Sensing the Future: A Design Framework for Context-Aware Predictive Systems

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Avital, Michel; Chatterjee, Samir; Furtak, Szymon

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ... Expand

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ever-growing streams of contextual data that convey information of interest about their operating environment. Although an increasing number of industries have embraced the utilization of sensors in routine operations, no clear framework is available to guide designers who aim to leverage contextual data collected from these sensors to develop predictive systems. In this paper, we applied design science research methodology to develop and evaluate a general framework that can help designers build predictive systems utilizing sensor data. Specifically, we developed a framework for designing context-aware predictive systems (CAPS). We then evaluated the framework through its application in MAN Diesel & Turbo, which served as a case company. The framework can be generalized into a class of demand-forecasting problems that rely on sensor-generated contextual data. The CAPS framework is unique and can help practitioners make better-informed decisions when designing context-aware predictive systems. Collapse

Topics: data quality evaluation criteria knowledge base systems design systems development

Methods: machine learning design science design artifact data transformation design process

Blockchain: Trouble in the Enterprise?

2023 | International Conference on Information Systems | Citations: 0

Authors: O’Leary, Daniel

Abstract: There has been substantial hype about the use of blockchain for supply chain an ... Expand

Abstract: There has been substantial hype about the use of blockchain for supply chain and trade finance, proclaiming that it would "change the world." Although during 2016-2018 blockchain was riding high on the hype curve, in 2019 it fell into the trough of disillusionment. Along the way, some consultants have recently stopped promoting blockchain and attention appears have shifted away from enterprise blockchain systems. As a result, it probably is not surprising that recently there have been several instances where those enterprise blockchain efforts went insolvent or were shutdown. This paper investigates those blockchain systems and identifies some of the potential factors affecting the success of those systems. We also provide some potential approaches to mitigate the limitations of those applications. Collapse

Topics: blockchain supply chain management digital transformation artificial intelligence Google+

Theories: lemon market theory

Towards Just-In-Time Arrival for Container Ships by the Integration of Prediction Models

2023 | HICSS | Citations: 0

Authors: Yu, J.; Voß, S.

Abstract: Within the context of green shipping, the concept of Just-In-Time (JIT) arrival ... Expand

Abstract: Within the context of green shipping, the concept of Just-In-Time (JIT) arrival has attracted much attention. Research achieves the JIT arrival for container ships by combining the berth allocation and quay crane assignment problem (BACAP) and the vessel speed optimization (VSO), both subject to the data exchange. Many prediction models of the research to date generally aim to reduce the uncertainty of the communicated estimated time of arrivals. There is a lack of research that simultaneously assesses the application effect of prediction models on both plans of the BACAP and the VSO. Therefore, this paper proposes a twostage model that integrates the prediction of the vessel arrival time with the optimization of the BACAP-VSO. The application in our specific case study shows that the random forest performs best in the first stage. The results are forwarded to the second stage and lead to a reduction of the service delay, fuel consumption cost, and vessel emissions. Collapse

Topics: Python missing data

Methods: optimization model machine learning method computational algorithm experiment case study

How Does Intelligent System Knowledge Empowerment Yield Payoffs? Uncovering the Adaptation Mechanisms and Contingency Role of Work Experience

2022 | Information Systems Research | Citations: 2

Authors: Chen, Liwei; Hsieh, J. J. Po-An; Rai, Arun

Abstract: Intelligent systems (IntelSys) are transforming the nature of work as humans and ... Expand

Abstract: Intelligent systems (IntelSys) are transforming the nature of work as humans and machines collectively perform tasks in novel ways. Although intelligent systems empower employees with algorithm-generated knowledge, they require employees to adapt how they work to enhance their job performance. We draw on the coping-adaptation framework as the overarching theoretical lens to explain how employees’ perceptions of IntelSys knowledge as an empowering external coping resource affect the mechanisms through which they adapt to IntelSys-induced changes to their work, as well as how their internal coping resources regulate their adaptation. Our coping-adaptation explanation of intelligence augmentation integrates (i) the empowering role of external coping resources, specifically IntelSys knowledge, captured as intelligent system knowledge empowerment (ISK-Emp); (ii) the benefit-maximizing adaptation mechanism (through infusion use enhancement) and the disturbance-minimizing adaptation mechanism (through role conflict reduction) that channel the impact of ISK-Emp on job performance; and (iii) the regulating role of internal resources, specifically, employees’ work experience, in influencing the importance of the adaptation mechanisms for the employee. We conduct studies in three distinct settings in which different intelligent systems were implemented to support employees’ knowledge work. Our findings show that ISK-Emp increases job performance through each of the two adaptation mechanisms. The benefit-maximization mechanism (via enhanced infusion use) plays a more important role for novice employees than for experienced employees, whereas the disturbance-minimization mechanism (via reduced role conflict) has higher importance for experienced employees than for novice employees. Our work provides insights into the critical role of adaptation mechanisms in linking ISK-Emp with performance outcomes and into the relative importance of the adaptation mechanisms through which job performance payoffs are realized by novice and experienced employees. Collapse

