Logistics and supply chain management have gained an important role within the organisations, from the procurement of raw materials until the delivery of the final product to the client (Lambert, Pagh & Cooper 1998). In this journey, choice of logistics service partner can have significant impact on operational costs and customer service level of an organisation, which ultimately impacts customer satisfaction and performance of the organisation. Therefore, the selection of an efficient and reliable logistics service provider (LSP) is one of the most critical factors in logistics planning. Existing literature have very detailed working on few factors of logistics procurement, but limited work on comprehensive assessment of factors in decision-making of express logistics buying. This research aims to create a theoretical model for the factors impacting buying decision of express logistics services, which can also help logistics practitioners.

A selection process goes through multiple levels of decision-making in logistics, ranging from mode selection, route selection and vendor selection (Vashist & Dey 2016). The first level of choice in the overall planning is mode selection, which depends on nature of product and available modal options (Liberatore 1979). This research does not include factors of mode selection and route selection. Next level of decision-making involves the vendor selection. The process in decision-making for vendor selection in logistics involves consideration of a number of criteria. Under such scenario, evaluation of multiple parameters having different dimensions is possible (Ceballos, Lamata & Pelta 2016). Normally, logistics is not core to an organisation and is outsourced to a service provider (Razzaque & Sheng 1998), but lately logistics outsourcing has increased in order to generate efficiency. Outsourcing also helps organisations to focus on their core what they do best (Daugherty, Theodore & Rogers 1996). Broadly, outsourcing works on few key factors such as time taken in service delivery, safety and visibility, but any decision-making is not limited to such factors and logistics services buying decision requires consideration of multidimensional factors (Karrapan et al. 2017). The objective of research is to create a framework of all factors that impact decision-making of logistics procurement. The review of literature shows as many as 10 factors, which may have an impact on decision-making process of logistics procurement. The identified factors are given in Table 1.

The efficiency of the logistics function influences business performance of an organisation and also the customer’s perception about quality (Kenyon & Meixell 2014). Therefore, the right selection of logistics partner becomes critical. Cost and performance in logistics is a coherent set of tools, which supports logistics decision-making (Bokor 2008); the same is applicable for express logistics as well. The literature review shows the following factors on logistics buying.

The literature review enabled in identifying key factors impacting logistics buying decision. In order to validate the factors identified from literature review, input from the subject matter experts of logistics industry was also taken for finalising the major factors. Thereafter, a model has been developed using interpretive structural modelling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) analysis. The ISM provides a directional and ordered framework for complex problems and gives a realistic and clear picture of the system and its variables to decision-makers (Attri, Dev & Sharma 2013; Jiang et al. 2019). The ISM approach has been accepted as this method gives structured direction to interactions among factors that influence the entire system (Singh & Kant 2008).

In the process, a group of 14 subject matter experts comprising managers, consultants and academicians having expertise in Indian logistics sector was selected as a focused group for this study and was briefed about objective of research study. All experts possessed significant experience in managing supply chain and logistics in current scenarios. The group was consulted in identifying the contextual relationship among the factors identified by them. It is followed with pairwise comparison, development of structural self-interpretive matrix, formulation of binary initial reachability matrix (IRM), development of MICMAC and diagraph preparation leading to ISM. This model is expected to metamorphose an unclear, poorly articulated mental model into a visible and well-defined model (Sage 1977). Flowchart of ISM steps is presented in Figure 1.

In the process of logistics buying decision, technology and network reach are driving factors. These factors clearly indicate the basic strength area of a service provider, on which LSP creates its service capability and differentiation for offering efficient services. Technology is enabler for efficient logistics ecosystem and better workflow management systems. Transport Management System, Vehicle Tracking Systems, Application Program Interface and others at service provider end significantly improves operational activities in logistics system. While in the absence of robust technology platform, information sharing between LSP and service buyer will not be efficient. Improved technology platform provides base and confidence to service buyer for the strategic partnership between both. Prime role of LSP is to serve the service buyer for its inbound and outbound logistics requirements in an efficient manner, which is not possible without adequate reach of service provider. If any LSP has a deep network reach coupled with good service levels, customers would choose such LSP to be their strategic partner. Information sharing and strategic partnership have two-way relationship. As foundation of strategic partnership lies on transparency, which is possible by way of enhanced information sharing between both. It gives higher degree of confidence to share information to logistics service provider and logistics service user. Higher degree of information sharing and strategic partnership between LSP and service user helps in improving visibility across supply chain. In present era, real-time information availability is one of the prerequisites for driving efficient supply chain, which not only enables management of logistics activity but also helps in proactive planning. Better visibility about movement of goods drives faster deliveries through proactive or real-time resolution of any bottle neck in flow of material. Logistics play a small part in any product’s time to market. At best, faster deliveries can help companies that deal with products of cut-throat competition and high demand. Research also indicates that lesser time in delivery leads to better time to market. On the other side, faster deliveries facilitate faster customer response on merchandise and so ease of reverse logistics. Ease of reverse logistics is also dependent on preceding factors such as technology and network reach of LSP. Presently when most of the company’s distribution model is moving towards omni channel and serving B2C and D2C channels, efficient reverse logistics is a sought-after service offering for such shippers. As accuracy and timeliness are key parameter of reverse logistics, faster delivery leads to ease of reverse logistics. Time to market and reverse logistics have a direct impact on service quality. Normally in logistics, two basic parameters of service quality are on time and accurate pickup and delivery. Therefore, service quality is driven by time to market in case of forward movement and ease of reverse in case of reverse movement. Normally, service quality becomes a key tangible factor in logistics service buying decision, which is driven by multiple factors at LSP’s end. Logistics cost remains a prominent factor, but this cost is not only direct cost but also includes all direct and indirect costs linked to logistics services. In logistics and supply chain, cost is dependent not only on deliveries but also includes costs related to transportation, warehousing, inventory, leakages, etc. Better service and fewer errors lead to lower overall cost of logistics.

As per the objective of research to create a model for the factors impacting buying decision of logistics services, which can also help logistics practitioners, the model output clearly suggests that final objective in decision-making process of logistics procurement is driven towards lower cost and improved service level. But it is driven by factors that directly add value in supply chain such as time to market and reverse logistics. These factors such as technology and network reach of LSP are key towards driving final objective. Therefore, in decision-making of logistics buying, network reach of the LSP and technology are the key drivers followed by information sharing and strategic partnership approach, which need due consideration.