management information system research paper

Journal of Management Information Systems (JMIS) is a top-tier scholarly journal aiming to advance the understanding and practice of information systems.

JMIS is published quarterly by Taylor & Francis.

Message from the Editor in Chief: Vladimir Zwass

Web Site Editors: Yang Gao and Sagar Samtani

Past Web Site Editor: David Eargle

Journal Profile | Board of Editors

Journal Rankings, FT50 Listing, H-Index, and Impact Factor

Information for Contributors

Contributor Index

Keyword Index

Award-Winning Papers

Subscription Information

Export References | RSS | Calls for Papers | About this Site

Journal of Management Information Systems Volumes and Issues

Volume 40 number 4 2023, volume 40 number 3 2023.

Special Section: Digital Strategies for Business Readiness Guest Editors: Kauffman, Robert J and Lahiri, Atanu

Volume 40 Number 2 2023

Volume 40 number 1 2023.

Special Issue: Information Systems, Artificial Intelligence, and Analytics to Support Value Creation in Communities and Organizations Guest Editors: de Vreede, Gert-Jan and Nunamaker, Jay F

Volume 39 Number 4 2022

Volume 39 number 3 2022.

Special Section: Reevaluating Markets for Information Guest Editors: Kauffman, Robert J and Weber, Thomas A

Volume 39 Number 2 2022

Volume 39 number 1 2022, volume 38 number 4 2021.

Special Issue: Fake News on the Internet Guest Editors: Dennis, Alan R , Galletta, Dennis F , and Webster, Jane

Volume 38 Number 3 2021

Special Section: Improving New Digital Market Mechanisms Guest Editors: Kauffman, Robert J and Weber, Thomas A

Volume 38 Number 2 2021

Special Section: Strategic Integration of Blockchain Technology into Organizations Guest Editors: Kohli, Rajiv and Liang, Ting-Peng

Volume 38 Number 1 2021

Volume 37 number 4 2020, volume 37 number 3 2020.

Special Section: The Economics of Sharing and Information Security Guest Editors: Kauffman, Robert J and Weber, Thomas A

Volume 37 Number 2 2020

Special Section: The Growing Complexity of Enterprise Software Guest Editors: Briggs, Robert O and Nunamaker, Jay F

Volume 37 Number 1 2020

Volume 36 number 4 2019.

Special Section: Social Influence and Networked Business Interaction Guest Editors: Kauffman, Robert J and Weber, Thomas A

Volume 36 Number 3 2019

Special Issue: Immersive Systems Guest Editors: Cavusoglu, Huseyin , Dennis, Alan R , and Parsons, Jeffrey

Volume 36 Number 2 2019

Volume 36 number 1 2019.

Special Section: Engineering Artifacts and Processes of Information Systems Guest Editors: Giboney, Justin S , Briggs, Robert , and Nunamaker, Jr., Jay

Volume 35 Number 4 2018

Volume 35 number 3 2018.

Special Section: The Digital Transformation of Vertical Organizational Relationships Guest Editors: Kauffman, Robert J and Weber, Thomas A

Special Section: The Transformative Value of Cloud Computing: A Decoupling, Platformization, and Recombination Theoretical Framework Guest Editors: Benlian, Alexander , Kettinger, William J , Sunyaev, Ali , and Winkler, Till J

Volume 35 Number 2 2018

Special Issue: Strategic Value of Big Data and Business Analytics Guest Editors: Chiang, Roger HL , Grover, Varun , Liang, Ting-Peng , and Zhang, Dongsong

Volume 35 Number 1 2018

Special Issue: Financial Information Systems and the Fintech Revolution Guest Editors: Gomber, Peter , Kauffman, Robert J , Parker, Chris , and Weber, Bruce W

Volume 34 Number 4 2017

Special Issue: Creating Social Value with Information Guest Editors: Giboney, Justin Scott , Briggs, Robert O , and Nunamaker Jr, Jay F

Volume 34 Number 3 2017

Special Issue: Action Research in Information Systems Guest Editors: Avison, David , Kock, Ned , and Malaurent, Julien

Volume 34 Number 2 2017

Special Section: Technological Innovations for Communication and Collaboration in Social Spaces Guest Editors: Clemons, Eric K , Dewan, Rajiv M , Kauffman, Robert J , and Weber, Thomas A

Volume 34 Number 1 2017

Volume 33 number 4 2016.

Special Issue: Designing Tools to Answer Great Information Systems Research Questions Guest Editors: Giboney, Justin Scott , Briggs, Robert O , and Nunamaker, Jay F

Volume 33 Number 3 2016

Volume 33 number 2 2016.

Special Section: When Machine Meets Society: Social Impacts of Information and Information Economics Guest Editors: Clemons, Eric K , Dewan, Rajiv M , Kauffman, Robert J , and Weber, Thomas A

Special Issue: Information Systems for Deception Detection Guest Editors: Nunamaker, Jay F , Burgoon, Judee K , and Giboney, Justin Scott

Volume 33 Number 1 2016

Volume 32 number 4 2015, volume 32 number 3 2015.

Special Issue: On the Contributions of Applied Science/Engineering Research to Information Systems Guest Editors: Briggs, Robert O , Nunamaker, Jay F , and Giboney, Justin S

Volume 32 Number 2 2015

Special Section: Online Social Connections: Efficiency Versus Regulation Guest Editors: Clemons, Eric K , Dewan, Rajiv M , Kauffman, Robert J , and Weber, Thomas A

Volume 32 Number 1 2015

Spring volume 31 number 4 2015.

Special Section: Cognitive Perspectives on Information Systems Guest Editors: Briggs, Robert O

Winter Volume 31 Number 3 2014

Special Section: IT-Enabled Social and Economic Transitions Guest Editors: Clemons, Eric K , Kauffman, Robert J , and Weber, Thomas A

Fall Volume 31 Number 2 2014

Special Issue: Economics of Electronic Commerce Guest Editors: Bapna, Ravi , Barua, Anitesh , and Whinston, Andrew B

Summer Volume 31 Number 1 2014

Special Section: IT Project Management Guest Editors: Jiang, James J and Klein, Gary

Special Section: Information Systems Support for Shared Understanding Guest Editors: Briggs, Robert O

Spring Volume 30 Number 4 2014

Special Issue: Neuroscience in Information Systems Research Guest Editors: Liang, Ting-Peng and vom Brocke, Jan

Winter Volume 30 Number 3 2013

Special Issue: Information Technology and Organizational Governance: The IT Governance Cube Guest Editors: Tiwana, Amrit , Konsynski, Benn , and Venkatraman, N

Fall Volume 30 Number 2 2013

Special Issue: Information Economics and Competitive Strategy Guest Editors: Clemons, Eric K , Goh, Kim Huat , Kauffman, Robert J , and Weber, Thomas A

Summer Volume 30 Number 1 2013

Spring volume 29 number 4 2013.

Special Issue: Multiple Dimensions of Value in Information Systems Guest Editors: Briggs, Robert O and Nunamaker Jr, Jay F

Winter Volume 29 Number 3 2012

Fall volume 29 number 2 2012.

Special Section: Information and Competitive Strategy in a Networked Economy Guest Editors: Kauffman, Robert J , Weber, Thomas A , and Wu, D J

Summer Volume 29 Number 1 2012

Spring volume 28 number 4 2012.

Special Section: Creating Value with Information Guest Editors: Briggs, Robert O and Nunamaker Jr, Jay F

Winter Volume 28 Number 3 2011

Fall volume 28 number 2 2011.

Special Section: Information and Technology: Understanding New Strategies for Firms, Networks, and Markets Guest Editors: Clemons, Eric K , Kauffman, Robert J , and Weber, Thomas A

Summer Volume 28 Number 1 2011

Special Section: Applied Science Research in Information Systems: The Last Research Mile Guest Editors: Briggs, Robert O , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Spring Volume 27 Number 4 2011

Winter volume 27 number 3 2010, fall volume 27 number 2 2010, summer volume 27 number 1 2010.

Special Section: Social Aspects of Sociotechnical Systems Guest Editors: Briggs, Robert O , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Spring Volume 26 Number 4 2010

Special Issue: Information Systems in Services Guest Editors: Bardhan, Indranil R , Demirkan, Haluk , Kannan, P K , and Kauffman, Robert J

Winter Volume 26 Number 3 2009

Fall volume 26 number 2 2009, summer volume 26 number 1 2009.

Special Section: Structure and Complexity in Sociotechnical Systems Guest Editors: Nunamaker Jr, Jay F , Sprague Jr, Ralph H , and Briggs, Robert O

Spring Volume 25 Number 4 2009

Winter volume 25 number 3 2008, fall volume 25 number 2 2008.

Special Issue: Impact of Information Systems on Market Structure and Function: Developing and Testing Theories Guest Editors: Clemons, Eric K , Kauffman, Robert J , and Dewan, Rajiv M

Summer Volume 25 Number 1 2008

Special Section: Online Coordination and Interaction Guest Editors: Briggs, Robert O , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Spring Volume 24 Number 4 2008

Special Issue: Trust in Online Environments Guest Editors: Benbasat, Izak , Gefen, David , and Pavlou, Paul A

Winter Volume 24 Number 3 2007

Fall volume 24 number 2 2007.

Special Section: Applying Information Economics to Corporate Strategy Guest Editors: Clemons, Eric K , Dewan, Rajiv M , and Kauffman, Robert J

Summer Volume 24 Number 1 2007

Spring volume 23 number 4 2007.

Special Section: Global Perspectives on Information, Communication, and E-Commerce Guest Editors: Briggs, Robert O , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Winter Volume 23 Number 3 2006

Special Section: Customer-Centric Information Systems Guest Editors: Ting-Peng, Liang and Tanniru, Mohan R

Fall Volume 23 Number 2 2006

Special Section: Digital Economy and Information Technology Value Guest Editors: Clemons, Eric K , Dewan, Rajiv M , and Kauffman, Robert J

Summer Volume 23 Number 1 2006

Spring volume 22 number 4 2006.

Special Issue: Crossing Boundaries in Information Systems Research Guest Editors: Briggs, Robert O , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Winter Volume 22 Number 3 2005

Special Section: Human-Computer Interaction Research in Management Information Systems Guest Editors: Ping, Zhang , Fui-Hoon Nah, Fiona , and Benbasat, Izak

Fall Volume 22 Number 2 2005

Special Section: Information Systems in Competitive Strategies Guest Editors: Kauffman, Robert J , Clemons, Eric K , and Dewan, Rajiv M

Summer Volume 22 Number 1 2005

Spring volume 21 number 4 2005.

Special Section: Context-Driven Information Access and Deployment Guest Editors: Briggs, Robert O , De Vreede, Gert-Jan , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Winter Volume 21 Number 3 2004

Fall volume 21 number 2 2004.

