AMCIS 2017 Panel Report: Experiences in Online Education

2019 | Communications of the Association for Information Systems | Citations: 1

Authors: Ferran, Carlos; González, Macedonio Alanís; Esteves, Jose; Reynoso, Juan M. Gómez; Guzman, Indira

Abstract: In this AMCIS 2017 online education panel, five experienced business school prof ... Expand

Abstract: In this AMCIS 2017 online education panel, five experienced business school professors from differently sized public and private institutions in three different countries (USA, Mexico, and Spain) discussed how online education (i.e., eLearning, technology-mediated knowledge transfer) occurred in their institutions. They presented low-budget and high-budget examples and described what they have found to be best practices in eLearning at both the institution and the instructor level. They also demonstrated that one can accomplish online education in many different ways and with varying budgets, but, as long as one bases it on solid educational principles and mastery of the technology, it can be as effective as (if not more than) traditional face-to-face education. This report builds on their presentations and additional information gathered from the literature. Collapse

Topics: usability user interface distributed database online learning system information technology capability

Methods: qualitative interview survey quasi experiment

Multilevel Organizational Adaptation: Scale Invariance in the Scottish Healthcare System

2017 | Organization Science | Citations: 0

Authors: Dattée, Brice; Barlow, James

Abstract: We use the case of a “whole-system” change program in a national healthcare syst ... Expand

Abstract: We use the case of a “whole-system” change program in a national healthcare system to empirically examine the multilevel dynamics underlying organizational adaptation. Our analysis demonstrates how the cognitive distance between agents’ causal representations affects opportunities to cooperate in hierarchical systems. Using complexity theory, we identify a scale-invariant causal pathway that can be applied recursively across many organizational levels. At each level, three coupled feedback loops determine how local agents modify their cognitive representations to include uncovered interdependencies and synchronize their adaptive search across organizational boundaries: a “boundary work” loop, a “small wins” loop, and a “parochialism” loop. Our results also point to the scale-dependency of the strength of dissipative processes across levels. These novel results further develop the theory of organizational change and have practical implications for large multilevel organizations, especially regarding the sustainability of improvements. Collapse

Topics: health information system IT personell turnover resistance to change authorization statistical process control

Methods: qualitative interview case study theory development survey hierarchical linear modeling

Theories: complexity theory

Application of Fuzzy Risk Analysis for Selecting Critical Processes in Implementation of SPC with a Case Study

2016 | Group Decision and Negotiation | Citations: 0

Authors: Khorshidi, Hadi Akbarzade; Gunawan, Indra; Nikfalazar, Sanaz

Abstract: Fuzzy risk analysis is widely used in risk assessment of components by linguisti ... Expand

Abstract: Fuzzy risk analysis is widely used in risk assessment of components by linguistic terms. Fuzzy numbers are used to quantify the associated uncertainty. This study employs fuzzy risk analysis to evaluate processes for implementing statistical process control (SPC) in a specified manufacturing system. To reach this goal, fuzzy risk analysis has been applied based on both ranking and similarity of generalized trapezoidal fuzzy numbers in a stepwise procedure. Therefore, a new approach has been introduced for fuzzy risk analysis of processes to overcome the shortcomings of previous fuzzy risk analysis approaches. As a result, fuzzy risk analysis is used as a decision making technique to select critical processes under uncertainty. Also, the application of the proposed SPC implementation algorithm is illustrated in the manufacturing line of a car battery factory. Collapse

Topics: manufacturing information system decision making innovation management statistical process control

Methods: computational algorithm case study trade-off analysis method TOPSIS cumulative sum control chart

Mathematical modeling and Bayesian estimation for error-prone retail shelf audits

2015 | Decision Support Systems | Citations: 0

Authors: Chuang, Howard Hao-Chun

Abstract: Prevalent execution errors such as out-of-stock, inventory record inaccuracy, an ... Expand

