Minding the IS Soft Skills Gap: Evidence of Discourse Convergence and Organizational Field Structure

IS continually struggles with the ‘gap’ between academic preparation and industry needs. To close this gap, we need to better understand its causes. Recent IS research suggests that gaps may arise when issues receive attention in only practitioner or academic discourses. Institutionalism suggests that gaps can be attributed to the structure of the organizational field. We conduct two studies to investigate these rival explanations. In Study 1 we analyze the practitioner and academic discourses on the need for soft skills in IS. In Study 2 we identify important actors in the IS field and the degree to which they are tightly coupled as evidenced by linkages in their discourses. We then present a process model of the identification, development and assessment of requisite IS skills. We conclude that convergence between academic and practitioner discourses alone cannot close the gap between preparation and industry needs in a loosely coupled organizational field

Who’s holding the bag? Accountability in the criminal justice system

Lack of accountability and transparency are major impediments in efforts to minimize delays, ensure due process of law and reduce backlogged cases in the criminal justice system of . Existing oversight mechanisms to track cases through physical files and archives are prone to tampering and damage. The problem is particularly acute since there is little or no coordination between police, prosecution, and courts. There is no meaningful consolidation of crime and prosecution analytics and a total absence of transparency in the process. The current system makes it difficult to see who’s holding the proverbial bag. _x000D_ This paper presents results from a first of its-kind survey of our criminal justice system in . We highlight the importance and policy implications of our work by presenting empirical data from 750 prosecution vouchers using the results to motivate a case-flow design that integrates and maps the case-management practices of all three institutions involved

An exploration of the diffusion dynamics of Open Source Software (OSS): An Agent-Based Computational Economics (ACE) approach

Despite the rising popularity of Open Source Software (OSS), there is limited understanding of the factors that affect the diffusion of OSS at the organizational level. Review of the literature suggests that previous empirical and analytical studies on this subject matter though valuable in their own respect, either did not address the full spectrum of critical factors in one model or did not investigate the impact of critical factors in enough detail leaving some gaps in the literature. In an effort to bridge these gaps, this dissertation develops a model to a) jointly investigate the effect of critical variables other than price on the diffusion dynamics of OSS, b) investigate the effects of social networks or inter-organizational relationships on the diffusion dynamics of OSS, c) propose a new software price discounting scheme and compare its effectiveness against traditional software price discounting schemes on the diffusion dynamics of OSS. An Agent-Based Computational Economics (ACE) approach is adopted to develop a comprehensive simulation model to investigate the aforementioned research problems. Although, desktop operating system software is used as an exemplar to investigate the diffusion of its open source and proprietary alternatives, the framework proposed in the dissertation is general enough to be applied in the investigation of diffusion of other kinds of software as well

Multimodal Logistics in Disaster Relief

This chapter aims to study multimodal logistics planning in disaster scenarios through literature review and two case studies. It builds a framework around the types of problems addressed in operations research literature and the two phases of disaster operations—preparation and response. The multimodal logistics literature in disaster scenarios is mapped on this framework. It uncovers research gaps by comparing the literature with real-life settings. It finds that the coordination problem is an important aspect of multimodal logistics in disasters that requires further attention in order to close the gap between literature and practice

Revenue composition and financial health of nonprofit humanitarian and emergency health services

Purpose Emergency health and humanitarian nonprofits work under volatile circumstances that strain nonprofits' financial resources. This study investigates the impact of revenue composition on the financial health of these nonprofits and the impact of financial health on the likelihood of financial distress. Design/methodology/approach A sample of 11,335 emergency nonprofits from 2003 to 2020 was obtained through form 990 data and studied through a difference generalized method of moments (GMM) approach for the impact of revenue composition on financial health. The impact of financial health on financial distress was studied through panel logistics regression. Findings Revenue diversification adversely affects the financial health of nonprofit emergency health and humanitarian organizations contrary to the implications of modern portfolio theory. The financial health of nonprofit emergency health and humanitarian organizations is persistent through the significant positive effect of lags in most cases. Originality/value The emergency health subsector of nonprofits was studied separately due to the unique nature of the sectors' operations and operating environment. The impact of revenue composition was investigated on key dimensions of financial health. Omitted variable bias, simultaneity and dynamic endogeneity were handled through difference GMM

Decision-tree inspired classification algorithm to detect Tuberculosis (TB)

Pakistan has the fifth highest incidence of Tuberculosis (TB) in the world. The current tests for TB diagnosis are smear and culture tests which have accuracies of about 40% and 70% respectively. They are inefficient, complicated and relatively expensive to perform in developing countries. In this paper, we present a novel computational predictive algorithm by modifying the standard decision tree that allows us to efficiently detect TB with high accuracy. It employs supervised learning to classify the samples into patients and healthy groups based on MFI values of different antibodies with an accuracy of about 94%, outperforming the traditional classifiers including decision trees, kNN, random forests and support vector machines (SVM). Our algorithm allows simultaneous, bench-top analysis of thousands of samples per day, does not rely on highly skilled or technical staff and provides easily interpretable results. Our work strongly suggests that developing, testing and implementing automated diagnostic algorithms such as ours can be helpful in overcoming infrastructural and human-resource constraints in poorly resourced countries

Effects of Conventional UPS vs Smart Energy Metering Solution on Harmonics and Grid Stability for Low Voltage Consumers in Developing Countries: A Case Study of Pakistan

To deal with frequent power outages in developing countries, people turn to solutions like uninterruptible power supply (UPS), which stores electric energy during normal operating hours and use it to meet energy needs during rolling blackout intervals. Locally produced UPSs of poorer power quality are widely accessible in the marketplaces, and they have a negative impact on power quality. The charging and discharging of the batteries in these UPSs generate significant amount of power losses in weak grid environments. The Smart-UPS is our proposed smart energy metering (SEM) solution for low voltage consumers that is provided by the distribution company. It does not require batteries, therefore there is no power loss or harmonic distortion due to corresponding charging and discharging. Through load flow and harmonic analysis of both traditional UPS and Smart-UPS systems on ETAP, this paper examines their impact on the harmonics and stability of the distribution grid. The simulation results demonstrate that Smart-UPS can assist fixing power quality issues in a developing country like Pakistan by providing cleaner energy than the battery-operated traditional UPSs

IoT-enabled Smart Energy Metering Solution with Soft-UPS for Developing Countries

Due to its potential in improving the efficiency of energy supply, smart energy metering (SEM) has become an area of interest with the surge in Internet of Things (IoT). SEM entails remote monitoring and control of the sensors and actuators associated with the energy supply system. This provides a flexible platform to conceive and implement new data driven Demand Side Management (DSM) mechanisms. The IoT enablement allows the data to be gathered and analyzed at requisite granularity. In addition to efficient use of energy resources and provisioning of power, developing countries face an additional challenge of temporal mismatch in generation capacity and load factors. This leads to widespread deployment of inefficient and expensive Uninterruptible Power Supply (UPS) solutions for limited power provisioning during resulting blackouts. Our proposed “Soft-UPS” allows dynamic matching of load and generation through a combination of managed curtailment. This eliminates inefficiencies in the energy and power value chain and allows a data-driven approach to solving a widespread problem in developing countries, simultaneously reducing both upfront and running costs of conventional UPS and storage. A scalable and modular platform is proposed and implemented in this paper. The architecture employs “WiMODino” using LoRaWAN with a “Lite Gateway” and SQLite repository for data storage. Role based access to the system through an android application has also been demonstrated for monitoring and control