Special Issue: Competitive Strategy, Economics, and Information Systems Guest Editors: Clemons, Eric K , Dewan, Rajiv M , and Kauffman, Robert J

Summer Volume 21 Number 1 2004

Special Section: Measuring Business Value of Information Technology in E-Business Environments Guest Editors: Mahmood, M Adam , Kohli, Rajiv , and Devaraj, Sarv

Spring Volume 20 Number 4 2004

Special Issue: Information Systems Design--Theory and Methodology Guest Editors: Briggs, Robert O , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Winter Volume 20 Number 3 2003

Special Section: Assuring Information Quality Guest Editors: Ballou, Donald , Madnick, Stuart E , and Wang, Richard

Fall Volume 20 Number 2 2003

Special Section: Information Systems, Electronic Commerce, and Economics: The Interdisciplinary Research Frontier Guest Editors: Kauffman, Robert J and Bin, Wang

Summer Volume 20 Number 1 2003

Spring volume 19 number 4 2003.

Special Issue: Information Systems Success Guest Editors: Briggs, Robert O , De Vreede, Gert-Jan , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Winter Volume 19 Number 3 2002

Special Section: Competitive Strategy, Economics, and the Internet Guest Editors: Chircu, Alina M and Kauffman, Robert J

Fall Volume 19 Number 2 2002

Summer volume 19 number 1 2002.

Special Section: Enterprise Resource Planning Guest Editors: Ragowsky, Arik and Somers, Toni M

Spring Volume 18 Number 4 2002

Special Issue: Decision-Making and a Hierarchy of Understanding Guest Editors: Briggs, Robert O , De Vreede, Gert-Jan , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Winter Volume 18 Number 3 2001

Fall volume 18 number 2 2001.

Special Section: Economics, Electronic Commerce and Competitive Strategy Guest Editors: Clemons, Eric K , Dewan, Rajiv M , and Kauffman, Robert J

Summer Volume 18 Number 1 2001

Special Issue: Knowledge Management Guest Editors: Davenport, Thomas H and Grover, Varun

Spring Volume 17 Number 4 2001

Winter volume 17 number 3 2000.

Special Issue: Enhancing Organizations' Intellectual Bandwidth: The Quest for Fast and Effective Value Creation Guest Editors: Nunamaker Jr, Jay F , Briggs, Robert O , De Vreede, Gert-Jan , and Sprague Jr, Ralph H

Fall Volume 17 Number 2 2000

Special Issue: Technology Strategy for Electronic Marketplaces Guest Editors: Clemons, Eric K and Yu-Ming, Wang

Summer Volume 17 Number 1 2000

Spring volume 16 number 4 2000.

Special Issue: Impacts of Information Technology Investment on Organizational Performance Guest Editors: Mahmood, M Adam and Mann, Gary J

Winter Volume 16 Number 3 1999

Special Section: Exploring the Outlands of the MIS Discipline Guest Editors: Briggs, Robert O , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Fall Volume 16 Number 2 1999

Special Section: Strategic and Competitven Information Systems - Fall 1999 Guest Editors: Clemons, Eric K and Weber, Bruce W

Summer Volume 16 Number 1 1999

Special Section: Data Mining Guest Editors: Chung, H Michael and Gray, Paul

Spring Volume 15 Number 4 1999

Winter volume 15 number 3 1998, fall volume 15 number 2 1998, summer volume 15 number 1 1998, spring volume 14 number 4 1998, winter volume 14 number 3 1997.

Special Issue: 1001 Unanswered Research Questions in GSS Guest Editors: Briggs, Robert O , Nunamaker Jr, Jay F , and Sprague Jr, Ralph H

Fall Volume 14 Number 2 1997

Summer volume 14 number 1 1997.

Special Section: The Impacts of Business Process Change on Organizational Performance Guest Editors: Chatfield, Akemi Takeoka and Bjorn-Andersen, Niels

Spring Volume 13 Number 4 1997

Winter volume 13 number 3 1996.

Special Issue: Information Technology and Its Organizational Impact Guest Editors: Nunamaker Jr, Jay F and Briggs, Robert O

Fall Volume 13 Number 2 1996

Special Section: Strategic and Competitive Information Systems Guest Editors: Clemons, Eric K and Weber, Bruce W

Summer Volume 13 Number 1 1996

Spring volume 12 number 4 1996, winter volume 12 number 3 1995.

Special Issue: Information Technology and IT Organizational Impact Guest Editors: Nunamaker Jr, Jay F and Sprague Jr, Ralph H

Fall Volume 12 Number 2 1995

Special Section: Strategic and Competitive Information Systems Guest Editors: Clemons, Eric K and Row, Michael C

Summer Volume 12 Number 1 1995

Special Section: Toward a Theory of Business Process Change Management Guest Editors: Kettinger, William J and Grover, Varun

Spring Volume 11 Number 4 1995

Special Section: Navigation in Information-Intensive Environments Guest Editors: Isakowitz, Tomas and Bieber, Michael

Winter Volume 11 Number 3 1994

Special Section: Information Technology and IT Organizational Impact Guest Editors: Nunamaker Jr, Jay F and Sprague Jr, Ralph H

Fall Volume 11 Number 2 1994

Summer volume 11 number 1 1994, spring volume 10 number 4 1994.

Special Section: Information Technology and Organization Design Guest Editors: Baroudi, Jack J and Lucas Jr, Henry C

Winter Volume 10 Number 3 1993

Special Issue: Organizational Impact of Group Support Systems, Expert Systems, and Executive Information Systems Guest Editors: Nunamaker Jr, Jay F and Sprague Jr, Ralph H

Fall Volume 10 Number 2 1993

Summer volume 10 number 1 1993.

Special Section: Realizing Value from Information Technology Investment Guest Editors: Kauffman, Robert J and Mukhopadhyay, Tridas

Spring Volume 9 Number 4 1993

Special Section: Computer Personnel Research Guest Editors: Lederer, Albert L

Special Section: Research in Integrating Learning Capabilities into Information Systems Guest Editors: Ting-Peng, Liang

Winter Volume 9 Number 3 1992

Special Issue: Collaboration Technology, Modeling, and End-User Computing for the 1990s Guest Editors: Nunamaker Jr, Jay F and Sprague Jr, Ralph H

Fall Volume 9 Number 2 1992

Summer volume 9 number 1 1992, spring volume 8 number 4 1992, winter volume 8 number 3 1991.

Special Issue: Decision Support Systems for Teams, Groups, and Organizations Guest Editors: Nunamaker Jr, Jay F

Fall Volume 8 Number 2 1991

Summer volume 8 number 1 1991, spring volume 7 number 4 1991, winter volume 7 number 3 1990.

Special Issue: Management Support Systems Guest Editors: Nunamaker Jr, Jay F

Fall Volume 7 Number 2 1990

Special Section: Competitive and Strategic Value of Information Technology Guest Editors: Clemons, Eric K

Summer Volume 7 Number 1 1990

Spring volume 6 number 4 1990, winter volume 6 number 3 1989, fall volume 6 number 2 1989, summer volume 6 number 1 1989, spring volume 5 number 4 1989, winter volume 5 number 3 1988, fall volume 5 number 2 1988, summer volume 5 number 1 1988, spring volume 4 number 4 1988, winter volume 4 number 3 1987, fall volume 4 number 2 1987, summer volume 4 number 1 1987, spring volume 3 number 4 1987, winter volume 3 number 3 1986, fall volume 3 number 2 1986, summer volume 3 number 1 1986, spring volume 2 number 4 1986, winter volume 2 number 3 1985, fall volume 2 number 2 1985, summer volume 2 number 1 1985, spring volume 1 number 4 1985, winter volume 1 number 3 1984.

Special Issue: Information System Design and Development Guest Editors: Weldon, Jay-Louise

Fall Volume 1 Number 2 1984

Summer volume 1 number 1 1984.

Send comments regarding this page to David Eargle .

A Review of the Effectiveness of Management Information System in Decision Making

Ieee account.

Change Username/Password
Update Address

Purchase Details

Payment Options
Order History
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical Interests
US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support
About IEEE Xplore
Accessibility
Terms of Use
Nondiscrimination Policy
Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2024 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

1. INTRODUCTION

2. evolution of smis, 3. research hotspots of smis, 4. typical applications of smis, 5. development directions of smis, 6. conclusion, acknowledgments, author contribution statement, smart management information systems (smis): concept, evolution, research hotspots and applications.

Changyong Liang is a Professor of Information Management at the School of Management, Hefei University of Technology, China. He obtained his Ph.D. degree from the Harbin Institute of Technology, China. His research interests lie in the areas of information management and management science, elderly care, etc. His research has been published in journals such as Information & Management, Applied Soft Computing, International Journal of Project Management , and Computers & Industrial Engineering .

Xiaoxiao Wang is a Ph.D. student majoring in Management Science at the School of Management, Hefei University of Technology, China. She obtained her master's degree from Harbin University of Science and Technology and focused on the research topic of management science. Her research interests include information management, supply chain management, and game theory.

Dongxiao Gu is a Professor of Information Management at the School of Management, Hefei University of Technology, China. He obtained his Ph.D. degree from the Hefei University of Technology, China. His research interests lie in the areas of data science and big data technology, digital health, artificial intelligence management and application, etc. His research has been published in journals such as Information & Management, Information Processing & Management, Journal of Medical Internet Research, Artificial Intelligence in Medicine , and International Journal of Production Research .

Pengyu Li graduated from Changchun University of Technology with a B.S. degree in management in 2019. He is a master student at Hefei University of Technology. His current research fields are machine learning, deep learning.

Hui Chen is a master's student at the School of Management, Hefei University of Technology. His current research areas include machine learning, smart elderly care, and bibliometrics.

Zhengfei Xu graduated from Shandong University of Finance and Economics with the B.S. degree in engineering management in 2020. He is a master student at Hefei University of Technology. His current research fields are deep learning, survival analysis and healthcare.

Cite Icon Cite
Open the PDF for in another window
Permissions
Article contents
Figures & tables
Supplementary Data
Peer Review
Search Site

Changyong Liang , Xiaoxiao Wang , Dongxiao Gu , Pengyu Li , Hui Chen , Zhengfei Xu; Smart Management Information Systems (Smis): Concept, Evolution, Research Hotspots and Applications. Data Intelligence 2023; 5 (4): 857–884. doi: https://doi.org/10.1162/dint_a_00231

Download citation file:

Ris (Zotero)
Reference Manager

Management information system (MIS), a human-computer system that deeply integrates next-generation information technology and management services, has become the nerve center of society and organizations. With the development of next-generation information technology, MIS has gradually entered the smart period. However, research on smart management information systems (SMIS) is still limited, lacking systematic summarization of its conceptual definition, evolution, research hotspots, and typical applications. Therefore, this paper defines the conceptual characteristics of SMIS, provides an overview of the evolution of SMIS, examines research focus areas using bibliometric methods, and elaborates on typical application practices of SMIS in fields such as health care, elderly care, manufacturing, and transportation. Furthermore, we discuss the future development directions of SMIS in four key areas: smart interaction, smart decisionmaking, efficient resource allocation, and flexible system architecture. These discussions provide guidance and a foundation for the theoretical development and practical application of SMIS.