Abstract: Prevalent execution errors such as out-of-stock, inventory record inaccuracy, and product misplacement jeopardize retail performance by causing low on-shelf availability, which discourages not only retailers who have lost sales but also manufacturers who have worked hard to deliver goods into retail stores. Thus, external service companies are hired by manufacturers to conduct manual inspection regularly. Motivated by the practical need of shelf audit service providers, we use a general cost structure to develop a decision support model for periodic inspection. Some qualitative insights about the intricate relationships among inspection efficacy, cost factors, failure rate of shelf inventory integrity, and optimal decisions are derived from analytics assuming risk-neutrality. From simulation experiments we also find that managers' risk preferences have non-trivial impacts on optimal decisions. Based on a total cost standpoint high-quality inspection is predominantly preferred regardless of the level of risk aversion. Finally, we propose a Bayesian statistical model and a Markov chain Monte Carlo approach to estimate model parameters such that managers can make empirically informed decisions. Our major contribution lies in developing a mathematical model that is practically applicable and proposing a Bayesian estimation approach to rationalize unobservable model parameters, which are influential to optimal decisions but often arbitrarily assumed by decision makers. Collapse

Topics: decision support accounting radio frequency identification statistical process control

Methods: simulation Bayesian analysis Monte Carlo simulation Markov chain Monte Carlo hazard function

Theories: expected utility theory

The impact of advanced analytics and data accuracy on operational performance: A contingent resource based theory (RBT) perspective

2014 | Decision Support Systems | Citations: 41

Authors: Chae, Bongsug (Kevin); Yang, Chenlung; Olson, David; Sheu, Chwen

Abstract: This study is interested in the impact of two specific business analytic (BA) re ... Expand

Abstract: This study is interested in the impact of two specific business analytic (BA) resources—accurate manufacturing data and advanced analytics—on a firms' operational performance. The use of advanced analytics, such as mathematical optimization techniques, and the importance of manufacturing data accuracy have long been recognized as potential organizational resources or assets for improving the quality of manufacturing planning and control and of a firms' overall operational performance. This research adopted a contingent resource based theory (RBT), suggesting the moderating and mediating role of fact-based SCM initiatives as complementary resources. This research proposition was tested using Global Manufacturing Research Group (GMRG) survey data and was analyzed using partial least squares/structured equation modeling. The research findings shed light on the critical role of fact-based SCM initiatives as complementary resources, which moderate the impact of data accuracy on manufacturing planning quality and mediate the impact of advanced analytics on operational performance. The implication is that the impact of business analytics for manufacturing is contingent on contexts, specifically, the use of fact-based SCM initiatives such as TQM, JIT, and statistical process control. Moreover, in order for manufacturers to take advantage of the use of data and analytics for better operational performance, complementary resources such as fact-based SCM initiatives must be combined with BA initiatives focusing on data quality and advanced analytics. Collapse

Topics: analytical information system data accuracy statistical process control organizational productivity data quality

Methods: survey partial least squares regression optimization model statistical hypothesis test partial least squares path modeling

Theories: resource based view of the firm

βP: A novel approach to filter out malicious rating profiles from recommender systems

2013 | Decision Support Systems | Citations: 3

Authors: Chung, Chen-Yao; Hsu, Ping-Yu; Huang, Shih-Hsiang

Abstract: Recommender systems are widely deployed to provide user purchasing suggestion on ... Expand

Abstract: Recommender systems are widely deployed to provide user purchasing suggestion on eCommerce websites. The technology that has been adopted by most recommender systems is collaborative filtering. However, with the open nature of collaborative filtering recommender systems, they suffer significant vulnerabilities from being attacked by malicious raters, who inject profiles consisting of biased ratings. In recent years, several attack detection algorithms have been proposed to handle the issue. Unfortunately, their applications are restricted by various constraints. PCA-based methods while having good performance on paper, still suffer from missing values that plague most user–item matrixes. Classification-based methods require balanced numbers of attacks and normal profiles to train the classifiers. The detector based on SPC (Statistical Process Control) assumes that the rating probability distribution for each item is known in advance. In this research, Beta-Protection (βP) is proposed to alleviate the problem without the abovementioned constraints. βP grounds its theoretical foundation on Beta distribution for easy computation and has stable performance when experimenting with data derived from the public websites of MovieLens. Collapse

Topics: missing data website recommender system statistical process control database system

Methods: computational algorithm experiment principal component analysis survey design data transformation

From information to operations: Service quality and customer retention

2012 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Padmanabhan, Balaji; Hevner, Alan; Cuenco, Michael; Shi, Crystal

Abstract: In business, information is abundant. Yet, effective use of that information to ... Expand