Topics: task productivity IT skill customer satisfaction system maintenance customer service

Methods: survey theory development chi squared test descriptive statistic statistical hypothesis test

Maritime Spare Parts Management: Current State-of-the-Art

2022 | HICSS | Citations: 0

Authors: Pahl, Julia

Abstract: Having the right spare part at the right time to the right place for ship mainte ... Expand

Abstract: Having the right spare part at the right time to the right place for ship maintenance to the minimal possible costs is an exigent management problem that maritime shipping companies face. This is especially challenging in bulk shipping where routes are not fixed, but subsequent port calls depend on spot market dynamics. Thus, spare parts allocation ahead in time is limited, but possible if failures rates of ship components and their timing can be foreseen, so that spare parts can be allocated to hedge against the risk of long waiting times and thus ship downtimes. Companies are very sensitive to the latter due to significant ship operational costs that accrue also during downtime, but without revenues. Thus, reducing ship downtimes by monitoring the condition of components key to the ships performance is essential to the task. However, shipping companies seem far away from applying sophisticated methods for forecasting and planning due to various challenges ranging from data gathering and cultivating an understanding of data quality needs, adaptation to move from preventive towards predictive and condition-based maintenance (CBM) thus enabling the introduction and application of decision support tools for demand forecasting, sourcing, spare parts allocation, and inventory management. In this paper, we investigate the current state of the art of spare parts logistics (SPL) management tightly related to CBM for maritime shipping and discuss the application of methods to the bulk carriage market. Collapse

Topics: knowledge base data quality decision support system logistics management

Methods: survey case study linear optimization operations research literature study

Use Of Blockchain As A Resource For Combating Corruption In Global Shipping: An Interpretive Case Study

2021 | Journal of Management Information Systems | Citations: 2

Authors: Sarker, Suprateek; Henningsson, Stefan; Jensen, Thomas; Hedman, Jonas

Abstract: Corruption is one of the most troubling societal challenges facing businesses to ... Expand

Abstract: Corruption is one of the most troubling societal challenges facing businesses today. Businesses have been combating corruption in fragmented ways, sometimes by creating anti-corruption policies applicable to certain stakeholders and, at other times, by harnessing digital technologies. Recently, the power of blockchain, with its capacity to provide full transactional disclosure and thereby reduce uncertainty, insecurity, and ambiguity in transactions, has been touted as being a game changer in the fight against corruption. Based on a study of the global shipping industry, we find that blockchain mitigates both process and document-related corruption. Based on these findings, we develop an understanding of how corruption may be combated using both social and digital/informational resources, including blockchain technology. Our model, drawing on past work on corruption, shows the complex interplay between identity, institutional actors, technical and other resources, and practices, and we develop conditions that could be effective in fighting corruption by using technologies such as blockchain. Collapse

Topics: blockchain pseudonymity cryptocurrency privacy marketing management

Methods: qualitative interview case study longitudinal research mixed method theoretical contribution

Theories: theory of economic development institutional theory

Agile IS Development Control: An Analysis of Four Different Scenarios and Their Control Implications

2021 | Americas Conference on Information Systems | Citations: 2

Authors: Virag, Peter; Bernroider, Edward; Remus, Ulrich

Abstract: Finding the optimal distribution of control and flexibility is an ongoing strug ... Expand

Abstract: Finding the optimal distribution of control and flexibility is an ongoing struggle in Information Systems Development (ISD). While flexibility allows projects to adapt to changing requirements, control helps reaching the desired time, cost and quality objectives. Agile approaches place higher emphasis on flexibility that challenges control conceptualizations typical in traditional ISD. Scarce research on controlling agile ISD provided conflicting control configuration recommendations probably due to different contexts and agile development rarely following instructions in a systematic manner. By drawing on a qualitative case study, we describe four distinct roles managers in agile ISD take contingent on contextual factors, and explore resulting control configurations in terms of control modes and enactment styles. Our findings in particular imply that costs of control fluctuate depending on the chosen role and that agency as a theoretical lens may be too narrow to understand the full spectrum of control activities in agile ISD projects. Collapse