In 1967, Professor Gordon B. Davis of the University of Minnesota established the discipline of Management Information Systems (hereafter referred to as MIS). In 1985, he and Professor Margrethe H. Olsen defined MIS as an integrated human-computer system that provides information to support organizations’ operations, management, and decision-making [ 1 ]. During the era of economic development dominated by the information industry, the widespread adoption of next-generation information technology has accelerated the growth of the digital economy and brought significant changes to both the organization and society. Consequently, organizations operate in complex and uncertain environments. As a fundamental tool for modern organizational operations, MIS deeply integrates next-generation information technology and management services. Driven by social needs, economic development, and next-generation information technology, MIS has entered a new development period. To cope with the complex and evolving external environment and meet the dynamic needs of users, MIS has gradually shifted towards smart solutions that support organizations in adapting to external changes, integrating internal and external resources, and providing users with personalized solutions.

In this paper, we define MIS in the smart period as Smart Management Information Systems (hereafter referred to as SMIS). SMIS is a human-computer integration system that can dynamically perceive environmental information, deeply analyze the potential needs of users, and provide personalized and scenario-based management services. Based on network communication technology and next-generation information technology, the system continuously acquires massive amounts of heterogeneous data from multiple sources through ongoing interactions with users and the environment. It dynamically identifies users’ behavioral characteristics and personalized needs, extracting knowledge from the accumulated data. Through learning processes, the system strengthens its self-monitoring, self-diagnosis, self-correction, and self-organization capabilities. It autonomously identifies the operational status of the organization, responds to and adapts to the dynamic external environment, and facilitates real-time sharing and coordination of internal resources. Additionally, the system can independently or collaboratively assist the organization in complex activities such as prediction, control, and decision-making, enhancing management services and fostering user value creation within a distributed human-machine collaborative symbiosis system. The system exhibits high agility, flexibility, openness, adaptability, self-organization, non-linearity, emergence, and robust interactivity.

Currently, research on SMIS primarily focuses on integrating next-generation information technology with the management domain. Some studies explore the smart features of MIS and investigate technological approaches to enhance its smart functions [ 2 – 4 ]. Furthermore, Jussupow et al. [ 5 ] and Cheng et al. [ 6 ] examine how SMIS improves management processes and decisions across various domains, such as business, healthcare, and public administration. Moreover, some researchers focus on the enhancement of the smart functions of organizational production and service systems by emerging technologies such as big data and the Internet of Things (IoT), which are used to solve the problems of dynamic perception, smart decision-making, and system agility [ 7 – 9 ]. These researches establish a vital theoretical foundation for the development of SMIS, fostering its smart, integration, and personalization. However, the current research on SMIS is still in the initial stage, lacking a comprehensive overview of the evolution and typical applications of SMIS. Moreover, the research hotspots and future development directions of SMIS are not yet clear.

The remainder of the paper is organized as follows: Section 2 summarizes the evolution of SMIS and analyzes the characteristics of each period. Section 3 utilizes bibliometric methods to summarize and analyze the research hotspots of SMIS in recent years. Section 4 presents notable industry examples to illustrate the application prospects of SMIS. The future research directions for SMIS are summarized in Section 5. Finally, this paper is concluded in Section 6.

MIS has undergone significant development since its origins in scientific computing and transaction processing in the 1970s [ 10 ]. With the widespread application of information technology, MIS has become an indispensable tool in people's work and life, playing a significant role as a nerve center in society and organizations. Under the interaction of computer-related technologies and the development need of enterprises, MIS progresses from the initial period of simple applications to the current period of deep integration. MIS transitions from centralized application systems that perform independent and basic tasks to intelligent and comprehensive service providers, gradually entering the smart period with the advent of next-generation information technology. Figure 1 illustrates the evolution of SMIS.

The evolution of SMIS.

2.1 Start-up Period: 1950s~1970s

The start-up period of MIS can be traced back to the 1950s to the 1970s. In 1954, IBM released the first computer capable of floating-point calculations, which prompted many companies to automate employee payroll calculations and process simple data in batches [ 11 ]. During this period, MIS was based on highlevel programming languages and document management technologies to process departmental data within organizations. This led to the achievement of electronic data processing and the emergence of information systems that could handle repetitive transactions in administration. These systems allow for the management of centralized documents, significantly enhancing the efficiency and accuracy of transaction processing. Furthermore, as the data required for calculations could also be utilized to generate reports for managers, computer-based management information systems become an unintended consequence of the automation of computing operations.

2.2 Development Period: 1970s~1990s

During the 1970s to 1990s, MIS experienced significant development driven by database technology, data communication, and computer networks. This period marks the expansion of MIS from single applications designed for specific positions to interdepartmental applications within enterprises. In 1971, Gorry and Scott-Morton [ 12 ] proposed an MIS framework (refer to Figure 2 ) to identify the types of information required for management at all levels. In this period, MIS forms a distributed, component-based, and service-oriented system technology architecture, and provides managers with integrated services for operations and supervision, decision support services, and other related systems, facilitating the transformation from operational control to management control. As a result, the comprehensiveness, systematicity, and timeliness of management information processing improved. Moreover, MIS that emerged during this period include Material Requirements Planning (MRP), Decision Support Systems (DSS), and Customer Relationship Management (CRM).

The framework of MIS proposed by Gorry and Scott-Morton.

2.3 Popularization Period: 1990s~2010s

At the end of the 20th century, the development of technologies such as the Internet and cloud computing led to the emergence of new applications like e-commerce and social media. This development expands the application scope of MIS beyond the boundaries of enterprises, propelling MIS into a period of globalization and popularization. During this period, the decision support systems evolved to encompass support for group decision-making and embedded artificial intelligence technologies. MIS transitions towards intelligent information systems with enhanced capabilities for knowledge innovation and solving unstructured affairs. These systems achieve integrated information management, a multidimensional service model, and intelligent computer-aided management with human-computer coordination. Gradually, MIS acquires the characteristics of intelligence and self-organization, and provides organizations with integrated services for strategic management and other collaborative system integration [ 13 ]. Figure 3 illustrates an open architecture of cloud-based MIS [ 14 ].

An open architecture of cloud-based MIS.

2.4 Integration Period: 2010s~present

In 2008, IBM proposed the concept of the “Smart Planet,” advocating for the development of wisdom across all industries to enhance the overall knowledge of human society globally [ 15 ]. As a crucial tool for the functioning of contemporary society, the explosive growth of data, the complexity of the external environment, and the diverse and personalized user needs necessitate the evolution of MIS towards the smart period. The next-generation information technology, including mobile Internet, big data, artificial intelligence, and IoT, has enabled advanced smart sensing, interaction, control, collaboration, and decisionmaking. This technological development significantly enhances organizations’ abilities to acquire, process, and apply data resources, providing the technical foundation for the smart development of MIS. SMIS, which is developed on the basis of the intelligent management information system combined with next-generation information technology, can continuously interact with the environment and users and obtain real-time environmental status information and dynamic user needs. It adapts to environmental changes and facilitates cross-domain, cross-organizational, and cross-departmental multi-channel resource sharing and collaborative allocation based on user needs, and makes independent or assisted managerial decisions, which significantly improves organizational management efficiency and decision-making agility. Hence, we propose a distributed SMIS architecture based on the cloud-edge-terminal, as shown in Figure 4 .

The architecture of SMIS.

With the continuous development and application of SMIS, a series of studies on SMIS have been conducted in the academic community. In this paper, we employ bibliometric analysis to analyze the relevant literature on SMIS in recent years. Moreover, we utilize Citespace software to visualize the results and provide valuable insights into the current trends and directions of SMIS research.

3.1 Data Source

This paper is based on the Web of Science repository, specifically the Web of Science Core Collection. The citation indexes selected for this study are the Science Citation Index Expanded and the Social Sciences Citation Index. The publication date range for the literature search is set from January 1, 2010, to May 1, 2023. The following search formula was used: (TS= (“Management Information System*”) OR (TS= (“Information System*”) AND TS=(“Smart”)) OR (TS= (“Information System*”) AND TS=(“Intelligent”)) OR (TS= (“Information System*”) AND TS= (“Big Data”)) OR (TS= (“Information System*”) AND TS= (“Internet of Things”)) OR (TS= (“Information System*”) AND TS= (“Cloud Computing”)) AND DT=(Article) AND LA=(English). We manually exclude the literature records with non-relevant and duplicate topics, and finally collect 4261 relevant literature records.

3.2 Research Hotspots

In this paper, we extract keywords from related literature and use Citespace 6.1 R6 software to reveal the research hotspots of SMIS. The following parameter settings are used in Citespace: Years Per Slice = 1, Node Types = Keyword. Moreover, we choose the critical pathfinder algorithm to simplify the network and highlight key nodes, and merge similar words such as Internet of Things (IoT) and Geographic Information Systems (GIS). Table 1 presents the compilation of the top 20 keywords based on their co-occurrence frequency in related literature. Additionally, Figure 5 illustrates the co-occurrence network of keywords in related literature from 2010 to 2023. These visual representations provide a clear understanding of the research trends and interrelationships among keywords in SMIS.

The keyword co-occurrence mapping of SMIS.

Frequency Ranking Statistics of Top 20 Keywords for the research of SMIS.

Table 1 reveals that the keywords with a high frequency are big data, IoT, information systems, and cloud computing. These keywords are interconnected and belong to next-generation information technology. Big data, IoT, and cloud computing are significant research drivers in SMIS. Information systems serve as the main research focus in the field. This aligns with the objective of this paper, which aims to explore the development of SMIS in the context of next-generation information technology. Furthermore, another category of keywords with high co-occurrence frequency includes machine learning, artificial intelligence, data mining, and deep learning. These keywords represent the technical and methodological aspects of research in SMIS. Figure 5 illustrates that most keywords are interconnected, indicating that published papers in SMIS often cover multiple topics. Combining with Table 1 , we can find that the research content of most of these papers is related to SMIS, mainly using different techniques and methods or applied in different research areas. Additionally, keywords with high co-occurrence frequency, such as geographic information systems, intelligent transportation systems, health information systems, Industry 4.0, and driver information systems, represent the application research fields of SMIS.

