Understanding the Process of Information Technology Implementation

Research concerned with the implementation of information technology (IT) in organizations can be divided, roughly, into two streams: factor, or variance studies; and process studies (Markus and Robey, 1988). The great majority of work has adopted a variance approach where several factors that are likelyto be associated with successful IT implementation are identified, made operational, and then tested, usually using a cross-sectional design, with statistical methods. In reviewing these studies, Lucas (1981) notes that although some 150 factors have beenidentified, only a relatively few, limited to top management support and user involvement , are consistently associated with successful implementation. In addition, researchers tend to create new factor models rather than extending and confirming the most promising existing models, and no integrated model has emerged that explains a reasonable portion of the variance in implementation outcomes (although Lucas, Ginzberg and Schultz, 1990, made a valiant attempt in this regard). Process studies, on the other hand, seek to understand the process by which IT is implemented in organizations, using interpretive techniques based on interview, observational, and collected data. Although there are relatively few process studies, they are particularly appropriatefor theory building (Glaser and Strauss, 1967). Markus and Robey (1988) have pointed to the need for more process studies of technology implementation. In this paper we describe an ongoing process study of IT implementation in five settlement houses in New York City, using an action research approach (Argyris et. al., 1985). Settlement houses are the primary way that social services are delivered to community members of inner cities. From a research perspective, the IT implementation in the settlement houses is important in several respects. First, while IT implementations in profit-seeking firms have been widely researched, relatively few studies have been conducted in not-for-profit businesses. Not-for-profit firms are likely to differ from their profit-seeking counterparts in terms of their organizational values, goals, reward and control structures of individuals, organizational processes, staffing, environmental influences, and acquisition of resources. Second, few existing studies address the dynamicsinvolved in implementing IT in a group of cooperating, autonomous organizations. Our implementation study involves a confederation of five settlement houses and United Neighborhood Houses of NYC (UNH), an organization which provides technical assistance to the houses. This confederation is analogous in structure to IT partnerships and alliances, which have become popular among businesses in the for-profit secto

Two-Stream Transformer Architecture for Long Video Understanding

Pure vision transformer architectures are highly effective for short video classification and action recognition tasks. However, due to the quadratic complexity of self attention and lack of inductive bias, transformers are resource intensive and suffer from data inefficiencies. Long form video understanding tasks amplify data and memory efficiency problems in transformers making current approaches unfeasible to implement on data or memory restricted domains. This paper introduces an efficient Spatio-Temporal Attention Network (STAN) which uses a two-stream transformer architecture to model dependencies between static image features and temporal contextual features. Our proposed approach can classify videos up to two minutes in length on a single GPU, is data efficient, and achieves SOTA performance on several long video understanding tasks

PLOT-TAL -- Prompt Learning with Optimal Transport for Few-Shot Temporal Action Localization

This paper introduces a novel approach to temporal action localization (TAL) in few-shot learning. Our work addresses the inherent limitations of conventional single-prompt learning methods that often lead to overfitting due to the inability to generalize across varying contexts in real-world videos. Recognizing the diversity of camera views, backgrounds, and objects in videos, we propose a multi-prompt learning framework enhanced with optimal transport. This design allows the model to learn a set of diverse prompts for each action, capturing general characteristics more effectively and distributing the representation to mitigate the risk of overfitting. Furthermore, by employing optimal transport theory, we efficiently align these prompts with action features, optimizing for a comprehensive representation that adapts to the multifaceted nature of video data. Our experiments demonstrate significant improvements in action localization accuracy and robustness in few-shot settings on the standard challenging datasets of THUMOS-14 and EpicKitchens100, highlighting the efficacy of our multi-prompt optimal transport approach in overcoming the challenges of conventional few-shot TAL methods.Comment: Under Revie

