Location Context Research Articles

SoHAM: A Sound-Based Human Activity Monitoring Framework for Home Service Robots

Monitoring daily activities is essential for home service robots to take care of the older adults who live alone in their homes. In this article, we proposed a sound-based human activity monitoring (SoHAM) framework by recognizing sound events in a home environment. First, the method of context-aware sound event recognition (CoSER) is developed, which uses contextual information to disambiguate sound events. The locational context of sound events is estimated by fusing the data from the distributed passive infrared (PIR) sensors deployed in the home. A two-level dynamic Bayesian network (DBN) is used to model the intratemporal and intertemporal constraints between the context and the sound events. Second, dynamic sliding time window-based human action recognition (DTW-HaR) is developed to estimate active sound event segments with their labels and durations, then infer actions and their durations. Finally, a conditional random field (CRF) model is proposed to predict human activities based on the recognized action, location, and time. We conducted experiments in our robot-integrated smart home (RiSH) testbed to evaluate the proposed framework. The obtained results show the effectiveness and accuracy of CoSER, action recognition, and human activity monitoring. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article is motivated by the goal to develop companion robots that can assist older adults living alone. Among many capabilities, monitoring human daily activities is an essential one for such robots. Though computer vision or wearable sensors-based methods have been developed by other researchers, they are not practical due to the privacy concern and intrusiveness. Sound-based daily activity recognition can address these concerns and offer a viable solution. In this regard, our proposed method adopts microphones on the robot and a small set of motion sensors distributed in the home. The proposed theoretical framework was tested in a small-scale mock-up apartment with promising results. Before such companion robots can be deployed to real homes for elderly care, there is a need to improve the robustness of the algorithms. More thorough tests in various realistic home environments should be conducted to fully evaluate the performance of the robots. In addition, privacy concern related to audio capture should be further mitigated.

Sustainability Gets Thrown in the Trash: Comparing The Drivers and Barriers of Festival Waste Management In Canada and New Zealand

Ten years ago, in 2012, the United Nations announced a global waste crisis. The festival industry produces a significant amount of waste; however, management practices and policies across locational contexts can help address sustainability goals. This study used Mair and Jago's model to understand the drivers and barriers experienced by festival organizers in Canada and New Zealand. Five key findings emerged from this study: (1) similarities in context, drivers, barriers, and catalysts exist across these two countries; (2) internal forces were generally more significant drivers than external forces; (3) waste management companies hold the potential to be a significant catalyst; (4) the most prominent barriers were a lack of resources and a lack of knowledge/awareness/skill; (5) political leadership as a contextual factor can support the adoption of festival waste management practices. Recommendations are put forth to leverage drivers and fill management and policy gaps in support of the United Nations SDGs.

Varied female and male courtship behavior facilitated the evolution of a novel sexual signal

Abstract Sexual selection can contribute to speciation when signals and preferences expressed during mate choice are coupled within groups, but come to differ across groups (generating assortative mating). When new sexual signals evolve, it is important to investigate their roles in both mate location and courtship contexts, as both signaling functions are critical in mate choice. In previous work, researchers identified two new male morphs (silent and purring) in Hawaiian populations of the Pacific field cricket, Teleogryllus oceanicus. These morphs likely evolved because they protect males from an acoustically orienting parasitoid, yet still obtain some reproductive success. But, it remains unknown how the purring morph functions in close courtship encounters. We compared the relative success of the very recently evolved purring morph to that of the ancestral and silent morphs during courtship encounters. Purring males produce a novel courtship song and were not as successful in courtship as the ancestral type, but were mounted by females as often and as quickly as the obligately silent morph that arose and spread ~20 years ago. Purring males initiate courtship more quickly than other morphs, and females from populations where purring is common exhibit higher overall mounting rates. Thus, differences in the behavior of purring males and of females from populations where purring is common may have facilitated the origin of this novel sexual signal. We found no assortative mating between males of a given morph and females from their own population, and so we hypothesize that multiple male types will be maintained within the species because each achieves fitness in different ways.