In addition, we employ a literature review approach to synthesize the literature related to SMIS over the last three years (2021-2023). The results are shown in Table 2 .

The focus of research related to SMIS from 2021 to 2023.

From Table 2 , we can find that research on SMIS in the last three years has predominantly utilized next-generation information technology, such as big data, IoT, blockchain, and cloud computing. The application areas of SMIS have been explored in various fields, including smart city, smart healthcare, smart manufacturing, smart transportation, and smart information systems. Drawing on the results obtained from the bibliometric analysis, we elaborate on the research hotspots for SMIS in the domains of smart medical management, smart manufacturing management, and smart transportation management.

The first research hotspot is smart healthcare and elderly care management. Researchers have developed IoT-based enterprise health information systems [ 33 ]. Research in medical informatics focuses on data mining and machine learning in the technical dimension, and elderly care in the health service dimension [ 34 ]. In the context of smart healthcare, Gu et al. [ 35 ] proposed a healthcare reasoning knowledge generation method with an evaluation mechanism that facilitates the generation of knowledge-based solutions for new decision problems. This method describes a healthcare decision case as a set of (x, y) vectors, where x = (x 1 , x 2 , …, x n ) represents a vector of feature attributes, y ∈ Y, and Y represents a discrete variable corresponding to a class. The class values (conclusion or scenario class knowledge) of historical cases in the case knowledge base are known. Given a new problem, the problem can be transformed into an unsolved target case with unknown class values. The variable-weighted heterogeneous value difference distance algorithm enables the generation of inferential knowledge to provide decision-makers with knowledge references.

Specifically, WHVDM ( t , r ) = ( ∑ i = 1 n w i d i 2 ( t , r ) ) 1 / 2 , where

where vdm i (t, r) is the value difference matrix (VDM), its value is calculated according to Equation (2) :

where y represents the conclusion class variable, and Y represents the domain of variable y. The term diff 2 (x t,i ,x r,i ) corresponds to a component of the traditional Euclidean distance and represents the squared distance between the target case t and the historical case r on continuous attributes, as shown in Equation (3) :

This algorithm is applied to distance measures in cases involving discrete and continuous variables, thereby emphasizing the relative importance of case attributes. Moreover, in a study on content analysis and health support using artificial intelligence algorithms for online health communities, Gu et al. [ 36 ] develop an intelligent method for identifying psychological cognitive changes based on natural language processing (NLP) techniques. This method aids in determining whether patients have experienced any psychological cognitive changes. Figure 6 illustrates the architecture of the model.

A model based on NLP for identifying mental cognitive changes.

In terms of smart healthcare information systems for elderly groups, the concept of a smart elderly service supply chain has been proposed in academia [ 37 , 38 ]. With the development of technologies such as the IoT, cloud computing, and big data, a smart elderly service system has been established [ 39 ]. This system aims to provide daily services and health support for the elderly. However, before providing services to the elderly, it is crucial to uncover their implicit service needs from their actual behavioral data. To gather behavioral data from the elderly, various sensing devices are utilized. One widely used sensing device for real-time healthcare applications in daily life is the Wireless Body Sensor Network (WBSN) [ 40 , 41 ]. Hussain et al. [ 42 ] propose a human sensor network that detects abnormal vital physiological parameters. The decision-making process is carried out by the sensor nodes. Events (E) are defined based on threshold values for these parameters. For instance, a healthcare system (S) can be defined with three parameters, E 1, E 2 , and E 3 , as follows:

If the parameter values are interdependent, and we denote the thresholds for E 1, E 2 , and E 3 as E 1th , E 2th , and E 3th , respectively, we can define the data collection function as

This event-driven data collection approach minimizes the utilization of communication resources and significantly reduces overhead. Furthermore, Su and Chiang [ 43 ] introduce the development and general architecture of the Intelligent Aging-in-place Home Care Web Services Platform (IAServ). This platform operates in a cloud computing environment and offers personalized healthcare services to support a cost-effective and highly satisfying approach to elderly care. The architecture of IAServ is depicted in Figure 7 .

The architecture of IAServ.

The second research hotspot is smart manufacturing management. Predictive manufacturing systems [ 44 ], event-driven manufacturing information systems [ 45 ], and data-driven intelligent manufacturing systems have gained prominence [ 46 ]. Additionally, researchers introduce a novel manufacturing paradigm known as cloud manufacturing. This paradigm combines emerging technologies such as cloud computing, IoT, service-oriented technologies, and high-performance computing [ 47 ]. Figure 8 depicts the architecture of a cloud manufacturing service system based on cloud computing and IoT technologies [ 48 ].

A cloud manufacturing service system architecture.

Cloud computing, a robust system with extensive computational capabilities, can store and aggregate relevant resources. It can be dynamically configured to provide personalized services to users [ 49 ]. The technical foundation of cloud computing lies in loose coupling, where the infrastructure is logically or physically separated through technologies like virtualization. Cloud computing operates on a client-server model, where the client or cloud user is loosely connected to the server or cloud provider with minimal data or control dependencies. However, data dependencies are crucial in high-performance computing and can be formalized in the following format [ 50 ]:

Users are categorized into user sets Uset 1, Uset 2 , …, Uset m (m ≥ 1), while providers are categorized into provider sets Pset 1, Pset 2 , …, Pset n (n ≥ 1). The user set Uset i , and provider set Pset j are loosely coupled, represented as Set(Uset i , Pset j ). The three attributes are defined as follows:

Independent user set:

Independent provider set:

Independent loosely coupled (cloud subscriber connected to cloud provider) set:

IoT plays a critical role in bridging the physical environment of manufacturing with the computing platforms and decision algorithms in cyberspace. Edge computing, a complement to cloud computing, focuses on big data analysis in IoT. It effectively addresses issues such as high latency and performance bottlenecks in cloud computing by offloading computation and storage tasks from remote cloud servers to local edge servers [ 51 ]. The selection algorithm for edge computing servers can be outlined as follows [ 52 ]:

where T trans represents the time taken to send task χ to the edge server (ES), T que represents the time spent in the queue, T process represents the processing time, and T re represents the time taken to receive the task.

The third research hotspot is smart transportation management. Researchers make significant advancements by developing intelligent transportation systems that leverage IoT and big data approaches to address challenges such as parking and route planning [ 53 , 54 ]. These systems transform the existing transportation infrastructure into smart transportation systems with Vehicle-to-Everything (V2X) [ 55 ]. V2X enables vehicles to connect with various entities. In this context, V stands for the vehicle, and X encompasses objects that interact with the vehicle to exchange information. The current X primarily includes vehicles, pedestrians, roadside infrastructure, and networks. The information exchange modes of V2X interactions include Vehicle-to-Vehicle (V2V) communication between vehicles; Vehicle-to-Infrastructure (V2I) communication between vehicles and roadside infrastructure; Vehicle-to-Pedestrian (V2P) communication between vehicles and pedestrians; Vehicle-to-Network (V2N) communication between vehicles and the network. Figure 9 illustrates the concept of a smart transportation system [ 56 ].

The conceptual diagram of a smart transportation system.

V2V enables vehicle-to-vehicle communication and data sharing through the device-to-device (D2D) protocol in Cellular-Vehicle-to-Everything (C-V2X), leveraging cellular networks. This communication facilitates effective path planning and helps reduce fuel consumption. Xiao et al. [ 57 ] propose an optimization algorithm to address energy efficiency issues related to multiplexing cellular user resources in D2D-based C-V2X. The algorithm aims to optimize the following problem:

where SINR k represents the signal-to-noise ratio for the k cellular user (C-UE) at the base station (BS), SINR m represents the signal-to-noise ratio for the k C-UE user at the BS, and 2 M p m 0 + η ρ k , m p m d − E m represents the power loss of the m pair of vehicular users (V-UE). Equation (10a) and (10b) impose constraints on the SINR for V-UE and C-UE users, respectively, while Equation (10c) restricts the maximum power for V-UE users. The variable p total represents the maximum transmit power allowed for the m pair of V-UE users.

According to the analysis of the core technologies employed in popular research fields of SMIS, we can find that an increasing number of technologies and methods have been introduced to facilitate the continuous development of SMIS. Moreover, the application areas of SMIS have expanded significantly, resulting in the emergence of various SMIS, such as smart healthcare information systems, smart elderly information systems, smart manufacturing management systems, and smart transportation management systems. These systems exhibit human-like features, including self-organization, self-adaptation, and self-evolution, enabling them to provide users with smart analysis, management, and decision-making services across diverse scenarios.

Based on the analysis of research hotspots in the academic community and the review of the current application of SMIS, we focus on four prominent practical applications: smart healthcare management system, smart elderly care management system, smart manufacturing management system, and smart transportation management system.

4.1 Smart Healthcare Management System

Smart healthcare has experienced rapid development since IBM introduced the concept in 2009. Healthcare information systems play a crucial role in hospital management and patient care, serving as integrated systems that support the comprehensive information needs of various stakeholders, including hospitals, patients, clinical services, ancillary services, and financial management [ 58 ]. The smart healthcare information system, integrating technologies like 5G, blockchain, IoT, and artificial intelligence, addresses the limitations of decentralized traditional healthcare systems, fragmented medical information, and resource disparities. It offers various scenario-based applications and personalized services, including one-stop consultation, electronic health record management, telemedicine, and intelligent prediction and analysis. These services facilitate enhanced interconnectivity, real-time information sharing, and business collaboration among patients, healthcare professionals, healthcare institutions, and healthcare devices.

Harman, a wholly-owned subsidiary of Samsung Electronics Co., Ltd., unveiled the Harman Intelligent Healthcare Platform, a new comprehensive digital health platform designed to help healthcare and life sciences enterprises in their journey towards personalized customer-centric services. Harman Intelligent Healthcare Platform leverages artificial intelligence and machine learning modules to improve customer experience and engagement through predictive analytics and actionable insights on data harnessed from disparate sources. The key modules of the Harman Intelligent Healthcare Platform are depicted in Figure 10 [ 59 ].

The key modules of the Harman Intelligent Healthcare Platform.

4.2 Smart Elderly Care Management System

The concept of smart elderly care was formally introduced by the Life Trust of the United Kingdom in 2012. It means that people can build an IoT system and information platform for family, community, and institutional elderly care through various modern scientific and technological means, such as the Internet and cloud computing [ 60 ]. Smart elderly care, guided by the needs of the elderly and facilitated by the smart elderly care platform, utilizes intelligent products to connect both the supply and demand sides [ 61 , 62 ]. It brings together the elderly, community, medical personnel, medical institutions, government, and service organizations to provide convenient, efficient, IoT-enabled, connected, and smart elderly care services.