Topics: Scrum agile software development IT skill

Methods: qualitative interview design methodology case study

Theories: lemon market theory agency theory stewardship theory signaling theory

Using Blockchain to Sustainably Manage Containers in International Shipping

2020 | International Conference on Information Systems | Citations: 12

Authors: Beck, Roman; Kildetoft, Mikkel Boding; Radonic, Nebojsa

Abstract: This paper investigates how blockchain technology can improve information flows ... Expand

Abstract: This paper investigates how blockchain technology can improve information flows on empty container repositioning at an inter-organizational level in the shipping industry. By adopting a theory-generating design science research approach, we develop and evaluate an industry-wide blockchain artefact, named Greenbox Platform, where container owners can register, trade and share containers. It brings efficiency for shipping companies via cost reduction through minimizing the need for empty container repositioning, and effectiveness for leasing companies via container proof of ownership. The paper contributes to its application domain by a practical, theory-driven and novel application of blockchain technology to the shipping industry. Theorizing on its development and evaluation, the paper provides preliminary groundwork for two nascent design principles: 1) Explicitly define a structure of incentives for interorganizational and cross-industrial blockchain applications where stakeholders’ interests are not necessarily aligned; and 2) Consider environmental sustainability as a non-functional requirement in the development of a blockchain artefact. Collapse

Topics: blockchain environmental sustainability Hyperledger smart contract business process improvement

Methods: qualitative interview theory development design principle design science design artifact

Augmenting the algorithm: Emerging human-in-the-loop work configurations

2020 | Journal of Strategic Information Systems | Citations: 0

Authors: Grønsund, Tor; Aanestad, Margunn

Abstract: How do configurations of humans and algorithms evolve as firms adopt artificial ... Expand

Abstract: How do configurations of humans and algorithms evolve as firms adopt artificial intelligence (AI) capabilities, and what are the implications for work and organization? We explored these questions through a two-year long case study of an organization in the international maritime trade that introduced automated algorithmic support for data analysis and prediction work. Drawing on a human–machine configuration perspective, we found that humans and the algorithm were configured and reconfigured in multiple ways over time as the organization dealt with the introduction of algorithmic analysis. In contrast to replacing human work, the emergent configurations required new roles and redistribution of extant expertise to augment and improve the accuracy of the algorithm. Our analysis suggests that the new configuration resembled a human-in-the-loop pattern, comprised of both the augmentation work of auditing (i.e. the generation of a ground truth and assessment of the algorithmic output against this) as well as the work of altering the algorithm and the data acquisition architecture. Our research points to the strategic importance of a human-in-the-loop pattern for organizational reflexivity to ensure that the performance of the algorithm meets the organization’s requirements and changes in the environment. Collapse

Topics: human in the loop human computer interaction IT work value creation data quality

Methods: computational algorithm case study field study qualitative interview natural language processing

Theories: dynamic capabilities theory

Novel Data Analytics Meets Conventional Container Shipping: Predicting Delays by Comparing Various Machine Learning Algorithms

2020 | HICSS | Citations: 0

Authors: Viellechner, Adrian; Spinler, Stefan

Abstract: Supply chain disruptions are expected to significantly increase over the next dec ... Expand

Abstract: Supply chain disruptions are expected to significantly increase over the next decades. In particular, delay of container vessels is likely to escalate due to rising congestion from continued growth of container shipping and higher frequency of extreme weather events. Predicting these delays could result in significant cost savings from optimizing operations. Both academic research and container shipping industry, however, lack analytical solutions to predict delay. To increase transparency on delay, we develop a prediction model based on 315 explanatory variables, 10 regression models, and 7 classification models. Using machine learning algorithms, we obtain best results for neural network and support vector machine with a prediction accuracy of 77 percent compared to only 59 percent of a naive baseline model. Various shipping players including sender, carrier, terminal operator, and receiver benefit from the easy-to-use prediction model to optimize operations such as buffers in schedules and the selection of ports and routes. Collapse

Topics: strategic management supply chain management natural hazard data quality logistics management

Methods: support vector machine regression analysis method computational algorithm literature study qualitative interview