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.
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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.
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PURPOSE: To study the preliminary effects and feasibility of the “Traffic Light Method for somatic screening and lifestyle” (TLM) in patients with severe mental illness. DESIGN AND METHODS: A pilot study using a quasi-experimental mixed method design with additional content analyses of lifestyle plans and logbooks. FINDINGS: Significant improvements were found in body weight and waist circumference. Positive trends were found in patients’ subjective evaluations of the TLM. The implementation of the TLM was considered feasible. PRACTICE IMPLICATIONS: The TLM may contribute to a higher quality of care regarding somatic screening and lifestyle training.
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Background: The present study investigates the suitability of various treatment outcome indicators to evaluate performance of mental health institutions that provide care to patients with severe mental illness. Several categorical approaches are compared to a reference indicator (continuous outcome) using pretest-posttest data of the Health of Nation Outcome Scales (HoNOS). Methods: Data from 10 institutions and 3189 patients were used, comprising outcomes of the first year of treatment by teams providing long-term care. Results: Findings revealed differences between continuous indicators (standardized pre-post difference score ES and ΔT) and categorical indicators (SEM, JTRCI, JTCS, JTRCI&CS, JTrevised) on their ranking of institutions, as well as substantial differences among categorical indicators; the outcome according to the traditional JT approach was most concordant with the continuous outcome indicators. Conclusions: For research comparing group averages, a continuous outcome indicator such as ES or ΔT is preferred, as this best preserves information from the original variable. Categorical outcomes can be used to illustrate what is accomplished in clinical terms. For categorical outcome, the classical Jacobson-Truax approach is preferred over the more complex method of Parabiaghi et al. with eight outcome categories. The latter may be valuable in clinical practice as it allows for a more detailed characterization of individual patients.
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The study aims to describe the implementation of Activity Scheduling (AS) as a nursing intervention in an inpatient population of older adults with a major depressive disorder. DESIGN AND METHODS: In a single case report, the implementation of the intervention was described. FINDINGS: This case report shows that AS, when adapted into a brief and prescriptive course, can be beneficial for depressed elderly in an inpatient care setting. PRACTICE IMPLICATIONS: Although previous research shows promising results, there is a need for additional research on the effectiveness of the intervention when AS is executed by nurses.
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The purpose of the research we undertook for this Conference Paper was to investigate whether marketing campaigns for specific types of drinks could be directed towards age cohorts rather than towards intercultural differences between countries. We developed consumer profiles based on drinking motives and drinking behavior by age cohorts. We hypothesized that differences between countries in the youngest age groups are smaller than in the older age groups, where country specific tradition and culture still plays a more prominent role. We, therefore tested, from the data obtained by the COnsumer BEhaviouR Erasmus Network (COBEREN), the hypothesis that the extent to which the age specific profiles differ between countries increases with age. The results confirm our hypothesis that the extent to which drinking motives differ between countries increases with age. Our results suggest that marketing campaigns which are directed towards drinking motives, could best be tailored by age cohort, in particular when it concerns age group 18-37 and more particular for beer, spirits and especially premix drinks. Marketing campaigns for non-alcoholic beverages should be made specific for the British countries and the Western countries, but even more effectively be made specific for the age cohort 18-37.
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In case of a major cyber incident, organizations usually rely on external providers of Cyber Incident Response (CIR) services. CIR consultants operate in a dynamic and constantly changing environment in which they must actively engage in information management and problem solving while adapting to complex circumstances. In this challenging environment CIR consultants need to make critical decisions about what to advise clients that are impacted by a major cyber incident. Despite its relevance, CIR decision making is an understudied topic. The objective of this preliminary investigation is therefore to understand what decision-making strategies experienced CIR consultants use during challenging incidents and to offer suggestions for training and decision-aiding. A general understanding of operational decision making under pressure, uncertainty, and high stakes was established by reviewing the body of knowledge known as Naturalistic Decision Making (NDM). The general conclusion of NDM research is that experts usually make adequate decisions based on (fast) recognition of the situation and applying the most obvious (default) response pattern that has worked in similar situations in the past. In exceptional situations, however, this way of recognition-primed decision-making results in suboptimal decisions as experts are likely to miss conflicting cues once the situation is quickly recognized under pressure. Understanding the default response pattern and the rare occasions in which this response pattern could be ineffective is therefore key for improving and aiding cyber incident response decision making. Therefore, we interviewed six experienced CIR consultants and used the critical decision method (CDM) to learn how they made decisions under challenging conditions. The main conclusion is that the default response pattern for CIR consultants during cyber breaches is to reduce uncertainty as much as possible by gathering and investigating data and thus delay decision making about eradication until the investigation is completed. According to the respondents, this strategy usually works well and provides the most assurance that the threat actor can be completely removed from the network. However, the majority of respondents could recall at least one case in which this strategy (in hindsight) resulted in unnecessary theft of data or damage. Interestingly, this finding is strikingly different from other operational decision-making domains such as the military, police and fire service in which there is a general tendency to act rapidly instead of searching for more information. The main advice is that training and decision aiding of (novice) cyber incident responders should be aimed at the following: (a) make cyber incident responders aware of how recognition-primed decision making works; (b) discuss the default response strategy that typically works well in several scenarios; (c) explain the exception and how the exception can be recognized; (d) provide alternative response strategies that work better in exceptional situations.