Hengfeng Information is an exceptional information technology service provider specializing in smart city solutions in China. Leveraging technologies such as the Internet, mobile Internet, IoT, and cloud computing, the company has developed an innovative “Internet + community home care services” platform. This platform has successfully established a comprehensive home care model. This model combines a “care center + service site + call center + shopping mall for the elderly + alliance merchants” approach [ 63 ]. The platform of Internet + community home care services developed by Hengfeng Information is shown in Figure 11 .

The platform of Internet + community home care services.

4.3 Smart Manufacturing Management System

With the introduction of Germany's Industry 4.0, enterprises have embraced the establishment of industrial Internet enterprise-level manufacturing platforms to facilitate their operations’ digital, networked, and intelligent transformation. This transformation is supported by intelligent manufacturing management information systems, ultimately enabling the realization of green and intelligent manufacturing practices. Smart manufacturing, further advancement of intelligent manufacturing, signifies the integrated application of next-generation information technology in the manufacturing industry. Through the utilization of technologies such as the IoT, active perception, and scene intelligence, smart manufacturing explores user needs, enables large-scale personalized customization, facilitates accurate supply chain management, and implements whole lifecycle management, thereby promoting a more intelligent approach to manufacturing management.

Haier, a prominent Chinese home appliance industry player, has established an integrated, digital, and intelligent service platform known as the Cloud of Smart Manufacture Operation Platform (COSMOPlat) [ 64 ]. COSMOPlat serves as a catalyst for the comprehensive upgrade of Chinese manufacturing by accelerating its transition towards a more advanced and efficient model. The architecture of COSMOPlat is depicted in Figure 12 .

The architecture of COSMOPlat.

4.4 Smart Transportation Management System

Smart transportation originated from the smart earth proposed by IBM in 2008 and the smart city proposed in 2010. It is developed by integrating intelligent transportation systems with emerging technologies such as the IoT, cloud computing, and the mobile Internet. The smart transportation system addresses the need for real-time traffic monitoring, public vehicle management, travel information services, and vehicle-assisted control. It enables collaborative interactions among humans, vehicles, and roads, significantly enhancing transportation efficiency, improving the transportation environment, and playing a crucial role in optimizing traffic operations and providing intelligent public travel services.

Baidu, a leading autonomous high-tech enterprise in China, has developed the “Baidu ACE (Autonomous Driving, Connected Road, Efficient Mobility)” vehicle-road mobility engine. This innovative solution utilizes artificial intelligence, big data, autonomous driving technologies, vehicle-road collaboration, high-precision maps, and other information technologies to advance road infrastructure and promote smart infrastructure, smart transportation equipment, and convenient travel services [ 65 ]. The architecture of the Baidu ACE traffic engine is depicted in Figure 13 .

The architecture of the Baidu ACE.

Based on the aforementioned practical application cases, SMIS has yielded significant accomplishments in smart healthcare, smart elderly care, smart manufacturing, and smart transportation. Moreover, applications are growing in areas such as smart communities [ 66 ] and smart tourism [ 67 ]. These successful application practices demonstrate the substantial potential for the development and wide-ranging application prospects of SMIS.

SMIS actively senses and adapts to changes in the external environment using multiple sensors, engaging in real-time interactions with users to collect multimodal data. It extracts knowledge and user preferences from vast data, providing customized smart solutions tailored to their specific requirements. To facilitate smart decision-making services, SMIS optimizes and allocates processes and resources across domains, organizations, and departments. This requires the development of an open and flexible architecture capable of integrating diverse systems on a larger scale. In light of these considerations, this paper identifies four key areas for the future development directions of SMIS: smart interaction, smart decision-making, efficient resource allocation, and flexible system architecture. These aspects are interconnected and supported by a flexible architecture, as illustrated in Figure 14 .

The research framework for the development directions of SMIS.

5.1 Dynamic Perception and Human-Computer Interaction Mechanisms in Complex and Open Environments

In the era of economic globalization, organizations face a rapidly changing market environment, requiring real-time interaction with the environment to gather information on its current state. Similarly, organizations need to engage with users directly to understand their needs and incorporate them into SMIS operations to enable effective human-machine collaboration. To achieve dynamic perception, SMIS should consider various sources such as user feedback, environmental conditions, and targeted data in order to gain comprehensive insights into stakeholder interactions in multimodal scenarios. This exploration of data characteristics and understanding of state change patterns enable the development of dynamic perception mechanisms for multiple scenarios.

Advancements in information technology have enabled the virtual synergy of human behavior and the fusion of nature and human society, ushering in a new era of data [ 68 ]. Consequently, when interacting with users and the environment, SMIS needs to acquire and analyze massive amounts of heterogeneous big data from various sources within and outside the system. This involves identifying implicit user needs, adapting to changes in the external environment, promptly responding to user needs, and providing comprehensive service support. Such actions facilitate the synergistic symbiosis of the human-machine.

For instance, in smart healthcare, SMIS can integrate and analyze big data features and knowledge requirements within complex medical scenarios such as diagnosis, treatment, prediction, warning, and rehabilitation. By employing knowledge semantic dynamic modeling methods based on heterogeneous health big data from multiple sources and interpretable machine learning, along with large-scale user collaborative modeling methods for cross-organizational multi-level task requirements, SMIS can achieve highly reliable and interpretable collaborative knowledge reasoning. This approach supports decisionmaking efficiency and service quality by leveraging healthcare expert experiences and incorporating patient feedback interventions.

5.2 Smart Collaborative Decision-Making and Personalized Knowledge Service Model for Users’ Implicit Needs

SMIS leverages emerging technologies such as big data, artificial intelligence, and deep learning to enable smart decision-making and scenario-based services. It provides smart decision-making support to users by employing multi-agent learning mechanisms in complex and dynamic environments. Current advancements in this area include multi-agent reinforcement learning based on populations [ 69 ], information systems supporting organizational creativity [ 70 ], and medical-assisted decision support systems [ 71 ]. Future research can explore smart group modeling and adaptive decision models to enhance the capabilities of SMIS.

Addressing users’ implicit needs, SMIS should develop personalized knowledge service models to recommend knowledge service solutions using digital twin technology. This approach enhances the system's knowledge service capabilities and improves user satisfaction. For instance, during major public health emergencies, cross-organizational health data resources from hospitals, public health institutions, and communities can be utilized. A collaborative knowledge inference method based on a multi-case base can generate medical knowledge maps rapidly and dynamically construct cross-organizational case bases. This enables disease risk identification and collaborative decision-making among multiple medical and defense bodies by leveraging joint data and knowledge. Moreover, it facilitates the integration, smart analysis, and active service of medical and health data, and public health monitoring data. This technical support is valuable for dynamic disease monitoring and intelligent collaborative decision-making in the context of medical and defense collaboration.

Additionally, in medical prevention and coordination, the personalized knowledge needs of various stakeholders, such as disease control personnel, doctors, and patients at different levels, can be analyzed in dynamic medical prevention and coordination task scenarios. Furthermore, mechanisms for matching the needs with service resources can be explored. This can involve the development of knowledge recommendation methods based on machine reasoning and natural language understanding, as well as multi-grain knowledge matching and retrieval methods. The goal is to provide personalized, dynamic, and smart knowledge services to individuals involved in disease prevention and control.

5.3 Cross-Organizational Scenario-Based Approach to System Process Optimization and Resource Allocation

SMIS plays a crucial role in providing smart decision-making and scenario-based services. To achieve smart decision-making goals and deliver scenario-based services effectively, SMIS needs to optimize process modeling and allocate resources efficiently. This requires the establishment of a flexible system process model and the exploration of methods for customizing and reusing personalized process modules. Furthermore, there is a need to address the demand for flexible and personalized modeling of cross-organizational business processes.

Regarding resource allocation, it is essential to study cross-domain, cross-organizational, and cross-departmental resource scheduling models and methods that incorporate smart and intelligence. This research can significantly enhance the efficiency and effectiveness of resource allocation. Given the diverse characteristics of resources in the human-computer system, such as varying sizes, distributions, and dynamics, applying self-organization theory can provide insights into the multi-level resource interaction mechanism across the value chain. Moreover, it can facilitate the development of dynamic self-organization methods for resources to pursue multiple objectives and tasks.

By analyzing resource management scenarios and resource optimization goals in complex and dynamic environments, it becomes possible to explore self-adaptive mechanisms for resource allocation, scheduling, and organization. Additionally, research on resource scheduling methods, based on deep reinforcement learning, can address the dynamic needs of multiple subjects and various grain sizes. This not only enables effective interaction and collaboration among multiple subjects within the system process model but also caters to users’ personalized and dynamic needs at different levels.

5.4 Open and Flexible Management Information System Architecture and Governance System

To ensure rapid processing and response to internal and external needs, the architecture of MIS needs to evolve from a traditional centralized structure to a distributed and flexible one. This involves building the system as a distributed and adaptive scheduling multi-subject architecture with reconfigurable real-time tasks. Flexible access system architectures capable of supporting diverse requirements and facilitating agile service creation have already been developed [ 72 ]. Additionally, middleware platforms based on OpenStack have been employed to facilitate and orchestrate the offloading process [ 73 ].

Regarding system architecture, SMIS can adopt an object-oriented approach to plan system functions and achieve flexibility within management information systems. This can be accomplished through the personalized configuration of functional modules and the utilization of multi-agent configuration methods. Hence, SMIS can effectively monitor and manage system functions, processes, and operational status, while also enhancing the system to adapt to environmental changes and individual user needs. Furthermore, the open and flexible architecture of SMIS places greater emphasis on the system's governance. In terms of SMIS governance, blockchain technology can be explored to establish mechanisms for data quality control, system security protection, and user privacy protection. These mechanisms ensure the continuous and stable operation of the system.

As an important tool for assisting organizations in management and decision-making, SMIS plays a crucial role in society and organizations. This paper begins by presenting the evolution of SMIS based on previous research and defines the different periods of SMIS, highlighting how management information systems have evolved into the smart period. Next, by analyzing literature related to SMIS over the past decade, the paper summarizes the research hotspots in SMIS and identifies the healthcare, elderly care, manufacturing, and transportation fields as prominent areas where SMIS is widely and maturely applied. Furthermore, the paper examines typical application cases of SMIS, showcasing the significant development potential of SMIS. Lastly, the paper outlines the future development directions of SMIS, focusing on four key aspects: smart human-computer interaction, smart decision-making services, efficient resource allocation, and flexible system architecture.

SMIS is capable of addressing complex and ambiguous user needs in real-time, providing users with smart analysis, management, and decision-making services. In future research, it is important to explore diverse human-machine partnerships to enhance the human-like capabilities of SMIS. By leveraging these partnerships, SMIS can deliver more smart and personalized services tailored to the unique requirements of different positions and users in various roles. Additionally, there should be a focus on cross-platform integration of SMIS to enable seamless resource integration and collaboration across domains, organizations, and departments. This cross-platform integration will facilitate the efficient utilization of resources and promote cooperation among different entities. To further advance SMIS, it is crucial to conduct in-depth case studies and experimental research. These studies will provide valuable insights into the practical implementation and impact of SMIS in real-world scenarios.

