Exploring the omnichannel transformation of material-handling configurations and logistics capabilities in grocery retail

Grocery retail is going through a rapid shift. Consumers now expect to be able to shop online or in stores, get orders delivered when and where they want, and preferably as quickly as possible. This development is called omnichannel and means grocery retailers must transform their logistics networks to meet consumers’ evolving expectations and demands. The omnichannel transformation includes, for example, setting up new material handling (MH) nodes to pick online orders and investing in new automated systems. While this might sound straightforward, grocery retailers struggle to succeed with the omnichannel transformation, particularly in living up to consumers’ evolving expectations and becoming profitable. To develop theoretical and practical knowledge on this under-researched topic, this dissertation aimed to explore and understand the MH configurations and logistics capabilities needed in the omnichannel transformation of grocery retail and the dynamic capabilities required to manage such a transformation. In responding to this purpose, this dissertation makes several important contributions for researchers and practitioners who aim to understand how grocery retailers manage the omnichannel transformation and what they are doing to reconfigure MH configurations and logistics capabilities.The dissertation is based on the results of five articles from three separate but subsequent studies. The first study, a case study–inspired interview project, applied a contingency approach to explore the configurations of four manual online fulfillment centers (OFCs) in omnichannel grocery retail. The study captured key configurations, main challenges, and influential contextual factors. Study two, a multiple case study, focused on sorting in omnichannels. The study increased knowledge of sorting in omnichannels, and by combining empirical data with transvection theory, it also resulted in an artifact for analyzing and designing omnichannel sorting. The third and last study was a multiple case study of three grocery retailers and had a two-fold focus. First, this study moved beyond exploring specific aspects of the MH configurations and logistics capabilities in omnichannel grocery retail (OFC configuration and sorting) and focused on how and why grocery retailers manage the transformation by contextualizing dynamic capabilities. Second, study one revealed that investment in automation is as one key to being competitive in the omnichannel environment. Study three further explored automated online order picking systems and captured key configuration aspects, main performance objectives, and influential contextual factors. This dissertation contributes to the research by combining the findings from the three studies with literature on omnichannel logistics and MH in grocery retail, warehouse theory, and transvection theory to elaborate knowledge on what and dynamic capabilities to understand how. Moreover, a contingency approach helped investigate why grocery retailers invest in and reconfigure specific MH configurations and logistics capabilities, as well as why some grocery retailers are more successful than others with the omnichannel transformation. As a result, an elaborate and comprehensive framework arose that explains the what, how, and why of omnichannel grocery retail. The analysis and development of the framework revealed that omnichannel grocery retailers adapt their MH configurations and logistics capabilities to their external context to meet evolving customer expectations and requirements. Hence, the potential configurations and logistics capabilities that grocery retailers develop and invest in are influenced and constrained by the external context. The dynamic capabilities required to manage the omnichannel transformation could be identified by applying dynamic capabilities as a theoretical lens. The findings revealed that the identified dynamic capabilities enabling the transformation reside to a large extent on organization-level, both corporate and logistics

An interactive product development model in remanufacturing environment: a chaos-based artificial bee colony approach

This research presents an interactive product development model in re-manufacturing environment. The product development model defined a quantitative value model considering product design and development tasks and their value attributes responsible to describe functions of the product. At the last stage of the product development process, re-manufacturing feasibility of used components is incorporated. The consummate feature of this consideration lies in considering variability in cost, weight, and size of the constituted components depending on its types and physical states. Further, this research focuses on reverse logistics paradigm to drive environmental management and economic concerns of the manufacturing industry after the product launching and selling in the market. Moreover, the model is extended by integrating it with RFID technology. This RFID embedded model is aimed at analyzing the economical impact on the account of having advantage of a real time system with reduced inventory shrinkage, reduced processing time, reduced labor cost, process accuracy, and other directly measurable benefits. Consideration the computational complexity involved in product development process reverse logistics, this research proposes; Self-Guided Algorithms & Control (S-CAG) approach for the product development model, and Chaos-based Interactive Artificial Bee Colony (CI-ABC) approach for re-manufacturing model. Illustrative Examples has been presented to test the efficacy of the models. Numerical results from using the S-CAG and CI-ABC for optimal performance are presented and analyzed. The results clearly reveal the efficacy of proposed algorithms when applied to the underlying problems. --Abstract, page iv

A framework for the implementation of drones in German automotive OEM logistics operations