On-device modeling of user’s social context and familiar places from smartphone-embedded sensor data

Context modeling and recognition represent complex tasks that allow mobile and ubiquitous computing applications to adapt to the user’s situation. The real advantage of context-awareness in mobile environments mainly relies on the prompt system’s and applications’ reaction to context changes. Current solutions mainly focus on limited context information generally processed on centralized architectures, potentially exposing users’ personal data to privacy leakage, and missing personalization features. For these reasons on-device context modeling and recognition represent the current research trend in this area. Among the different information characterizing the user’s context in mobile environments, social interactions and visited locations remarkably contribute to the characterization of daily life scenarios. In this paper we propose a novel, unsupervised and lightweight approach to model the user’s social context and her locations based on ego networks directly on the user mobile device. Relying on this model, the system is able to extract high-level and semantic-rich context features from smartphone-embedded sensors data. Specifically, for the social context it exploits data related to both physical and cyber social interactions among users and their devices. As far as location context is concerned, we assume that it is more relevant to model the familiarity degree of a specific location for the user’s context than the raw location data, both in terms of GPS coordinates and proximity devices. We demonstrate the effectiveness of the proposed approach with 3 different sets of experiments by using 5 real-world datasets collected from a total of 956 personal mobile devices. Specifically, we assess the structure of the social and location ego networks, we provide a semantic evaluation of the proposed models and a complexity evaluation in terms of mobile computing performance. Finally, we demonstrate the relevance of the extracted features by showing the performance of 3 different machine learning algorithms to recognize daily-life situations, obtaining an improvement of 3% of AUROC, 9% of Precision, and 5% in terms of Recall with respect to use only features related to physical context.

Get Up and Tie Your Fingers Eyemouth: Listening for dialogic resonance within a co-produced community performance

This article addresses concepts and theories of listening and the impact these can have on community theatre-making. The article draws on Jean-Luc Nancy’s analysis of listening as resonance (écouter) rather than listening to hear meaning (entendre), and considers his concept of renvoi (a return, send back, repeat). Get Up and Tie Your Fingers Eyemouth was a participatory performance work that the authors of this article – theatre director Fiona MacPherson and dance artist Liz Pavey – together with musician Eleanor Logan, realized with multigenerational cast in Eyemouth, Scotland. We analyse how listening techniques became the primary model of rehearsal activity and approach to performing which Fiona developed with the narrators in this production. An emphasis on listening supported the development of new methods of ensemble storytelling fostering a collective creative agency in how participants worked with the script and explored the musicality of the dialogue. These innovative methodologies question conventional and hierarchical delineation of artistic roles in performance making and storytelling challenging traditional notions of ownership in theatre practice. Our analysis considers listening as an embodied and emplacement activity particularly within the context of a coastal location. We argue that an attention to listening can foster aesthetic and somatic sensibility and awareness of interrelationship of self and environment. The article concludes with initial analysis of how we have been furthering our exploration of the application of listening practices to performance making within our subsequent collaboration with the Eyemouth community, Eyemouth: People and The Sea.

Small-series supply network configuration priorities and challenges in the EU textile and apparel industry

PurposeTechnology and market pressures are encouraging localized and small-series production in customer-driven industries. The purpose of this paper is to explore and understand the supply chain-, product- and process-design factors for small-series production in EU's textile and apparel industry, to understand configuration decisions, priorities and challenges.Design/methodology/approachAn interview study was undertaken with ten companies that represent diverse small-series production models and value chain roles. Interview data was analysed to identify supply network configuration characteristics, decision priorities and challenges.FindingsThree small-series production models emerged from the analysis, differing with respect to adoption of process postponement and customization. The findings confirm and extend past research regarding diverse decision priorities and product, process, supply chain structure/relationship configurations. Challenges identified relate to planning (priorities) and implementation (configuration). Whereas competence availability and digital technology challenges are common, several difficulties are linked to production model like tensions related to priorities and small volumes, which are not found with customization.Research limitations/implicationsFuture research can make comparisons with other industry and location contexts; adopt dynamic approaches to distinguish between design and reconfiguration processes; and address indicated paradoxical-tensions.Practical implicationsThe study findings can provide guidance for companies regarding identification of priorities and management of (planning/implementation) challenges impacting small-series production in T&A.Originality/valueThe paper brings a configuration perspective at the supply chain level to the problem of small-series production implementation, which demands holistic and context-specific understanding.