This work was supported by the National Natural Science Foundation of China (grant number: 72131006, 72071063, 72271082); Anhui Provincial Key R&D Programme (grant number: 2020i01020003).

Changyong Liang (Email: [email protected] ): has proposed the research problems and designed the research framework. Xiaoxiao Wang (Email: [email protected] ): has designed the research framework and wrote and revised the manuscript. Dongxiao Gu (Email: [email protected] ): has designed the research framework and revised the manuscript. Pengyu Li (Email: [email protected] ): has wrote and revised the manuscript. Hui Chen (Email: [email protected] ): has collected and analyzed the data. Zhengfei Xu (Email: [email protected] ): has wrote and revised the manuscript.

Email alerts

Affiliations.

Online ISSN 2641-435X

A product of The MIT Press

Mit press direct.

About MIT Press Direct

Information

Accessibility
For Authors
For Customers
For Librarians
Direct to Open
Open Access
Media Inquiries
Rights and Permissions
For Advertisers
About the MIT Press
The MIT Press Reader
MIT Press Blog
Seasonal Catalogs
MIT Press Home
Give to the MIT Press
Direct Service Desk
Terms of Use
Privacy Statement
Crossref Member
COUNTER Member
The MIT Press colophon is registered in the U.S. Patent and Trademark Office

This Feature Is Available To Subscribers Only

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

We're Hiring!
Help Center

REVIEW OF MANAGEMENT INFORMATION SYSTEMS RESEARCH: A MANAGEMENT SUPPORT EMPHASIS

Related Papers

Journal of Information Engineering and Applications

PIUS VINCENT OKOYE

Saiful Islam

Alexander Decker

Dinasti International Journal of Education Management And Social Science

Ali M Zebua

Management Information System (MIS) is one of the most important achievements in the field of work administration, which aims to provide reliable, accurate, relevant and complete information to managers to improve organizational performance in organizations. This research reviews other research in the field of MIS adoption in organizations. Synthesizing from the previous literature with several books, articles and related studies, this paper proposes a theoretical framework. Previous research or relevant research is very important in a research or scientific article. Previous research or relevant research serves to strengthen the theory and phenomena of the relationship or influence between variables. This article reviews the factors that influence Information Systems in the academic field, namely: Software, Databases and Information Technology, a literature study on Information Systems Management. The purpose of writing this article is to build a hypothesis of the influence between...

Information Systems Journal

Tor Magnus T M L Larsen

Renée Pratt , Christopher Furner

The purpose of this paper is to classify the most cited papers in Management Information Systems (MIS) by theoretical perspective and subject area. The determination of the underlying theoretical perspective of these papers facilitates and verifies the dominance of positivist perspectives. Our analysis indicates that 74% of the most cited articles are positivist and 26% are interpretivist. The presence of a significant percentage of interpretive work suggests that differing theoretical perspectives are being considered relevant to solving the problems identified in the current research streams. Our results also indicated User Satisfaction and Instrument Development and Group Support Systems as the most cited articles subject areas, 16% and 14% respectively. The significance of these subject areas promotes and supports that systems is the foundation of MIS.

Relatively speaking, the field of information systems is still young, developing into a coherent field. This introduction to the minitrack is organized into the following four sections. The first section discusses three prerequisite conditions for MIS to become a coherent field of a study, as suggested by Keen (1980). 1.1 Clarifying reference disciplines 1.2 Building a cumulative research tradition 1.3 Defining the dependent variables The second section is concerned with the process by which an academic discipline becomes establishment. Once the prerequisite conditions for becoming a classic field of study have been met, a review of the major works of Kuhn (1970), Kaplan (1964), and Cushing (1990) describes the process by which an academic discipline becomes establishment in terms of the following steps: 2.1 Consensus building 2.2 Empirical studies 2.3 Articulation of Theories 2.4 Paradigm Building The third section overviews the current state of MIS research in terms of the prerequ...

JUSTIN GABRIEL

Abstract : Information has become an essential resource for managing modern organizations. This is so because today’s business environment is volatile, dynamic, turbulent and necessitates the burgeoning demand for accurate, relevant, complete, timely and economical i nformation needed to drive the decision - making process in order to accentuate organizational abilities to manage opportunities and threats . This paper is a reflection of amassed discourse available in literature concerning the nexus between management inf ormation systems – MIS and corporate decision - making. The paper suggests that a painstaking development and management of MIS in organizations is capable of triggering decisions that would not only be fast and accurate but would be in line with industry best practices and ultimately result in organizational efficiency and effectiveness.

Mahmoud Moussa, PhD

Employers at all levels, in all settings, are continually in search of information to develop decisions that can be supportive when facing complex, and unpredictable scenarios in the global market. Hence, information and information systems have become strategic tools in the hands of decision makers in today " s businesses. This paper is a presentation of the contemporary reality of information systems, and their influence in enhancing organizational performance. Further, the author identifies the types and levels of information systems available, and their fundamental purposes and roles, alongside the challenges and risks involved. Ultimately, practical implications for business leaders, and recommendations for further studies are provided.

Management information systems for community based interventions to improve health: qualitative study of stakeholder perspectives

Linda Penn ORCID: orcid.org/0000-0003-1272-5239 1 , 2 ,
Louis Goffe 1 , 2 ,
Anna Haste 1 , 2 &
Suzanne Moffatt 1 , 2

BMC Public Health volume 19 , Article number: 105 ( 2019 ) Cite this article

9020 Accesses

4 Citations

4 Altmetric

Metrics details

Community based providers are well place to deliver behavioural interventions to improve health. Good project management and reliable outcome data are needed to efficiently deliver and evaluate such interventions, and Management information systems (MIS) can facilitate these processes. We explored stakeholders perspectives on the use of MIS in community based behavioural interventions.

Stakeholders, purposively selected to provide a range of MIS experience in the delivery of community based behavioural interventions to improve health (public health commissioners, intervention service managers, project officers, health researchers and MIS designers), were invited to participate in individual semi-structured interviews. We used a topic guide and encouraged stakeholders to reflect on their experiences.: Interviews were recorded, transcribed and analysed using five steps of Framework analysis. We applied an agreed coding framework and completed the interviews when no new themes emerged.

We interviewed 15 stakeholders. Key themes identified were: (i) MIS access; (ii) data and its function; (iii) MIS development and updating. Within these themes the different experiences, needs, use, training and expertise of stakeholders and the variation and potential of MIS were evidenced. Interviews advised the need to involve stakeholders in MIS design and development, build-in flexibility to accommodate MIS refinement and build on effective MIS.

Conclusions

Findings advised involving stakeholders, early in the design process. Designs should build on existing MIS of proven utility and ensure flexibility in the design, to incorporate adaptations and ongoing system development in response to early MIS use and evolving stakeholder needs.

Peer Review reports

The National Health Service (NHS) Five Year Forward View [ 1 ] emphasised the importance of disease prevention and outlined how behavioural interventions can support people to make healthy behaviour choices to improve their health and prevent disease [ 2 ]. It is recognised that good project management with reliable outcome data are needed to provide information for policy makers [ 2 ] and modern information technology, including access to web-based hosting, can facilitate good administration and robust data collection through well-designed MIS Voluntary and community sector organisations are well place to deliver behavioural health interventions, but [ 2 ] good MIS may be difficult to achieve where intervention providers are working on a small scale or to a tight budget.

The design and implementation of health information systems goes beyond the technical aspects [ 3 ] of the system and can incur, “unforeseen costs, unfulfilled promises, and disillusionment (Anderson & Aydin 2005, page vii)” [ 4 ]. In one conceptual model the technical aspects, design and implementation consequences of a management information system (MIS) are assumed to be within the control of a single organisation, with MIS design responsive to the information needs of that organisation and its management [ 4 ]. However, situations regularly occur where MIS are required to function across different organisations and stakeholder groups [ 5 ], thus design and implementation should ideally be responsive to multiple management and information needs [ 6 ]. For example intervention providers may use MIS for administration, public health commissioners may access MIS data to monitor and commission interventions and researchers may use these data to evaluate intervention effectiveness.

Different evaluation methodologies can be used to examine MIS design and implementation including surveys, observational methods and qualitative interviews [ 3 ]. In this study we used qualitative research and individual interviews to investigate the perspectives of stakeholders, who had a range of relevant roles and experience, on the design and use of MIS in delivery and evaluation of behavioural interventions to improve health. We aimed to explore stakeholders perspectives on the use of MIS in delivery and evaluation of community based behavioural interventions and examine their views on how to optimise the design, provision and utility of MIS where these are required to function across different organisations.

Data collection and analysis

To identify stakeholders and recruit study participants we initially focussed on two empirical research studies: ‘Ways to Wellness,’ a social prescribing intervention targeting people in socio-economically deprived communities with long-term health conditions [ 7 , 8 ] and ‘New life, New you’ a small scale intervention for the prevention of type 2 diabetes in adults at high risk, which included a cultural adaptation of the intervention that was specifically designed to engage local black and ethnic minority communities [ 9 , 10 ].

‘Ways to Wellness’ social prescribing intervention

Ways to Wellness social prescribing intervention is available to people aged 40 to 74 years, with one or more long-term health condition (diabetes, heart disease, lung disease, osteoporosis, asthma, epilepsy) living in an urban area of high socio-economic deprivation. Patients are referred to the service by their doctor and allocated to a link worker, trained in behavioural techniques, who supports their clients to improve their health behaviours, self-care, condition management and social integration. ‘Ways to Wellness’ takes account of the wider determinants of health and aims to improve clients health related outcomes.

‘New life, New you’ intervention for prevention of type 2 diabetes

‘New life, New you’ behavioural intervention is available to people at high risk of type 2 diabetes, living in an urban area of high socio-economic deprivation. Clients are recruited from the community and there is a specific focus on recruitment of people of Black and UK minority ethnic populations. ‘New life, New you’ is delivered by fitness trainers as group supervised physical activity sessions, with space for reflection, behavioural techniques and nutritional advice. ‘New life, New you’ aims to prevent or delay the onset of type 2 diabetes.

