This thesis studies the factors that influence physical distribution structure design. Distribution Structure Design (DSD) concerns the spatial layout of the distribution channel as well as the location(s) of logistics facilities. Despite the frequent treatment of DSD in supply chain handbooks, an empirically validated conceptual framework of factors is still lacking. This thesis studies DSD in multiple industry sectors (Fashion, Consumer Electronics, Online Retail) and proposes a conceptual framework.
MULTIFILE
This paper studies the factors that drive distribution structure design (DSD), which includes the spatial layout of distribution channels and location choice of logistics facilities. We build on a generic framework from existing literature, which we validate and elaborate using interviews among industry practitioners. Empirical evidence was collected from 18 logistics experts and 33 decision-makers affiliated to shippers and logistics service providers from the fashion, consumer electronics and online retail sectors. It turns out that interviewees share similar rankings of main factors across industries, and even confirm factor weights from earlier research established using multi-criteria decision analysis, which would indicate that the framework is sector- neutral at the highest level. The importance attached to subfactors varies between sectors according to our expectations. We were able to identify 20 possible new influencing subfactors. The results may support managers in their decision-making process, and regional policy-makers with regard to spatial planning and regional marketing. The framework is a basis for researchers to help improve further quantitative DSD support models.
DOCUMENT
Distribution structures, as studied in this paper, involve the spatial layout of the freight transport and storage system used to move goods between production and consumption locations. Decisions on this layout are important to companies as they allow them to balance customer service levels and logistics costs. Until now there has been very little descriptive research into the factors that drive decisions about these structures. Moreover, the literature on the topic is scattered across various research streams. In this paper we review and consolidate this literature, with the aim to arrive at a comprehensive list of factors. Three relevant research streams were identified: Supply Chain Management (SCM), Transportation and Geography. The SCM and Transportation literature mostly focus on distribution structure including distribution centre (DC) location selection from a viewpoint of service level and logistics costs factors. The Geography literature focuses on spatial DC location decisions and resulting patterns mostly explained by location factors such as labour and land availability. Our review indicates that the main factors that drive decision-making are “demand level”, “service level”, “product characteristics”, “logistics costs”, “labour and land”, “accessibility” and “contextual factors”. The main trade-off influencing distribution structure selection is “service level” versus “logistics costs”. Together, the research streams provide a rich picture of the factors that drive distribution structure including DC location selection. We conclude with a framework that shows the relative position of these factors. Future work can focus on completing the framework by detailing out the sub factors and empirically testing the direction and strength of relationships. Cooperation between the three research streams will be useful to further extend and operationalize the framework.
DOCUMENT
The design of a spatial distribution structure is of strategic importance for companies, to meet required customer service levels and to keep logistics costs as low as possible. Spatial distribution structure decisions concern distribution channel layout – i.e. the spatial layout of the transport and storage system – as well as distribution centre location(s). This paper examines the importance of seven main factors and 33 sub-factors that determine these decisions. The Best-Worst Method (BWM) was used to identify the factor weights, with pairwise comparison data being collected through a survey. The results indicate that the main factor is logistics costs. Logistics experts and decision makers respectively identify customer demand and service level as second most important factor. Important sub-factors are demand volatility, delivery time and perishability. This is the first study that quantifies the weights of the factors behind spatial distribution structure decisions. The factors and weights facilitate managerial decision-making with regard to spatial distribution structures for companies that ship a broad range of products with different characteristics. Public policy-makers can use the results to support the development of land use plans that provide facilities and services for a mix of industries.
DOCUMENT
Research statementOur study analyses the factors that drive decision-making on distribution structures, including the layout of distribution channels and the locations of distribution centres. Distribution is a primary firm activity, which strongly influences logistics costs and logistics performance. Distribution is a challenging activity as customer demand is often volatile and unpredictable. Consumers continuously expect higher service related to distribution, e.g., same day delivery and more flexibility in delivery locations. Therefore, it is of strategic importance to shippers and Logistics Service Providers (LSPs) to decide which distribution channel layout to use and, accordingly, plan distribution centre location(s). Distribution structure selection concerns the number and locations of distribution centres, as part of the larger corporate planning process. The main questions we strive to answer in this paper are: (1) what are the main criteria that determine the spatial layout of distribution structures? and (2) how important are these criteria, relative to each other?Methodology The literature on distribution channel design mostly revolves around optimization methods; we are not aware of literature that takes a descriptive approach. We therefore develop a descriptive conceptual model that includes these factors, developed from the contextual literature around this decision. The second part of the study concerns the measurement of the relative importance of these factors. We implemented an elaborate survey and used the Best-Worst Method (BWM) to identify these weights. The survey considers different experts (e.g., logistics managers versus logistics professors) and population segments (e.g., in-house versus outsourced distribution).Data and resultsCurrently we are completing the survey dedicated to evaluating the above factors. We have received sufficient response to estimate a first model. These first estimations already provide useful results. Final estimations will be completed and reported in June 2017. At the I-NUF conference we will be able to present the results and analysis of all factors when comparing respondents and parameters.Preliminary conclusionsBased on literature review, eight main factors – divided into 33 sub factors – are included in our research: 1) Demand factors, 2) Service level factors, 3) Product Characteristics factors, 4) Logistics costs factors, 5) Proximity-related location factors, 6) Accessibility-related location factors, 7) Resources-related location factors and 8) Institutional factors. A number of hypotheses were built from the literature analysis relating, for example, to the relative importance of service- and cost- related factors within different industries. We will revisit these hypotheses and provide the quantitative results of the importance of the individual factors in our paper and at the conference.