MEDICAL ASSIST FOR ISOLATED WARD PATIENTS IN HOSPITALS

Monitoring daily activities is essential for home service robots to take care of the older adults who live alone in their homes. In this article, we proposed a Medical Assist for isolated ward pateints in hospital framework by recognizing sound events in a home environment. First, the method of context-aware sound event recognition (CoSER) is developed, which uses contextual information to disambiguate sound events. The locational context of sound events is estimated by fusing the data from the distributed passive infrared (PIR) sensors deployed in the home. A two-level dynamic Bayesian network (DBN) is used to model the intratemporal and intertemporal constraints between the context and the sound events. Second, dynamic sliding time window-based human action recognition (DTW-HaR) is developed to estimate active sound event segments with their labels and durations, then infer actions and their durations. Finally, a conditional random field (CRF) model is proposed to predict human activities based on the recognized action, location, and time. We conducted experiments in our robot-integrated smart home (RiSH) testbed to evaluate the proposed framework. The obtained results show the effectiveness and accuracy of CoSER, action recognition, and human activitymonitoring. Key Words: Activity monitoring, context-awareness, elderly care, sound event.

The association of social and food preparation location context with the quality of meals and snacks consumed by young adults: findings from the MYMeals wearable camera study

PurposeThis study examined the association of social contexts and food preparation location with the quality of meals and snacks (predominately from the five food groups (FFG) versus discretionary foods) in a sample of young Australian adults (18–30 years old) using wearable camera technology.MethodsA sub-sample from the cross-sectional MYMeals study wore a wearable camera that captured images every 30 s for three consecutive days. Eating episodes from 133 participants (55% female) were classified across 4 domains: food quality (observed proportion of FFG and discretionary items), preparation location, social interaction, and screen use. Socio-economic status (SES) was assigned using residential postcode and gender self-reported. Associations of contexts and demographic factors with food quality stratified by meal type were determined using mixed binary logistic regression models.ResultsOf the 1840 eating episodes identified, 1775 were included in analysis (n = 8 preparation location and n = 57 food components that could not be identified were excluded). Food prepared at home was more likely to be from the FFG at lunch (OR = 4.8 95% CI 2.7–8.6), dinner (OR = 14.8 95% CI 7.6–28.6), and snacks (OR = 3.2 95% CI 2.2–4.8). Participants from higher SES areas were more likely to consume breakfasts (OR = 3.2 95% CI 1.4–7.4) and lunches (OR = 1.9 95% CI 1.0–3.7) predominately from the FFG. Females were more likely to consume lunches (OR = 2.0 95% CI 1.1–3.8) that was largely from the FFG. Social interaction and screen use were not associated with meal or snack quality.ConclusionWearable cameras have verified the importance of addressing meals and snacks prepared outside of home as an important contributor of discretionary food.

Design of hand detection based on attention and feature enhancement pyramids

Hand detection plays an important role in human–computer interaction. Because of the convenient and natural advantages of hands, hand detection is increasingly used in virtual reality, remote control, and other fields. However, since the complex background and the diversity of hand postures, the YOLOv4 algorithm for hand detection suffers from low accuracy and robustness. Therefore, A YOLOv4-HAND network, improved from YOLOv4, is proposed to solve the problem. We first use the dilation convolution to build the feature enhancement pyramid that enables the network to expand semantic information. Second, for better detection of different hand scales, we design a multiscale attention module to capture the correlation of channel information within different scales. Third, we design a head that incorporates a spatial attention module to compensate for the network’s lack of spatial contextual location information correlation. Finally, we use soft nonmaximum suppression to reduce the impact of occlusion. The results show that the YOLOv4-HAND detection network can achieve 83.22% and 93.95% mAP on the publicly available datasets Oxford hand and Egohands datasets. Compared with the most recent method, the YOLOv4-HAND network effectively improves the accuracy of hand detection for practical applications.

Unified system describing factors related to the eradication of an alien plant species.