From these studies we identified different stakeholder roles in the provision and evaluation of interventions to improve health as: public health commissioners, voluntary and community sector service managers, project officers (administration and intervention delivery staff), independent researchers and MIS designers. We used purposive sampling to provide a spread of experience across these roles and invited stakeholders to participate in individual semi-structured interviews. Initially we focussed recruitment on the two empirical studies outlined although all study participants had relevant MIS experience beyond these specific studies. To ensure balance across the different stakeholder groups we also accessed other research contacts from within the Institute of Health and Society at Newcastle University. Interviews were conducted face to face or by telephone using a topic guide that covered views on MIS use generally and detailed consideration of MIS use in one or more specific behavioural interventions. All interviews were digitally audio recorded and transcribed for analysis. We used the five steps of Framework analysis: (1. Familiarization, 2. Identifying a thematic framework, 3. Indexing, 4. Charting and 5. Mapping / interpretation), to analyse transcripts and identify anticipated and emergent themes [ 11 , 12 ]. Researchers LP, LG and AH each coded two different interview transcripts and then met to discuss and agree a coding framework. We used constant comparison to ensure the robustness of the coding framework which was then applied to these six transcripts [ 13 ] NVivo 11 software was used to facilitate data management and a further two transcripts were independently coded by LP and AH to further check and validate the framework. We completed the interviews when no new themes emerged from the analysis (data saturation was reached) and the final coding framework was applied to all transcripts.

Researchers LP, LG and AH conducted a total of 15 interviews, ( n = 6 face to face and n = 9 by telephone), between August 2016 and November 2017. Interviews lasted between 20 min and 59 min, with a mean duration of 41 min. Participant roles and demographics are summarised in Table 1 .

From our thematic analysis of interview data we identified three key themes as: (i) access to MIS; (ii) data and its function; (iii) development and updating of MIS. These themes and sub-themes are summarised in Table 2 and then described in detail, with brief supporting quotations below. More detailed quotations are also provided in Additional file 1 .

Access to MIS

The key theme of access to MIS encompassed different stakeholder access requirements and included the sub-themes: collecting and inputting data, setting and time of access, reasons for access by different stakeholders, perspectives of MIS value and usability, and support and training in the use of MIS. Each of these sub-themes are detailed, with supporting quotes, below.

Collecting and inputting data

Participants spoke about data collection as a predominantly paper based exercise. This was seen as a pragmatic, but not an ideal strategy and there was support for more digitally facilitated data collection.

“If you worked out how much it cost for an iPad versus having someone's time cost to sit and enter things twice it probably saves money.” (researcher 8)

Direct input to an electronic system, and a workable strategy for this, was also described.

“They’ve got laptops, [and] when they’re back at base they can sync it all back up.” (commissioner 14)

There was concern over the impact of onerous data collection on service user experience, for both paper based and electronic data collection methods.

“The service user is either going to disengage with the service completely or we are only going to get partial data”. (service manager 15)

Often those inputting the data were different from those who had collected the data and this could lead to delay and frustration as described below.

“It [data] will come in in dribs and drabs.” (service manager 3)

In a different situation the ultimate adverse consequences of a paper based data collection strategy were explained.

“I think it [data]’s sitting on pieces of paper in a draw somewhere.” (researcher 8)

In contrast an automated system where intervention participants entered some of their data directly to an online hosting facility was described.

“You can just give it [tablet] to the patient, they type the stuff in themselves.” (database designer 12)

Setting and time when the MIS was accessed

We asked about when and where stakeholders accessed the MIS and found that this was related to their reason for access. Where MIS access was to enter data, this was usually described as an office based procedure.

However, for data review and analysis, web-hosting facilitated access from other settings, including working from home.

The benefit of new technology, was also described in terms of facilitating multiple simultaneous use. For example an old system might only allow one person to access at any one time whereas a new system could allow multiple access.

“It’s [MIS] been set up for .. [name] study, where multiple people can be in it [MIS] at once.” (researcher 9)

Access to the MIS, reason for stakeholder access

Stakeholders described their different MIS access needs, knowledge and permissions. Reasons for accessing the MIS were for data input, administration of the intervention programme and for monitoring and evaluation.

Some MIS were set up to alert administrators to non-attendance of intervention clients, which might be linked to applications, such as mail-merge or text messaging to send participant reminders.

“We want to track as patients drop off the programme.” (service manager 1)

“If somebody hasn't attended, we send out a non-attendee letter notifying them.” (commissioner 5)

In contrast, those responsible for external evaluation might not need access to client contact details and MIS access was set up accordingly as explained in the different levels of access permissions and how these had to be justified.

“The people pulling it [data] off at the other end, it [data] was completely anonymous.” (service manager 3)

In one scenario client access to their own data, as a self-regulatory part of the intervention, was described.

“They [clients] are each provided with a key with a programme on and what it does, it records what they've done. They can compare week by week whether they've improved” (commissioner 5)

Support and training in use of the MIS

Training consisted of both formal and more informal procedures, and the need for training to be an ongoing process was evident. A training pathway, from formal introduction to self-supportive user groups, was described by some participants.

“We had half a day [training] at the very beginning with everyone who was new … .. then it was about week three or four where we came together for another half a day [training] [Now staff] convene their own user groups … they’re training one another” (service manager 1)

The collaboration and supportive role of MIS users was a frequent theme.

Some people, especially if they were not involved in all aspect of MIS use, spoke about wanting to understand it better and particularly how an appreciation of different data functions might help stakeholders to appreciate the importance of the data to different end-users.

It would be good if there was someone like the evaluation team coming in to do something … around, “This is why it's important. This is what a validated measure means.” (project officer 4)

Others, especially if they had responsibilities for data extraction and analyses spoke about the need for training to support data quality.

“You can't remove the human factor. I think the staff need continual training. It's hard because some of them have been using this system [MIS] for years, even though it's a new service [intervention] they think they know it all.” (researcher 8)

Usability and value of MIS

Designers of MIS spoke about making the system easy for people to use and the need to accommodate different levels of expertise and confidence in MIS use and the ways in which interface design could make systems better for end-users.

“You’re going to have people there who are good with computers and people who are like, "I don’t want to touch it. If you can make it [screen] look like what they see in front of them on paper, it’s just better.” (database designer 12)

However, the value of MIS might not be properly appreciated.

“The expectation within a project that that it [MIS} is a valued part – an absolutely integral part – of what is being developed, alongside, obviously, the high priority around the actual service that’s being delivered. From my experience, it’s [MIS] never really had a high enough priority.” (service manager 15)

Data and its function

This key theme included: confidence in the data (quality, security and accuracy), data processing (cleaning, extraction, analyses and linkage), and use of data (administration, monitoring, evaluation).

Confidence in the data, including data quality, security and accuracy

The need for data to be accurate and secure was a frequent theme. Respondents spoke about accuracy in terms of data input, the need to make sure all those inputting data were using the MIS in the same way to ensure consistency , and ways in which MIS design could facilitate accuracy in data input. The safeguards to prevent data input error were clearly important for managing quality, for example drop down boxes could improve consistency by limiting field choice. However, mandatory fields (which meant that there was no distinction between a ‘not answered’ and ‘no’ response) were an issue. The quality of self-report data was questioned, with particular reference to a situation where participants reported their own weight over the phone, after a weight loss intervention, and the weight loss was greater than expected.

“I was thinking, "Well that will explain why the BMI looks so great at follow up.” (project officer 7)

Data security was a major issue, especially where systems included NHS patient data

Details of a security procedure was explained as:

“ ‘Two-factor authentication’, so two levels of encryption, and two passwords to get in.” ( project officer 2)

Different levels of access contributed to the data security.

“We've got reviewer access, which means we can see everything but it's all anonymised.” (researcher 8)

Also, the need for data ‘back –up’ was seen as important.

“Having a backup as well … making sure you've got the databases backed up.” (project officer 7)

Data processing, including data cleaning, extraction, analysis and linkage

Ensuring data was ‘cleaned’ and ready for analysis was raised as essentially a planning issue.

“It can be that the amount of work taken to look over some data, clean it and get it in a nice, presentable fashion, is a lot more than anticipated at the design stages of a study” (database designer 12)

The difficult of data linkage and , “ trying to get different systems to talk to each other” (commissioner 5) was mentioned. The need to complement pre-set queries with manual calculations was seen as important to identify data trends and one respondent spoke about transferring data to a ‘monitoring and evaluation database’ to follow trends. (commissioner 5)

Some of the security issues impacted on data analyses, especially with NHS data. Difficulties with individual level data, even when data were anonymised, were raised.

Use of the data, including administration, monitoring and reporting

Data was used for administration purposes, such as sending reminders when people failed to attend the intervention or when they needed to come for their follow-up appointment or review, which often involved collection of outcome data. Monitoring the progress of individual participants was seen as an important use of data, as well as monitoring the progress of the entire project, both in terms of overall participant progress and in comparison with other projects and areas.

“From the commissioner perspective, it gives them assurance that what they are commissioning is having an impact on the outcomes, the indicators and the performance measures of the services that they’re commissioning.” (commissioner 14)

Development and updating of the MIS

Which included: procurement (cost complexity and ownership), specificity (bespoke or generic) and stakeholder involvement (degree of stakeholder input).

Procurement of the MIS, including cost complexity and ownership

Procurement rules for public service MIS were mentioned.

The cost of MIS development was a strong theme and there was clearly a balance between ideal and pragmatic solutions.

“That was a very, very expensive, tailored database. Where the one we’ve got is fine.” (project officer 4)

Ownership of the MIS was raised by one manager. The intellectual property was not always clear-cut, especially when MIS development had evolved.

“I think it is our intellectual property, I think anyone who goes into this probably would want to make sure that it is their IP, if they ever need to move it [platform].” (service manage 1))

Specificity of the MIS, degree to which it is bespoke or generic

Stakeholders described MIS that were fairly simple and built on generic platforms, such as Microsoft Access and MIS that were complex and bespoke. There was some support for simple platforms.

“I think the simple platforms have their place … and probably work well particularly with the volunteering community and social enterprise sector. For them it can provide them with a basis to be able to build up that knowledge of management information system and prove what they’re doing is successful and get them in a position to be able to bid for more work.” (commissioner 14)

Whereas the problems of a new, complex system were to some extent considered inevitable.

“There are lots of very legitimate, kind of, bugs you need to work out with a new system” (service manager 1)

However, participants identified a clear link between size and complexity of service and MIS needed.

The opportunities to co-ordinate services through the use of complex and co-ordinated MIS were described.

“They [managers] took the ambitious view that what we needed was one [MIS} for [the lead provider organisation] and to be able to layer it so each delivery organisation had the right system, information storage and reports that they needed.” (commissioner 10)

Stakeholder involvement in the development of the MIS

Amongst all respondents, there was consensus about the need to involve different stakeholders in MIS development from the outset.

“Bring everybody together, the people who are going to be using it every day.” (project officer 2)

Sometimes stakeholder involvement, although agreed to be desirable, was hampered by practicalities of delivery timescales.

