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Factors influencing crime location choices are not only significant to rape investigations, but they are especially important for geographic profiling. The purpose of the current study is to use temporal, hunting behavior, and modus operandi factors to determine those variables that influence the victim encounter and release locations in serial sexual crime.

Due to the possible correlated nature of serial rapes, the authors use generalized estimating equations (GEE) on a sample of 361 rapes committed by 72 serial sex offenders.

Results indicate that temporal factors, offender hunting behavior, and modus operandi strategies are significant predictors of both the victim encounter and release sites, but the importance of these factors varies depending on whether the location is in a residential land use area, a private site, inside location, or a site that is familiar to the offender.

Police can learn from the current findings and apply them to subsequent rapes within a series by recognizing the timing of the offense, the type of hunting pattern and attack method used in prior sexual crimes committed by the same offender, and modus operandi strategies, to determine the type of location where the rapist is likely to offend next.

This paper is the first attempt to predict factors related to both the encounter and the victim release site in serial rapes using GEE.

In the past decade, firms have become more aware of supply chain disruptions and their impact on the firm. Developing a supply chain resilience organizational culture has been proposed as an effective way to manage supply chain risks. This study intends to explore how the geographical location risks impact the decision to develop a supply chain resilience strategy, in particular, to anticipate the disruption proactively and have a business continuity plan in place. Using a unique database including thousands of manufacturing locations that belong to over 7,000 firms across 102 countries, we test three hypotheses to understand if geographical location risks, frequency of disruptive events, and the region in which a site is located are factors for the likelihood of a firm having a business continuity plan at their locations. The study also seeks to understand if there are regional effects and firm effects affecting the decision to develop resilience. With a particular focus in Latin America and the firms with a manufacturing presence in that region. The main findings of the study are that natural disaster risks do tend to develop a culture of resilience, while macroeconomic risks tend to do the opposite. These results remain stable for firms' effects. The Latin America region shows no observable statistical difference in developing resilience compared to the Asia region. While the Northern America region shows more resilience compared to Asia. We conclude that economic risk is less predictable and harder to develop a plan for than disruptions, such as natural disasters. The findings of this study present an opportunity for governments to develop resilience plans that can make their countries more attractive for investment to multinational firms looking to establish new manufacturing locations around the world.

Presents an AHP (analytical hierarchy process) decision model for facility location selection from the view of organizations which contemplate locations of a new facility or a relocation of existing facilities. The AHP model provides a framework to assist managers in analysing various location factors, evaluating location site alternatives, and making final location selections. The primary principle of the AHP model is to match decision‐makers’ preferences with location site characteristics. The model requires that a number of potential sites have been proposed. Alternatives are then evaluated and compared under both quantitative and qualitative factors to allow managers to incorporate managerial experiences and judgement in the solution process. Uses an example problem to illustrate the solution process. Addresses managerial implications for future research.

The purpose of this paper is to investigate the strategic role of plants, in terms of the type and level of site competence, the relationship with the strategic reason for location, and the impact on operational performance.

The authors use a survey of 103 Swedish manufacturing plants that belong to global production networks and analyze patterns within this context to identify potential archetypes of plants with respect to plant roles, based on factor analysis and cluster analysis.

It is found that the areas of site competence can be grouped into three bundles, characterized thematically as production‐related, supply chain‐related and development‐related. The plants fall into three categories: some plants have only production‐related competences, some have competences concerning both production and supply chain, and the third group of plants possesses all three bundles of competences.

The results provide empirical evidence that site competences come in bundles in three steps according to themes rather than individually. No significant relationship was found between the level of site competence and the strategic reason for site location.

The results provide empirical support for the co‐location of product development and production, since plants with full responsibility for all competence bundles significantly outperform plants having only production‐related competences on cost efficiency, quality, and new product introductions.

The authors research patterns of site competence at a more detailed level than before in the related literature, as well as study the impact on performance, which has not been done before.

Site selection is critical for planning a real estate development project. Different mathematical and statistical models have been applied to support real estate developers in selecting suitable sites for development projects. This paper presents a new approach to site location selection that makes use of Geographical Information Systems (GIS) that incorporates the utilization of the Data Envelopment Analysis (DEA) method called a GISbased site selection system. With the implementation of this system, users can determine the most suitable site objectively and visually. The paper also demonstrates an application of the system to a residential building project.

Many States in America have enacted laws to encourage redevelopment of contaminated urban properties. The laws attempt to do this by addressing one barrier to redevelopment, the environmental liability attached to contaminated urban properties. In general, the laws attempt to remove or reduce the significance of that barrier by reducing or eliminating the environmental liability risk attached to these properties. Our hypothesis was that these efforts cannot encourage significant redevelopment because they fail to address non‐environmental barriers to urban redevelopment. To determine whether this legislative focus on environmental liability is misplaced, we conducted a survey of Northeast Ohio businesses which had decided, since the enactment of Ohio’s brownfields law, either to move to a new location, or to expand at an existing location. The survey asked businesses to rank the relative importance to their relocation decision of environmental and non‐environmental factors. The results of the survey show that numerous non‐environmental factors were of equal or greater importance to decision‐makers than the environmental status of the property. Therefore, legislative efforts to encourage redevelopment of contaminated urban properties must be expanded to address non‐environmental barriers to redevelopment

This paper aims to propose an innovative building information modelling (BIM)-based framework for multi-objective and dynamic temporary construction site layout design (SLD), which uses a hybrid approach of systematic layout planning (SLP) and mathematical modelling.