A stakeholder-based system dynamics model of return-to-work: a research protocol

Background. Returning to work following a job-related injury or illness can be a complex process, influenced by a range of interrelated personal, psychosocial, and organizational components. System dynamics modelling (SDM) takes a sociotechnical systems perspective to view return-to-work (RTW) as a system made up of multiple feedback relationships between influential components. Design and Methods. To build the RTW SDM, a mixed-method approach will be used. The first stage, that has already been completed, involved creating a baseline model using key informant interviews. Second, in two manufacturing companies, stakeholder-based models will be developed through interviews and focus groups with senior management, frontline workers, and frontline supervisors. Participants will be asked about the RTW process in general and more targeted questions regarding influential components. Participants will also be led through a reference mode exercise where they will be asked to estimate the direction, shape and magnitude of relationships between influential components. Data will be entered into the software program Vensim that provides a platform for visualizing system-structure and simulating the effects of adapting components. Finally, preliminary model validity testing will be conducted to provide insights on model generalizability and sensitivity. Expected Impact of the study for Public Health. The proposed methodology will create a SDM of the RTW process using feedback relationships of influential components. It will also provide an important simulation tool to understand system behaviour that underlies complex RTW cases, and examine anticipated and unanticipated consequences of disability management policies

How a Goat-Farming Immigrant Changed Everything

In the dozens of articles and obituaries written about George Mitchell, who died late last month at 94, the Texas oilman, entrepreneur and philanthropist was remembered mostly as the father of the fracking boom, whose innovations led to the shale-gas revolution.https://digitalcommons.usu.edu/huntsman_news/1140/thumbnail.jp

Think Ethanol is Environmentally Friendly? Think Again

America\u27s prairies are disappearing at the fastest rate since the 1930s\u27 Dust Bowl.https://digitalcommons.usu.edu/huntsman_news/1087/thumbnail.jp

A Low Cost, Portable Fluorescence Correlation Spectrometer for Disease Diagnosis

People being treated for HIV need to periodically test to determine if their antiviral medication is effectively keeping their viral loads at a safe level. Individuals living in rural areas of developing countries would be more likely to get these viral load tests if an instrument existed which reduced costs and was small and rugged enough to be brought to the client rather than require the client to travel for hours to a clinic. The Diagnostics for Viral Disease team is developing such a device in cooperation with Dr. Edgar Simulundu and the Macha Research Trust in Zambia. Our design is based on advanced fluorescence spectroscopy utilizing a fluorescence protein probe, confocal optics, and low-cost, low-power electronics. This poster reviews work done in three subsystems of the overall instrument. First, we have optimized the program used during burst analysis spectroscopy for identification of individual viruses in dilute samples. Second, we have confirmed the operation of the amplifying and discriminating sections of the photon processing circuitry which converts light pulses into a digital signal ready to be processed in the signal analysis subsystem. Finally, we have completed the Field Programmable Gate Array (FPGA) and Raspberry Pi programming allowing successful transfer of the results of the signal processing in the FPGA to the Raspberry Pi for display to the end user. Going forward we will integrate these subsystems into a fully functional exploded prototype ready for the final stage of condensing the design into a portable prototype that can be tested and delivered to our client. Funding for this work provided by The Collaboratory for Strategic Partnerships and Applied Research.https://mosaic.messiah.edu/engr2022/1003/thumbnail.jp

Big Brother Declares War on Consumption

Doctors routinely advise patients to avoid a wide range of unhealthy behavior, such as smoking, excessive alcohol consumption, a poor diet, and lack of exercise. Beyond these salutary suggestions, however, there is also a growing paternalistic trend to prohibit activities like smoking—and through targeted taxation, governments are taking aim at food deemed unhealthy for having too much fat, preservatives, salt, or sugar. New York City Mayor Michael Bloomberg\u27s ban on large, sugary drinks was just ruled unconstitutional in a unanimous decision by the state Supreme Court\u27s Appellate Division—but this ruling isn\u27t likely to discourage hardened advocates.https://digitalcommons.usu.edu/huntsman_news/1141/thumbnail.jp