BackgroundIn the field of biological invasions science, a problem of many overlapping terms arose among eradication assessment frameworks. Additionally there is a need to construct a universally applicable eradication evaluation system. To unify the terminology and propose an eradication feasibility assessment scale we created the Unified System for assessing Eradication Feasibility (USEF) as a complex tool of factors for the analysis of eradications of alien (both invasive and candidate) plant species. It compiles 24 factors related to eradication success probability reported earlier in the literature and arranges them in a hierarchical system (context/group/factor/component) with a possibility to score their influence on eradication success.MethodologyAfter a literature survey we analyzed, rearranged and defined each factor giving it an intuitive name along with the list of its synonyms and similar and/or related terms from the literature. Each factor influencing eradication feasibility is ascribed into one of four groups depending on the context that best matches the factor: location context (size and location of infestation, ease of access), species context (fitness and fecundity, detectability), human context (knowledge, cognition and resources to act) and reinvasion context (invasion pathways). We also devised a simple ordinal scale to assess each factor’s influence on eradication feasibility.ConclusionsThe system may be used to report and analyze eradication campaign data in order to (i) prioritize alien species for eradication, (ii) create the strategy for controlling invasive plants, (iii) compare efficiency of different eradication actions, (iv) find gaps in knowledge disabling a sound eradication campaign assessment. The main advantage of using our system is unification of reporting eradication experience data used by researchers performing different eradication actions in different systems.

Livelihood Transformation through the Existence of Mining and Tourism Industries: Case of North Halmahera District, North Maluku, Indonesia

Development has changed indigenous people's cultural structure and function, which is identical to a traditional lifestyle to the modern one, encouraging livelihood diversification or transformation. The development approach is vulnerable to socio-cultural, economic, and environmental changes, including in the mining and tourism sector. This article aims to describe the development process that has caused changes in the structure and function of indigenous culture and rural livelihoods in Northern Maluku, Indonesia. This study was done qualitatively using a case study approach to describe the livelihood strategies of indigenous people to cope with the existence of the mining and tourism industry’s activity in the North Halmahera Regency. The key informants involved in this research are traditional leaders, community leaders, and youth. Data collection is adjusted to the context of the research location, both around tourist destinations and mining areas. Data processing uses a triangulation approach. These findings indicate that the traditional community of Hibualamo had cultural structures and functions that mobilised access to social and natural capital. Furthermore, The challenges of globalisation cause a livelihood transformation and influence the capability of local communities to access financial capital, human capital, and physical capital.

A Review of Maps in PhDs: Is Your Map Worth a Thousand Words?

ABSTRACT Maps are useful for providing location context and for graphically presenting spatial relationships. They are often used in PhD dissertations to show the location of a study area or to present scientific results. These maps have to tell their story without the PhD candidate being present. We searched for maps in 575 PhD dissertations, and reviewed 192 maps in 65 of these: 38% were created by PhD candidates, 48% were inserted and 14% were adapted from other sources. Maps prepared by PhD candidates had more design shortcomings than other maps. Nevertheless, the number of problems with maps from other sources suggests that guidelines for including them in a dissertation could be useful. Our results suggest that PhD candidates use GIS software to design maps, but that there is room for improvement to guide users towards appropriate design choices. The results will help to plan support services for PhD candidates at universities.

From the Green Zone to Havana Syndrome: Making Geographic Sense of Rotationality and Hardship in Diplomacy

Abstract Most foreign ministries use a rotational system in deploying personnel abroad, with diplomats moving between foreign posts every few years and earning salary premiums based on the risks, dangers, and hardships associated with different foreign posts. We examine rotationality and hardship in diplomacy, identifying these as spatial and institutional practices for managing a global network of diplomatic personnel and sites. These are institutionalized in foreign ministries’ processes for assessing and compensating hardship and danger, and embodied in the design, function, and locational contexts of embassy buildings in foreign capitals. We rely on empirical examples from the US and Canadian foreign services, looking at US embassies in Berlin and Baghdad, and “Havana syndrome” among American and Canadian diplomats and their family members. We conclude that security-heavy forms of hardship assessment and management can limit diplomats’ ability to build local knowledge and constrain the interaction and openness usually prized in diplomatic practice.

A contextualist perspective to drivers of BIM in the architecture, engineering and construction (AEC) industry

There are disparities in the adoption of BIM between firms of different sizes and diverse locations. Although extant studies have explored drivers to BIM, there is a dearth of contextualist perspectives. How does the context of size (SME or large firm) and location (developed or developing economy) affects the perception of firms on drivers to BIM? Questions relating to these contexts are still underexplored in extant literature. Thus, this study aims to evaluate and analyse the divide of BIM drivers in these contexts via a comparative study. Data was collected through an international survey from 228 professionals in firms of diverse sizes and locations. The responses were analysed using mean score ranking, rank agreement factor, Mann-Whitney U test and principal components analysis. A comparative analyse was conducted which revealed that the SMEs and large firms differ in their perceptions of desire for innovation, availability of resources and collaboration as drivers to BIM. Similarly, it was highlighted that there is a deep divide between developed and developing countries which would underscore the transferability of best practices and global BIM solutions. The study provided empirical evidence of the BIM divide and would be of importance in bridging the traditionally fragmented construction industry.

