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On the Evolution of Product Portfolio of Cooperatives versus IOFs: An Agent-Based Analysis of the Single Origin Constraint
Full text linkAn agent-based model is developed to address the relationship between the ownership structure of an
enterprise and the evolution of its product portfolio. The coherence and evolution of a product
portfolio is operationalized by transition rules regarding the Moore environment. The distinguishing
feature of a cooperative is the single origin constraint according to Cook (1997), which is modelled
as a cooperative assigning an infinite lifetime to the first product in its product portfolio, while all
other products have finite lifetime. All product of an investor-owned firm (IOF) are assumed to have
finite lifetime. Our simulation results show that the single origin constraint pulls the activities of the
cooperative in one cluster centered around the first activity, while the IOF’s product portfolio
develops in a centrifugal way. The cooperative and the IOF are more diversified in a mixed duopoly
A Data-driven Approach to Enhance Worker Productivity by Optimizing Facility Layout
Full text linkThe facility layout problem (FLP) is the problem of determining non-overlapping positions
of departments on the shop floor to minimize material handling costs. Traditional methods for
solving FLPs consider pairwise (from-to) flows to optimize layouts. This paper shows that these
traditional methods underestimate the total travel distance of a layout, when departments have
more than a single input/output point and some flows consist of visits to more than two de-
partments. To accurately calculate the traveled distances, the actual routes of the workers and
transporters (so-called connected movements) in the system need to be determined. The con-
nected movements of the workers in a facility can now be captured using the Internet of Things
network and stored in the cloud server for analysis. We propose a mixed-integer non-linear
programming model for the FLP that minimizes the total travel distance using these connected
movements as the input data. Because of the complexity of the problem, a biased random key
genetic algorithm is used to find the layout. To ensure the validity of the method, a case study is
carried out at a fertilizer production company that implemented an Internet of Things network
to capture worker movement data to minimize worker productivity loss via an improved layout.
By using these connected movements, the best layout for the case company is found. The results
of the proposed data-driven optimization method indicate that leveraging connected movements
can reduce the total travel distance by 10.6% compared to the best possible layout generated
by the traditional pairwise method in the case study
Does accountability enhance service delivery?
Full text linkThis article assesses whether the Local Government Council’s Scorecard Initiative, implemented in
Uganda since 2009, achieved its intended impact of enhancing service delivery by providing information
on the performance of local government. We analyse a district-level panel dataset (2005–2016) with
administrative data, as well as Afrobarometer data on citizen perceptions (2005–2017). Empirically,
we exploit the phasing in of the scorecard for a meticulous difference-in-difference framework with
district-specific trends. The results show some small measurable impacts of the scorecard along the
so-called ‘long route of accountability’ on public service delivery. Scorecard districts appear to spend less
of their budgets in comparison with non-scorecard districts. This points to greater budgetary restraint of
local government councils in scorecard districts. Although no direct impacts on service delivery can be
detected, districts with more electoral competition in their constituencies perform better on one
service-delivery indicator, the primary school leaving exam pass rate. Concomitantly, the scorecard
impacts on perceptions of corruption, as citizens of scorecard districts perceive the local councillors as
less corrupt compared to citizens of non-scorecard districts. This result can be interpreted as an indica-
tion of the trust-enhancing effect of government scorecards and civic engagement. Overall, our results
provide a quantitative contribution to the literature on accountability by demonstrating that civil society
reporting mechanisms about the performance of political representatives only trickle down slowly to
improved services. The findings suggest that the sustained implementation of instruments to provide cit-
izens with more information about their political representatives may have a positive impact on civil
society perceptions as well as relevant political and policy outcomes. Like earlier research, we find that
impacts also depend on political competitiveness, thus highlighting the positive role of democracy.
Ó 2022 The Authors. Published by Elsevier Ltd
Victims’ Fundamental Need for Safety and Privacy and the Role of Legislation and Empirical Evidence
Full text linkVarious laws, guidelines and other types of regulation have been created that introduced new rights worldwide for victims of crime. Many of these rights focus on active victims who wish to step into the open and to orally express their views and experiences in court. Rights and wishes to remain in the background and to preserve one’s privacy received less attention. This article focuses primarily on the wishes of victims that reveal their intention to not play an active role in the criminal process, and on victims who fear an invasion of their safety and privacy. According to the literature, such wishes and needs can be considered to be fundamental. The article questions the empirical basis for the present victim legislation: are the new laws that have been created over the decades founded on empirically established victim needs, or on presumed victim needs? The article concludes with a plea for a more extensive use of empirical findings that shed light on victim wishes in the legislation and the criminal process
Automatic detection of actionable findings and communication mentions in radiology reports using natural language processing
Full text link__Objectives:__ To develop and validate classifiers for automatic detection of actionable findings and documentation of nonroutine communication in routinely delivered radiology reports.