Abstract: In business, information is abundant. Yet, effective use of that information to inform and drive business operations is a challenge. Our industry-university collaborative project draws from a rich dataset of commercial demographics, transaction history, product features, and Service Quality Index (SQI) factors on shipping transactions at FedEx. We apply inductive methods to understand and predict customer churn in a noncontractual setting. Results identify several SQI variables as important determinants of churn across a variety of analytic approaches. Building on this we propose the design of a Business Intelligence (BI) dashboard as an innovative approach for increasing customer retention by identifying potential churners based on combinations of predictor variables such as demographics and SQI factors. This empirical study contributes to BI research and practice by demonstrating the application of data analytics to the fundamental business operations problem of customer churn. Collapse

Topics: service quality logistics management digital dashboard database system statistical process control

Methods: regression analysis method survey machine learning logistic regression descriptive statistic

EFFICIENT QUALITY MANAGEMENT OF HUMAN-BASED ELECTRONIC SERVICES LEVERAGING GROUP DECISION MAKING

2011 | European Conference On Information Systems | Citations: 0

Authors: Kern, Robert; Thies, Hans; Satzger, Gerhard

Abstract: Human-based electronic services (people services) provide a powerful way of outs ... Expand

Abstract: Human-based electronic services (people services) provide a powerful way of outsourcing tasks to a large crowd of remote workers over the Internet. Because of the limited control over the workforce in a potentially globally distributed environment, efficient quality management mechanisms are a prerequisite for successful implementation of the people service concept in a business context. Research has shown that multiple redundant results delivered by different workers can be aggregated in order to achieve a reliable result. However, existing implementations of this approach are highly inefficient as they multiply the effort for task execution and are not able to guarantee a certain quality level. Our weighted majority vote (WMV) approach addresses this issue by dynamically adjusting the level of redundancy depending on the historical error rates of the involved workers and the level of agreement among them. A practical evaluation in an OCR scenario demonstrates that the approach is capable of gaining reliable results at significantly lower costs compared to existing procedures. Collapse

Topics: quality management statistical process control crowdsourcing

Methods: optical character recognition simulation literature study experiment

Validating results of human-based electronic services leveraging multiple reviewers

2010 | Americas Conference on Information Systems | Citations: 0

Authors: Kern, Robert; Bauer, Cordula; Thies, Hans; Satzger, Gerhard

Abstract: Crowdsourcing in the form of human-based electronic services (people services) p ... Expand

Abstract: Crowdsourcing in the form of human-based electronic services (people services) provides a powerful way of outsourcing so called micro tasks to large groups of people over the Internet in order to increase the scalability and productivity of business processes. However, quality management of the work results continues to be a challenge. Most existing approaches assume that multiple redundant results delivered by different people for the same task can be aggregated in order to achieve a reliable result, but for a lot of task types an automatic aggregation or comparison of task results is not possible. Also, cost considerations and estimators for outgoing quality have experienced little attention. Our majority review approach addresses these challenges by leveraging the crowd not only for delivering work results but also for validating the results delivered by others. An evaluation in a business context confirms that the approach is capable of gaining reliable results. Collapse

Topics: internet technology quality management statistical process control anonymity user requirement

Methods: computational algorithm experiment literature study

Machine learning and genetic algorithms in pharmaceutical development and manufacturing processes

2009 | Decision Support Systems | Citations: 1

Authors: Chi, Hoi-Ming; Moskowitz, Herbert; Ersoy, Okan K.; Altinkemer, Kemal; Gavin, Peter F.; Huff, Bret E.; Olsen, Bernard A.

Abstract: We develop an adaptive Automated Intelligent Manufacturing System (AIMS) for Cas ... Expand

Abstract: We develop an adaptive Automated Intelligent Manufacturing System (AIMS) for Case 1:to a well-understood-pharmaceutical-process to demonstrate our methodology, Case 2:with clustering, to a not-well-controlled or understood-process for seemingly identical experiments yielding disparate results, Case 3:to scale-up a process from development to manufacturing, and Case 4:to deploy AIMS adaptively, to modify the process model and reoptimize the system contemporaneously, when predictive errors are significant. The results showed AIMS had both explanatory and predictive power. We have developed the following methodological extensions: a random probe method for feature selection, a simulation approach to establish tolerances for target inputs, and an adaptive capability integrated with statistical-process-control to modify the model. Collapse

Topics: statistical process control new product development decision making manufacturing information system database system

Methods: computational algorithm support vector machine machine learning experiment cluster analysis

Theories: statistical learning theory