A Spatial-Temporal-Semantic Method for Location Prediction in Indoor Spaces

While a large number of works concentrated on forecasting trajectories in the outdoor environment, predicting the movement of users in indoor settings has attracted much more attention recently because of the development of smartphones and maturity of Wi-Fi services, e.g., in office buildings. Predicting a user’s movement in indoor spaces can not only help better understand his/her intentions but also improve his/her living experience. While most of the prediction approaches to date tackle the problem by constructing the mathematical models to learn the mobility of objects, they cannot efficiently model the movement of indoor users in the constraint but filled with spatial-temporal-semantic info settings. In order to solve this issue, we propose a frequent subtrajectory-based Markov model that incorporates the spatial location, the temporal aspect, and the shop category context into a unified framework. We first present the frequent subtrajectory algorithm to model and predict adjacent moving points from physical movement perspective, and then, by taking the duration of stay at a specific location into account, we further improve the prediction precision. Finally, by taking location context in the indoor environment (e.g., shop categories) into consideration, we successfully model and predict the user’s future visiting points from the semantic perspective. To validate the effectiveness of our model, we conduct a complete evaluation on a large-scale real-world dataset with more than 261,269 trajectories collected from over 120,000 customers in a shopping mall. The experiment results demonstrate that our method performs significantly superior prediction performance comparing the state-of-the-art models.

Intergenerational gendered livelihoods: Marriage, matchmaking and Rural-Urban migration in China

This paper uses marriage as a lens to highlight norms, customs, identities and shared values that shape livelihoods and give meaning to intergenerational and gendered practices at the individual and household level. Drawing on feminist contributions to understanding power differences between women and men and between generations, this paper shows that while livelihood may be seen as involving mainly the economic and material aspects of living, it is equally a matter of how people pursue important goals in life such as marital formation, and how these goals are situated in social, cultural, historical and locational contexts. Based on interviews in Anhui and Sichuan provinces, I highlight how intergenerational livelihoods are influenced by gendered ideology and practice, in particular transactional marriage, parents’ and children’s responsibilities in enabling marital formation and lineage, and the pursuit of rural-urban migration to enhance men’s competitiveness in the marriage market. I foreground the voices and narratives of rural Chinese and rural-urban migrants, who share how they live their lives, resources that they have access to, strategies that they pursue, and their goals and desired outcomes that are situated in relevant social, cultural and spatial contexts. Quotes from interviewees underscore the deep-rooted patriarchy that has manifested itself through marriage, especially the traditions of patrilocal exogamy and transactional matchmaking. Specifically, I draw attention to the roles of house-building and bride price in marital formation, and their implications for rural-urban migration as a long-term household strategy and a way of life. By doing so, this paper emphasizes the social and cultural contexts, in particular gender and intergenerational relations, for research on rural-urban migration.

Aspect-level sentiment analysis with aspect-specific context position information

In recent years, an increasing number of researchers have focused on the aspect-level sentiment analysis in the field of natural language processing. A coarse-grained sentiment analysis at the document level and a sentiment analysis at the sentence level can only judge an entire text comprehensively, whereas a fine-grained sentiment analysis distinguishes each concrete aspect of the text and makes separate judgments on the sentiment polarity. The word vector representation obtained by a recurrent neural network lacks a description of the distance relationship between the context words and aspect, and traditional models rarely consider the influence of the association between contextual sentences. In this paper, we propose an aspect-level sentiment analysis model with aspect-specific contextual location information. By designing two asymmetrical contextual position weight functions respectively, the model adjusts the weight of contextual words according to the positions of the aspect words in the sentences, and alleviates the interference of the difference in the number of words on both sides of the aspect words on the judgment of sentimental polarity. By utilizing single-sentence-level and multiple-sentence-level bidirectional GRU layers, model will extract the influence of the contextual association of each sentence in the document on the aspect sentiment polarity of individual sentences. In addition, we analyze the distribution properties of hard samples and design a novel loss function for the class imbalance problem in the field of sentiment analysis. For dataset 15Rest, the accuracy of our model is 4.27% higher than that of ASGCN, whereas the f1-score, which is more indicative of the classification performance on an imbalanced dataset, can be seen to be improved by 4.31% in comparison to the ASGCN.

