result are limited to a single country. The methodology should be further validated with data from other countries. The quality of the survey data could be improved by targeting multiple informants from a single firm.Social implicationsOne outcome of the research is that policymakers will be better able to estimate the size of the logistics market on a national level. For service providers, the results provide additional information on the market potential of logistics services.Originality/valueThe novelty of the research lies in combining multiple data sources and expanding the estimation of the logistics market to include services provided in-house.