Decision Framework for Engaging Cloud-Based Big Data Analytics Vendors

Organizations face both opportunities and risks with big data analytics vendors, and the risks are now profound, as data has been likened to the oil of the digital era. The growing body of research at the nexus of big data analytics and cloud computing is examined from the economic perspective, based on agency theory (AT). A conceptual framework is developed for analyzing these opportunities and challenges regarding the use of big data analytics and cloud computing in e-business environments. This framework allows organizations to engage in contracts that target competitive parity with their service-oriented decision support system (SODSS) to achieve a competitive advantage related to their core business model. A unique contribution of this paper is its perspective on how to engage a vendor contractually to achieve this competitive advantage. The framework provides insights for a manager in selecting a vendor for cloud-based big data services

Digital Rule of Thumb: A Natural Experiment on Autocomplete in Search Engines

Search engines are an essential part of our lives. However, we do not fully understand what affects users\u27 search inputs. One of the most notable features affecting search inputs is autocomplete, an intelligent agent suggesting queries while typing. Understanding the impact of autocomplete helps eCommerce companies retain customers; examining its impact is difficult since all search engines have adopted it, and experiments are risky for firms. We overcome the challenges by leveraging a novel natural experiment of an eCommerce company. Our preliminary results suggest that the deactivation of autocomplete for the incorrect keyword led to a substantial drop in website visits in the PC channel compared to the mobile channel. In addition, website visits substantially shifted from the incorrect keyword to the correct keyword in the mobile channel but not in the PC environment. This short paper is expected to shed new light on our understanding of autocomplete\u27s impact

Management of Digital Evidence: Body Worn Camera Use by Law Enforcement Agents

Body Worn Camera (BWC) is an emergent technology that has started to be deployed in law enforcement agencies in the recent past. Although there are many expected advantages to adoption and implementation of BWC, potential negative concerns range from loss of public privacy to failure in appropriate management of digital evidence. As insiders in police organizations, law enforcement agents have the capacity of either correctly or incorrectly managing digital evidence. Having clear and well-developed written policies regarding the BWC based on organizational, moral, and individual issues, is important for successful BWC implementation. In this research, we focus on ethical judgement regarding potential privacy violations of law enforcement agents in the context of BWC usage. Finding from this study will help in understanding perceptions of police officers and their ethical judgement and will assist in development of policies and provide actionable guidelines

Understanding Crowdsourcing Contest Fitness Strategic Decision Factors and Performance: An Expectation-Confirmation Theory Perspective

Contest-based intermediary crowdsourcing represents a powerful new business model for generating ideas or solutions by engaging the crowd through an online competition. Prior research has examined motivating factors such as increased monetary reward or demotivating factors such as project requirement ambiguity. However, problematic issues related to crowd contest fitness have received little attention, particularly with regard to crowd strategic decision-making and contest outcomes that are critical for success of crowdsourcing platforms as well as implementation of crowdsourcing models in organizations. Using Expectation-Confirmation Theory (ECT), we take a different approach that focuses on contest level outcomes by developing a model to explain contest duration and performance. We postulate these contest outcomes are a function of managing crowdsourcing participant contest-fitness expectations and disconfirmation, particularly during the bidding process. Our empirical results show that contest fitness expectations and disconfirmation have an overall positive effect on contest performance. This study contributes to theory by demonstrating the adaptability of ECT literature to the online crowdsourcing domain at the level of the project contest. For practice, important insights regarding strategic decision making and understanding how crowd contest-fitness are observed for enhancing outcomes related to platform viability and successful organizational implementation

Electric Car Sharing Service Using Mobile Technology

Millions of urban dwellers face difficulties owning a car because of congested and accident-prone infrastructure, sky-high parking fees, and high maintenance cost. The need for car ownership can be reduced by providing an efficient and effective car sharing system. In this paper, we propose an electric car sharing service system using mobile technology, which can be a substitute for fuel consuming cars. Our system will be helpful in saving the resources and the energy consumed in producing and owning cars as well as improving the quality of life in urban areas

An Examination of Emotions in the Boston Bombing Twitterverse

Social Network Services (SNS) such as Twitter play an important role in the way people share their emotions or cognitions regarding specific events. Emotions can be spread via SNS and can spur user’s actions. Therefore, managing emotion in SNS is important. In this Research In Progress, we investigate Twitterverse that is associated with event related hazard describing keywords (Explosion, Bomb) and their related emotions in the Boston Bombing context. We compare the results with an exploration of Twitterverse that is not associated with the above hazard describing keywords. A sentiment analysis shows Positive emotion, Discrepancy, Tentativeness, and Certainty had consistent patterns over five days of the Boston Bombing incident. When keywords were excluded, the expressed emotions or cognition were higher than when were keywords included. This paper contributes by examining how emotion and cognition differed across keywords relating to the extreme event

Pedestrians’ Intention Recognition Method using Hidden Semi-Markov Model: The Case of Crossing the Crosswalk

It is very important to ensure that elder people can perform safe outdoor activities, especially crossing the crosswalk. In this paper, we propose a novel system that can recognize intentions of the elder pedestrians in the vicinity of traffic lights to support the safe crossing. In order to recognize the intention, we applied Hidden Semi-Markov Model (HSMM), which is the most widely adopted method in this field of research. Our system consists of three functions: spatial context identification, HSMM-based learning, and intention recognition. To implement our system, we used GPS data collected from sensors embedded in the elder pedestrians’ smartphone, traffic lights data collected through Open API, and pre-classified activity data for activity learning. In the experimental section, to evaluate the performance of our system, we conducted experiments to find optimum k of k-prototype clustering and to determine the number of hidden states. The key contribution of this paper is to recognize the intentions from the pedestrians’ point of view for the safety of the pedestrians, not the intention of the driver for safe driving of the car

Security Violation Prevention; CPTED in the context of information Security

Mitigating Information Security (IS) violations is crucial since organizations relying more on their information systems. This cannot be achieved only by advancements in security software and hardware technologies, but also there is a need to have multi-perspective approaches toward security violation prevention in organizations. Thus, we apply Crime Prevention through Environmental Design (CPTED) approach to develop conceptual research model in the context of IS. Our model considers both technical and non-technical perspectives as well as covers human-related, managerial and physical aspects of IS management. Moreover, we propose the moderation roles of two personality traits (trait anxiety and negative affectivity) on the relationships between all five variables of the research model and IS violation because impacts of personality is an inseparable part of human behaviors. To our best knowledge, this is the first study that applied CPTED into IS domain. This may help to reduce security violation in the organization

Internal Audit Function (IAF)’s Competencies and Cybersecurity Audit

Internal Audit Functions (IAFs) are expected to play a critical role in cybersecurity risk management as they play critical role in enterprise risk management. In this emergent research forum, we proposed a research model, based on auditors’ risk assessment that explains how different types of IAFs competencies -1) Information Technology (IT), 2) Governance, Risk, and Compliance (GRC) and 3) Communication competencies- can play a role in information security audit. Since cybersecurity risk management demands concerted effort on the part of different stakeholders including boards, audit committee and so on, the research will shed light on the critical role of IAFs to address cybersecurity risk management. This research contributes to the information system auditing literature by highlighting the importance of auditor competencies in security audit. Furthermore, the findings of the research will help practitioners (external auditors) evaluate control activities when they assess higher security risks in organizations’ information systems. \