Intralogistics operations in automotive OEMs increasingly confront problems of overcomplexity caused by a customer-centred production that requires customisation and, thus, high product variability, short-notice changes in orders and the handling of an overwhelming number of parts. To alleviate the pressure on intralogistics without sacrificing performance objectives, the speed and flexibility of logistical operations have to be increased. One approach to this is to utilise three-dimensional space through drone technology. This doctoral thesis aims at establishing a framework for implementing aerial drones in automotive OEM logistic operations. As of yet, there is no research on implementing drones in automotive OEM logistic operations. To contribute to filling this gap, this thesis develops a framework for Drone Implementation in Automotive Logistics Operations (DIALOOP) that allows for a close interaction between the strategic and the operative level and can lead automotive companies through a decision and selection process regarding drone technology. A preliminary version of the framework was developed on a theoretical basis and was then revised using qualitative-empirical data from semi-structured interviews with two groups of experts, i.e. drone experts and automotive experts. The drone expert interviews contributed a current overview of drone capabilities. The automotive experts interview were used to identify intralogistics operations in which drones can be implemented along with the performance measures that can be improved by drone usage. Furthermore, all interviews explored developments and changes with a foreseeable influence on drone implementation. The revised framework was then validated using participant validation interviews with automotive experts. The finalised framework defines a step-by-step process leading from strategic decisions and considerations over the identification of logistics processes suitable for drone implementation and the relevant performance measures to the choice of appropriate drone types based on a drone classification specifically developed in this thesis for an automotive context

The Influence of Education and Experience upon Contextual and Task Performance in Warehouse Operations

Supply chain workers make observable, preventable errors while completing their assigned tasks in the shipping process. Previous research has indicated that individuals with a greater grasp of their work and better system knowledge are less likely to commit interpretation errors. We believe worker-performance may, likewise, be affected by an individuals knowledge of why and where they fit into a larger system defined as mission knowledge. To assess our research objectives, we conduct a controlled experiment with 100 workers in the Air Force supply career field to discern how mission clarity, that is, education, experience and subject characteristics affect pick and pack errors in simulated warehouse order fulfillment tasks. Results indicate that participants who received the experience treatment committed fewer errors, resulting in increased task performance

Developing a Methodical Approach for the Systematic Identification of Innovative Technological Applications – Based on Mixed Reality in Manual Order Picking

The need to be economically successful is the key driver for companies to be innovative and implement new technologies with increasing efficiency and effectiveness. Uncertainty about whether to use new technologies and missing knowledge about their advantages lead to staggering and withholding from fast diffusion of innovations. Focusing on the industry of logistics and the technology Mixed Reality, this research project developed a methodical approach for evaluating the fitness of an innovative technology and a specific process of application. A mixed methods approach was derived, based on interviews and experiments. The main methodologies used, were semi-structured interviews with decision makers in logistics companies to elaborate triggering criteria in the investment process and laboratory experiments for the evaluation of competing technologies. These methods were framed by an initial field experiment and feedback interviews after the analysis for the validation of the approach. The research proved the competitively viable applicability of Mixed Reality and its specific strengths and weaknesses in manual order picking. This set the foundation for possible further development and implementation of the technology. The developed methodological approach proved to be a valid and reliable assessment of the intersection between a technology and specified process of application. This can greatly enhance the speed of implementing new innovations and gaining competitive advantages for companies

The process improvement dilemma in dynamic 3PL firms: A systems and agency lens

For the past several decades, firms have been shifting from contending as autonomous entities to working and competing as part of supply chains. In this context, warehousing, transportation, and distribution needs are being increasingly outsourced to third-party logistics (3PL) firms. 3PL providers operate in fast-moving, time-sensitive, and priority-changing supply chain environments, constantly demanding efficient, cost-effective, and routinized responses. To attain the ultimate end of maximizing efficiency, reducing costs, and improving customer satisfaction, scholars and supply chain industry opinion leaders alike talk about process improvement as part of a broader organizational learning strategy to be pursued in order to keep a competitive edge. This thesis explores the relationship between daily bottom-line pressures and prioritization and the design, implementation, and control of process improvement initiatives in complex and dynamic 3PL service providers. It uses a systems-agency lens to unveil intra- and inter-firm relations around process improvement activity and the links with organizational learning. The study utilized multi-case study-based qualitative-interpretive methods used in conjunction with system dynamics and agency tools. Data collection was carried out through in-depth interviews with 41 employees from two 3PL service providers and complemented by two collaborative enquiry exercises organized for each case study firm. Contrary to recommendations made by scholars and industry leaders, this thesis has found that day-to-day operational firefighting in 3PL scenarios revolving around managing multiple demands, conflicting priorities, and unexpected events often prevail over less tangible process improvement and broader organizational learning goals. This is aggravated by constant cost-reduction pressures centering on human resources headcount deemed critical for the development of learning and improvement practices. Consequently, there is little evidence that the case study firms demonstrate the necessary conditions for process improvement and organizational learning to actually take place. The study also revealed that when process improvement does happen, its focus mainly centers on customer satisfaction or cost-saving, rather than on the improvement of shop floor work routines aiming at operational effectiveness. It also shows process improvement to be more reactive and ad hoc as opposed to the continuous, widespread, and long-term-oriented practices associated with continuous improvement and organizational learning