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Spatial decisions on distribution channel layout involve the layout of the transport and storage system between production and consumption as well as the selection of distribution centre locations. Both are strategic company decisions to meet logistics challenges, i.e. delivering the right product at the right location on time. In this paper we study the main factors and sub factors that drive spatial decisions on distribution channel layout. The current literature has a strong focus on normative approach and lacks descriptive research into these factors. In the second part of the study, we investigated the importance of the factors. Best-Worst Method (BWM) has been used to calculate the factor weights. BWM provides consistent results and requires fewer comparisons than ‘matrix based’ methods. An online survey was used to collect the data. According to total sample of respondents, the most important factors are ‘Logistics costs’, ‘Service level’ and ‘Demand level’. Logistics costs being the most important factor is in line with Supply Chain Management literature. Logistics experts consider ‘Customer demand’ as the second most important factor, whereas decision makers consider ‘Service level’ the second most important factor. A limitation of the research is that the majority of respondents are from Europe and the USA. For future research we suggest to test how respondents from non-Western countries value the importance of several factors.
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The moment of casting is a crucial one in any media production. Casting the ‘right’ person shapes the narrative as much as the way in which the final product might be received by critics and audiences. For this article, casting—as the moment in which gender is hypervisible in its complex intersectional entanglement with class, race and sexuality—will be our gateway to exploring the dynamics of discussion of gender conventions and how we, as feminist scholars, might manoeuvre. To do so, we will test and triangulate three different forms of ethnographically inspired inquiry: 1) ‘collaborative autoethnography,’ to discuss male-to-female gender-bending comedies from the 1980s and 1990s, 2) ‘netnography’ of online discussions about the (potential) recasting of gendered legacy roles from Doctor Who to Mary Poppins, and 3) textual media analysis of content focusing on the casting of cisgender actors for transgender roles. Exploring the affordances and challenges of these three methods underlines the duty of care that is essential to feminist audience research. Moving across personal and anonymous, ‘real’ and ‘virtual,’ popular and professional discussion highlights how gender has been used and continues to be instrumentalised in lived audience experience and in audience research.
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Electric vehicles have penetrated the Dutch market, which increases the potential for decreased local emissions, the use and storage of sustainable energy, and the roll-out and use of electric car-sharing business models. This development also raises new potential issues such as increased electricity demand, a lack of social acceptance, and infrastructural challenges in the built environment. Relevant stakeholders, such as policymakers and service providers, need to align their values and prioritize these aspects. Our study investigates the prioritization of 11 Dutch decision-makers in the field of public electric vehicle charging. These decision-makers prioritized different indicators related to measurements (e.g., EV adoption rates or charge point profitability), organization (such as fast- or smart-charging), and developments (e.g., the development of mobility-service markets) using the best-worst method. The indicators within these categories were prioritized for three different scenario's in time. The results reveal that priorities will shift from EV adoption and roll-out of infrastructure to managing peak demand, using more sustainable charging techniques (such as V2G), and using sustainable energy towards 2030. Technological advancements and autonomous charging techniques will become more relevant in a later time period, around 2040. Environmental indicators (e.g., local emissions) were consistently valued low, whereas mobility indicators were valued differently across participants, indicating a lack of consensus. Smart charging was consistently valued higher than other charging techniques, independent of time period. The results also revealed that there are some distinct differences between the priorities of policymakers and service providers. Having a systematic overview of what aspects matter supports the policy discussion around EVs in the built environment.
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