The hybrid approach, which follows a step-by-step process for site layout planning, is designed to facilitate both qualitative and quantitative data collection and processing. BIM platform is usedto facilitate the determination of the required quantitative data, while the qualitative data are generated through knowledge-based rules.

The multi-objective layout model represents two important aspects: layout cost and adjacency score. The result shows that the model meets construction managers’ requirements in not only saving cost but also assuring the preferences of temporary facility relationships. This implies that the integration of SLP and mathematical layout modelling is an appropriate approach to deliver practical multi-objective SLD solutions.

The proposed framework is expected to serve as a solution, for practical application, which takes the advantage of technologies in data collection and processing. Besides, this paper demonstrates, by using numerical experimentation and applying Microsoft Excel Solver for site layout optimisation, how to reduce the complexity in mathematical programming for construction managers.

The original contribution of this paper is the attempt of developing a framework in which all data used for the site layout modelling are collected and processed using a systematic approach, instead of being predetermined, as in many previous studies.

The purpose of this paper is to take a novel approach to help users better understand and be more aware of what third parties are learning about them as they browse the web.

The approach the authors take is to personalize the awareness by using JavaScript embedded in a web page to examine portions of a user's web‐browser history in order to ascertain web sites that the user has visited. The authors then personalize information reported to the user about what third‐party sites are tracking the user's behavior along with demographic information these sites may be inferring from these visited sites and the user's geographic location.

It was found that 63 percent of users agreed with a statement of concern for third parties monitoring activities, about half of the respondents agreed with a concern for knowledge about a user's location and a little more than half agreed to concern about inference of demographic information. It was found that females are more concerned about these issues than males. In terms of possible actions, a majority of users report using an ad blocker tool and even more delete cookies at least some amount of time. Using an opt‐out mechanism or removing browser history is done by less than 20 percent of users. Despite expressing more concern for information known by third parties, females are not significantly more likely to take actions that may limit what is leaked to these third parties. A contributor to this discrepancy is that females were much less likely to know their settings for many of the actions, indicating less familiarity with them.

Web privacy is an important social issue so helping users to better understand tracking of their actions, along with what actions can be taken to limit tracking, is important.

The paper takes an original approach to helping users understand what third parties learn about them and follows up that approach with a survey of user attitudes and actions on this important topic.

Terrorist attacks, natural disasters, and regional power outages from the past several years have all highlighted the low levels of disaster preparedness that exist at many firms. Supply chain disruptions caused by external events can have a significant financial and operational impact on firms not properly prepared. Therefore, improving disaster preparedness in supply chains is critical. One critical component of disaster management planning in supply chains is the storage of emergency supplies, equipment, and vital documents that will be needed in times of crisis. The goal of this paper is propose a decision process for establishing an efficient network of secure storage facilities that can effectively support multiple supply chain facilities.

The authors use the five‐stage disaster management process for supply chains as the framework for a proposed decision process for secure site locations. The decision process combines recommendations from FEMA's Disaster Management Guide with a set cover location model from the location sciences field to help establish a network of secure site locations.

Storing emergency supplies at every supply chain facility can be cost‐prohibitive. In addition, gaining access to emergency supplies that are stored at each facility may be prevented by some external events, such as fires or hurricanes, because items stored on‐site are destroyed or are inaccessible. Therefore, the proposed secure site selection process can balance operational effectiveness and cost‐efficiency by identifying the minimum number and possible locations of off‐site storage facilities.

One important contribution of the paper is that it combines recent recommendations for disaster preparedness in supply chains with established models in location sciences research to create an interdisciplinary solution to an important supply chain issue. Even though the storage of important documents, equipment, and materials is only one small part of disaster management planning, it is hoped that this model will do its share in helping supply chains become better prepared for the next emergency.

The COVID-19 pandemic has forced countries to consider how to reach vulnerable communities with extended outreach services to improve vaccination uptake. The authors created an optimization model to align with decision-makers' objective to maximize immunization coverage within constrained budgets and deploy resources considering empirical data and endogenous demand.

A mixed integer program (MIP) determines the location of outreach sites and the resource deployment across health centers and outreach sites. The authors validated the model and evaluated the approach in consultation with UNICEF using a case study from The Gambia.

Results in The Gambia showed that by opening new outreach sites and optimizing resource allocation and scheduling, the Ministry of Health could increase immunization coverage from 91.0 to 97.1% under the same budget. Case study solutions informed managerial insights to drive gains in vaccine coverage even without the application of sophisticated tools.

The research extended resource constrained LMIC vaccine distribution modeling literature in two ways: first, endogenous calculation of demand as a function of distance to health facility location enabled the effective design of the vaccine network around convenience to the community and second, the model's resource bundle concept more accurately and flexibly represented complex requirements and costs for specific resources, which facilitated buy-in from stakeholders responsible for managing health budgets. The paper also demonstrated how to leverage empirical research and spatial analysis of publicly available demographic and geographic data to effectively represent important contextual factors.