__Methods:__ Two radiologists annotated all actionable findings and communication mentions in a training set of 1,306 radiology reports and a test set of 1,000 reports randomly selected from the electronic health record system of a large tertiary hospital. Various feature sets were constructed based on the impression section of the reports using different preprocessing steps (stemming, removal of stopwords, negations, and previously known or stable findings) and n-grams. Random forest classifiers were trained to detect actionable findings, and a decision-rule classifier was trained to find communication mentions. Classifier performance was evaluated by the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity.
__Results:__ On the training set, the actionable finding classifier with the highest cross-validated performance was obtained for a feature set of unigrams, after stemming and removal of negated, known and stable findings. On the test set, this classifier achieved an AUC of 0.876 (95% CI 0.854-0.898). The classifier for communication detection was trained after negation removal, using unigrams as features. The resultant decision rule had a sensitivity of 0.841 (95% CI 0.706-0.921) and specificity of 0.990 (95% CI 0.981-0.994) on the test set.
__Conclusions:__ Automatic detection of actionable findings and subsequent communication in routinely delivered radiology reports is possible. This can serve quality control purposes and may alert radiologists to the presence of actionable findings during reporting
Machine Learning-Based Feasibility Checks for Dynamic Time Slot Management
Full text linkOnline grocers typically let customers choose a delivery time slot to receive their goods. To ensure a reliable service, the retailer may want to close time slots as capacity fills up. The number of customers that can be served per slot largely depends on the specific order sizes and delivery locations.
Conceptually, checking whether it is possible to serve a certain customer in a certain time slot given a set of already accepted customer orders involves solving a vehicle routing problem with time windows. This is challenging in practice as there is little time available and not all relevant information is known in advance. We explore the use of machine learning to support time slot decisions in this
context. Our results on realistic instances using a commercial route solver suggest that machine learning can be a promising way to assess the feasibility of customer insertions. On large-scale routing problems it performs better than insertion heuristic
Diversity matters in the world of finance: does ethnic and religious diversity hinder financial development in developing countries
Full text linkThis paper investigates the relationship between ethnic and religious diversity and financial development by using the data for 102 developing countries. It is widely accepted that financial depth, and the more ready availability of finance, has a central role to play in fostering economic growth. We hypothesize that financial development in developing countries, especially those at the early stages of economic development, may be retarded by pre-existing ethnic and religious diversity, which may produce conflict. However, we believe that this risk can be moderated by sound institutional functioning – including good governance and democracy. Financial depth is measured by M2 and private credit (as a percentage of GDP); the Alesina fragmentation index is used for measuring ethnic and religious diversity, varieties of democracy (VDEM) and the quality of governance datasets. Our results are supportive of our hypothesis that ethnic and religious diversity can indeed hamper financial development; these risks, however, are mitigated by well-functioning institutional arrangement
Do physical work factors and musculoskeletal complaints contribute to the intention to leave or actual dropout in student nurses?
Full text link_Background:_ Little is known, whether physical workload and musculoskeletal complaints (MSCs) have an impact on the intended or actual dropout of nursing students in the later years of their degree program.
_Purpose:_ Studying the determinants of intention to leave and actual dropout from nursing education. We hypothesized that physical workload and MSCs are positively associated with these outcomes.
_Methods:_ A prospective cohort study among 711 third-year students at a Dutch Bachelor of Nursing degree program. Multivariable backward binary logistic regression was used to examine the association between physical work factors and MSCs, and intention to leave or actual dropout.
_Results:_ Intention to leave was 39.9% and actual dropout 3.4%. Of the nursing students, 79% had regular MSCs. The multivariable model for intention to leave showed a significant association with male sex, working at a screen, physical activity, decision latitude, co-worker support, distress and need for recovery. The multivariable model for dropout showed a significant association with living situation (not living with parents), male sex, sick leave during academic year and decision latitude.
_Conclusions:_ Our research shows that the prevalence of MSCs among nursing students is surprisingly high, but is not associated with intention to leave nor with actual dropout
Antimicrobial Use and Antimicrobial Resistance in Community-Acquired Urinary Tract Infections
Full text linkThis thesis describes the prescribing of antimicrobial drugs by GP's to treat urinary tract infections, possible risk factors for antimicrobial resistance in urinary tract infections and the possible effects of antimicrobial drug use on the composition of the microbiota
How Do Victims With the Need for Protection Judge Their Experiences With the Police in the Netherlands?
Full text linkThis article presents a preliminary analysis of how victims who report to the police for protection in the Netherlands judge their experiences with the police, in comparison with victims reporting crimes for other reasons. An existing dataset was used: the data was originally collected for a comprehensive survey among crime victims of 12 years and older in 2016. Female victims of violent (sexual and non-sexual) crimes constitute the major part of the victims for whom protection is the most important reporting reason. Victim perceptions of police contribution to safety as well as police information were investigated. The analyses show that overall, victim perceptions of the police’s contribution to safety are rather negative. Contribution to safety is judged somewhat better by victims for whom protection is their most important reporting reason; however, the respondents who are positive still form a minority. Police information is judged positively by more victims than contribution to safety. Of the respondents for whom protection is a reporting reason, victims of sexual crimes appear to judge police information positively more often than victims of other crime types