DOCUMENT
Distribution structures and distribution centre (DC) locations are essential for logistics companies to optimise logistics costs and service levels. This paper reviews Supply Chain Management (SCM), Geography and Economic Geographic literature on distribution structure and DC locations decision-making. Two central decision-making elements are discussed: process steps and decision-making factors. Added value of our paper is 1) A literature review 2) Conclusions on the state of current scientific knowledge in three research streams 3) A research agenda. Reviewing literature shows decision-making factors are renowned, however, importance of factors in each process step is unknown. Results also show literature diverges on which process steps logistics companies take (descriptive) or should optimally take (prescriptive) in distribution structure and DC location decision-making. Thus, more research is needed. Developing a descriptive conceptual model and testing on several industry sectors will be valuable to understand differences on distribution structure and DC location decision-making.
DOCUMENT
Plant photosynthesis and biomass production are associated with the amount of intercepted light, especially the light distribution inside the canopy. Three virtual canopies (n = 80, 3.25 plants/m2) were constructed based on average leaf size of the digitized plant structures: ‘small leaf’ (98.1 cm2), ‘medium leaf’ (163.0 cm2) and ‘big leaf’ (241.6 cm2). The ratios of diffuse light were set in three gradients (27.8%, 48.7%, 89.6%). The simulations of light interception were conducted under different ratios of diffuse light, before and after the normalization of incident radiation. With 226.1% more diffuse light, the result of light interception could increase by 34.4%. However, the 56.8% of reduced radiation caused by the increased proportion of diffuse light inhibited the advantage of diffuse light in terms of a 26.8% reduction in light interception. The big-leaf canopy had more mutual shading effects, but its larger leaf area intercepted 56.2% more light than the small-leaf canopy under the same light conditions. The small-leaf canopy showed higher efficiency in light penetration and higher light interception per unit of leaf area. The study implied the 3D structural model, an effective tool for quantitative analysis of the interaction between light and plant canopy structure.
MULTIFILE
Several studies show that logistics facilities have spread spatially from relatively concentrated clusters in the 1970s to geographically more decentralized patterns away from urban areas. The literature indicates that logistics costs are one of the major influences on changes in distribution structures, or locations and usage of logistics facilities. Quantitative modelling studies that aim to describe or predict these phenomena in relation to logistics costs are lacking, however. This is relevant to design more effective policies concerning spatial development, transport and infrastructure investments as well as for understanding environmental consequences of freight transport. The objective of this paper is to gain an understanding of the responsiveness of spatial logistics patterns to changes in these costs, using a quantitative model that links production and consumption points via distribution centers. The model is estimated to reproduce observed use of logistics facilities as well as related transport flows, for the case of the Netherlands. We apply the model to estimate the impacts of a number of scenarios on the spatial spreading of regional distribution activity, interregional vehicle movements and commodity flows. We estimate new cost elasticities, of the demand for trade and transport together, as well as specifically for the demand for the distribution facility services. The relatively low cost elasticity of transport services and high cost elasticity for the distribution services provide new insights for policy makers, relevant to understand the possible impacts of their policies on land use and freight flows.
DOCUMENT
The circular economy (CE) is heralded as reducing material use and emissions while providing more jobs and growth. We explored this narrative in a series of expert workshops, basing ourselves on theories, methods and findings from science fields such as global environmental input-output analysis, business modelling, industrial organisation, innovation sciences and transition studies. Our findings indicate that this dominant narrative suffers from at least three inconvenient truths. First, CE can lead to loss of GDP. Each doubling of product lifetimes will halve the related industrial production, while the required design changes may cost little. Second, the same mechanism can create losses of production jobs. This may not be compensated by extra maintenance, repair or refurbishing activities. Finally, ‘Product-as-a-Service’ business models supported by platform technologies are crucial for a CE transition. But by transforming consumers from owners to users, they lose independence and do not share in any value enhancement of assets (e.g., houses). As shown by Uber and AirBNB, platforms tend to concentrate power and value with providers, dramatically affecting the distribution of wealth. The real win-win potential of circularity is that the same societal welfare may be achieved with less production and fewer working hours, resulting in more leisure time. But it is perfectly possible that powerful platform providers capture most added value and channel that to their elite owners, at the expense of the purchasing power of ordinary people working fewer hours. Similar undesirable distributional effects may occur at the global scale: the service economies in the Global North may benefit from the additional repair and refurbishment activities, while economies in the Global South that are more oriented towards primary production will see these activities shrink. It is essential that CE research comes to grips with such effects. Furthermore, governance approaches mitigating unfair distribution of power and value are hence essential for a successful circularity transition.
LINK
This article examines the network structure, criminal cooperation, and external interactions of cybercriminal networks. Its contribution is empirical and inductive. The core of this study involved carrying out 10 case analyses on closed cybercrime investigations – all with financial motivations on the part of the offenders - in the UK and beyond. Each analysis involved investigator interview and access to unpublished law enforcement files. The comparison of these cases resulted in a wide range of findings on these cybercriminal networks, including: a common division between the scam/attack components and the money components; the presence of offline/local elements; a broad, and sometimes blurred, spectrum of cybercriminal behaviour and organisation. An overarching theme across the cases that we observe is that cybercriminal business models are relatively stable.
DOCUMENT