Naval museum spaces a study on accessibility and visibility based on the relationship between the sea and land

The relationship between location and context, design, and usage gains importance in architectural structures. The interrelated patterns of different syntactic and semantic layers compose the built space especially museums or exhibition spaces. The museum spaces have a considerable part of everyday life in terms of social interaction. The accessibility, visibility, and circularity of the museum spaces are affecting the integration of the human-space activity. The museums by the sea are recognized with the silhouette of the city. These museums are accessible from the seaway and overland routes. It is important that the museums as an exhibition space in the city are visible from both the sea and the land and provide two different accesses. For this reason, the study investigates two naval museums which emphasize the importance of location belonging and the type of the museum. Within the scope of the study, Genova Galata Museo Del Mare in Italy and the Istanbul Deniz Müzesi in Turkey with a similar location and function are examined. The museums are close to the seaway and visible from the sea. However, Istanbul Deniz Müzesi’s access is provided from the motorway due to the actual usage. On the other hand, in the case of Galata, the situation is the opposite. Thus, the museum structure is passed through in it and creates the connection space between the sea and land. The aim of the study is not only a representation of the maritime structure of the museum in a city that is the sea but also to highlight the importance of access from both sides. Furthermore, with the examination of the visibility, accessibility and circularity affect, the usage and time-related changes in the museum to be focused. For this purpose, use from the sea and the land, the relationship between the land and the sea will be evaluated as a bridge of the ground floor. In this study, the space syntax analysis method is applied. Space syntax provides an analytical analysis of human-environment relations, accessibility, and movement values. (Hillier et al., 1987). The relevant results will create a research base for further use and change over time. In conclusion, in two different sea countries’ naval museums are evaluated with the context of location and usage comparatively. The accesses of the museums and exhibitions areas are also evaluated by the visibility, accessibility, circularity analyses. A scientific base has been created to examine past, present, and future usage.

No Perfect Outdoors: Towards a Deep Profiling of GNSS-Based Location Contexts

While both outdoor and indoor localization methods are flourishing, how to properly marry them to offer pervasive localizability in urban areas remains open. Recently, proposals on indoor–outdoor detection have made the first step towards such an integration, yet complicated urban environments render such a binary classification incompetent. Fortunately, the latest developments in Android have granted us access to raw GNSS measurements, which contain far more information than commonly derived GPS location indicators. In this paper, we explore these newly available measurements in order to better characterize diversified urban environments. Essentially, we tackle the challenges introduced by the complex GNSS data and apply a deep learning model to identify representations for respective location contexts. We further develop two preliminary applications of our deep profiling: one, we offer a more fine-grained semantic classification than binary indoor–outdoor detection; and two, we derive a GPS error indicator that is more meaningful than that provided by Google Maps. These results are all corroborated by our extensive data collection and trace-driven evaluations.

Market proliferation and the impact of locational complexity on network restructuring

This manuscript investigates the problem of locational complexity, a type of complexity that emanates from a company’s territorial strategy. Using an entropy-based measure for supply chain structural complexity (pars-complexity), we develop a theoretical framework for analysing the effects of locational complexity on the profitability of service/manufacturing networks. The proposed model is used to shed light on the reasons why network restructuring strategies may result ineffective at reducing complexity-related costs. Our contribution is three-fold. First, we develop a novel mathematical formulation of a facility location problem that integrates the pars-complexity measure in the decision process. Second, using this model, we propose a decomposition of the penalties imposed by locational complexity into (a) an intrinsic cost of structural complexity; and (b) an avoidable cost of ignoring such complexity in the decision process. Such a decomposition is a valuable tool for identifying more effective measures for tackling locational complexity, moreover, it has allowed us to provide an explanation to the so-called addiction to growth within the locational context. Finally, we propose three alternative strategies that attempt to mimic different approaches used in practice by companies that have engaged in network restructuring processes. The impact of those approaches is evaluated through extensive numerical experiments. Our experimental results suggest that network restructuring efforts that are not accompanied by a substantial reduction on the target market of the company, fail at reducing complexity-related costs and, therefore, have a limited impact on the company’s profitability.