“I would rather have sat down and done it together, … ... But because our study was very busy, everything was needed now, now, now, so we didn't have that time to be able to do it.” (researcher 9)

The need for MIS development to be multi-stage was also described along with the tendency for MIS importance to be overlooked.

“Yes, it definitely is multi-stage. If you develop a database for capture of data for a study, you don’t just build it. You have lots of drafts, and it’s expected that the whole study team could comment and make useful suggestions..” (database designer 12)

How MIS updates are managed

The difficulties of complex MIS were reflected in the many references to ‘updating’ in stakeholder interviews. The need to make the system user friendly was complicated by the need to preserve data integrity within a ‘live’ data collection environment.

“We have been trying to make it more usable for [delivery staff] but I think it will be ever-evolving, really, to adapt to their needs and to make data entry easier and more efficient for them” (project officer 2)

The need for in-built flexibility was described, with the facility for stakeholder feedback, but the approach to feedback was seen as variable.

“You need to have the functionality to continue to grow and develop.” (service manager 13)

Main findings

Stakeholders appreciated the value of well-designed MIS and evidenced the need to involve a range of stakeholders, taking into account their different information requirements, to improve MIS design and utility. Training in the use of MIS as an evaluation tool was viewed as important to maximise the accuracy and utility of data collected. The potential for inputting data at the point of patient engagement, thus making use of developments in information technology, was highlighted by stakeholders.

MIS design that builds on existing systems of proven utility, with in-built flexibility to accommodate revisions and refinement in response to early use, was regarded as most likely to provide optimal MIS for delivery and evaluation of community based behavioural interventions.

Strengths and limitations

The rapid development of information technology means that MIS opportunities are constantly evolving and some of the procedures and perspectives evidenced here, such as a reliance on paper based data collection, may be superseded by new options, including data input by intervention participants. However, the general principles of stakeholder involvement, building on effective systems and providing system flexibility are likely to be resilient to technological innovation.

Comparison with other studies and implications

In their paper on stakeholder roles and perceptions in health information systems Pouloudi et al. [ 14 ] discuss the development and implementation of information systems in the UK National Health Service. They cite a commonly used definition of a stakeholder in relation to an organisation as, ‘ A stakeholder in an organization is (by definition) any group or individual who can affect or is affected by the achievement of the organization’s objectives’ [ 15 ] However, Pouloudi et al. then go on to expand this definition, extending the scope and shifting the focus beyond a single organisation, and defining information systems stakeholders as, ‘ The individuals, groups, organizations or institutions who can affect or be affected by an information system.’ [ 14 ] This broad definition is applicable to our study, where the intra-organisational use of MIS is the research focus.

At a macro level, the World Health Organization explains the importance of, ‘Sound and reliable information’ as the ‘foundation of decision-making across all health system building blocks’. [ 16 ] (WHO report page 1). It is reasonable to assume that information collected locally is similarly important at a local level. There has long been interest in the use of design science to inform information systems [ 17 ] and a distinction has been made between natural and social sciences, which have ‘understanding reality’ as their focus, and design science, where the focus is more towards ‘solving problems and making things that are useful in human service’ [ 18 ]. In this study we used standard qualitative research techniques and, by understanding different stakeholder perspectives on their experience of MIS, we explored how to optimise the design, provision and utility of these MIS.

Unanswered questions and future research

The need to shift the health care focus more towards prevention, was identified in the NHS Five Year Forward View [ 1 ]. Community based services are well placed to support this shift in focus, but the value of such services cannot be assessed without reliable and accessible information. In particular there is a pressing need to evaluate the effectiveness and cost-effectiveness of preventive interventions to inform decisions on the allocation of resources for health improvement. Any such evaluation relies on the quality and completeness of information and data collection. In turn efficient service administration is needed to facilitate good data collection. Stakeholders interviewed in this study all valued the MIS data, collected through the interventions that they were involved with, for their different information requirements. We suggest further research on use of MIS in community based organisations is needed to inform the efficient development of secure systems with optimal utility. In particular there is a need to explore the linkage between health service (e.g. NHS) data and data collected by community based organisations.

Well-designed MIS were appreciated by a range of stakeholders, with experience of many projects, for their various information needs. Involving a range of stakeholders, at an early stage in the process, could improve MIS design and training in the use of MIS as an evaluation tool was considered important to maximise data utility.. MIS design that builds on existing systems of proven utility, with in-built flexibility to accommodate revisions and refinement in response to early use, was regarded as most likely to provide optimal MIS for delivery and evaluation of community based behavioural interventions.

Abbreviations

Management Information Systems

National Health Service in the United Kingdom

Department of Health. Health and social care act 2012. London: The stationery Office; 2012.

Google Scholar

Brownson RC, Baker EA, Deshpande AJ, Gillespie KN. Evidence-based public health. Oxford: Oxford University Press; 2018.

Eslami Andargoli A, Scheepers H, Rajendran D, Sohal A. Health information systems evaluation frameworks: a systematic review. Int J Med Inform. 2017;97:195–209.

Article Google Scholar

Anderson J, Aydin C (eds.): Evaluating the organizational impact of healthcare information systems. United States of America: Library of Congress control number: 2005923548; 2005.

Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. Safety risks associated with the lack of integration and interfacing of hospital health information technologies: a qualitative study of hospital electronic prescribing systems in England. BMJ Quality & Safety. 2017;26(7):530–41.

Sligo J, Gauld R, Roberts V, Villa L. A literature review for large-scale health information system project planning, implementation and evaluation. Int J Med Inform. 2017;97:86–97.

Moffatt S, Steer M, Penn L, Lawson S. What is the impact of ‘social prescribing’? Perspectives of adults with long-term health conditions. BMJ Open. 2017;0:e015203. https://doi.org/10.1136/bmjopen-2016-015203.

Beacon North Ltd: Newcastle Social Prescribing Project. In . www.ers.org.uk ; 2013.

Penn L, Dombrowski SU, Sniehotta FF, White M. Perspectives of UK Pakistani women on their behaviour change to prevent type 2 diabetes: qualitative study using the theory domain framework. BMJ Open. 2014;4(7):e004530.

Penn L, Ryan V, White M. Feasibility, acceptability and outcomes at a 12-month follow-up of a novel community-based intervention to prevent type 2 diabetes in adults at high risk: mixed methods pilot study. BMJ Open. 2013;3(11):e003585.

Srivastava A, Thomson SB: Framework analysis: a qualitative methodology for applied policy research. . JOAAG , 4(2) 2009.

Ritchie J, Lewis J, editors. Qualitative research practice: a guide for social science students and researchers. London: Sage Publications; 2003.

Boeije H. A purposeful approach to the constant comparative method in the analysis of qualitative interviews. Qual Quant. 2002;36(4):391–409.

Pouloudi N, Currie W, Whitley EA. Entangled stakeholder roles and perceptions in health information systems: a longitudinal study of the UK NHS N3 network. J Assoc Inf Syst. 2016;17(2):107–61.

Freeman RE. Strategic management: a stakeholder approach. Cambridge, Mass: Ballinger publishing; 1984.

World Health Organization. Toolkit on monitoring HEALTH systems strengthening; HEALTH INFORMATION SYSTEMS. In: Health metrics network framework and standards for country health information systems; 2008.

Peffers K, Tuunanen T, Rothenberger MA, Chatterjee S. A design science research methodology for information systems research. J Manag Inf Syst. 2007;24(3):45–77.

Simon H. In: Cambridge MIoT, editor. The sciences of the artificial; 1969.

Download references

Acknowledgements

We wish to thank all participants in this study for their interest and for their time spent in being interviewed. We wish to thank the management of ‘New life, New you’ intervention for prevention of type 2 diabetes and ‘Ways to Wellness’ social prescribing intervention for allowing us to approach their staff and invite their interview participation.

This study was funded by Newcastle University Institute for Ageing. The funder had no influence on the content of the manuscript. Linda Penn is a member of Fuse, the Centre for Translational Research in Public Health ( www.fuse.ac.uk ). Fuse is a UK Clinical Research Collaboration (UKCRC) Public Health Research Centre of Excellence. Funding for Fuse from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the National Institute for Health Research, under the auspices of the UKCRC, is gratefully acknowledged. The views expressed in this paper do not necessarily represent those of the funders or UKCRC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Availability of data and materials

To access data for further analysis please contact the Corresponding Author.

Author information

Authors and affiliations.

Institute of Health and Society, Newcastle University, Baddiley Clark Building, Richardson Road, Newcastle upon Tyne, NE2 4AX, UK

Linda Penn, Louis Goffe, Anna Haste & Suzanne Moffatt

Fuse, UKCRC Centre for Translational Research in Public Health, Newcastle upon Tyne, UK

You can also search for this author in PubMed Google Scholar

Contributions

LP, SM and LG designed the study and secured funding. LP, LG and AH conducted the interviews and analysed the data. All co-authors contributed to interpretation of analyses, study reports and drafts of this summary paper. All co-authors have reviewed and agreed this final draft of the paper that is submitted for publication. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Linda Penn .

Ethics declarations

Ethics approval and consent to participate.

Ethical approval for this study was provided by Newcastle University ethics committee (NO5727). All participants gave written informed consent to take part in the study.

Consent for publication

Not applicable.

Competing interests

All co-authors are employees of Newcastle University. Otherwise there are no financial relationships with any organisations that might have an interest in the submitted work in the previous three years and no other relationships or activities that could appear to have influenced the submitted work.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Additional file

Additional file 1:.

Results with detailed quotations. The appendix provides more detailed results with more extensive quotations. (DOCX 20 kb)

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Cite this article.

Penn, L., Goffe, L., Haste, A. et al. Management information systems for community based interventions to improve health: qualitative study of stakeholder perspectives. BMC Public Health 19 , 105 (2019). https://doi.org/10.1186/s12889-018-6363-z

Download citation

Received : 28 June 2018

Accepted : 21 December 2018

Published : 23 January 2019

DOI : https://doi.org/10.1186/s12889-018-6363-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Qualitative
Interview study
Behavioural intervention
Public health
Community based
Management information system
Stakeholder
Data collection
Commissioners
Administration

BMC Public Health

ISSN: 1471-2458

Submission enquiries: [email protected]
General enquiries: [email protected]

IMAGES

Information Systems Research Template
Concept paper for Educational Management Information System
[PDF] Management Information Systems Research: What's There in a
(PDF) A Research Paper on College Management System
IPhone Management Information System Research Paper Example
(PDF) REVIEW OF MANAGEMENT INFORMATION SYSTEMS RESEARCH: A MANAGEMENT

VIDEO

Lecture -43 || Management Information System || MIS || 📚📝📢
Google File System- Research Paper Presentation
Management Information System in SDLC
Management Information System (MIS)-
Management Information System (MIS)
MANAGEMENT INFORMATION SYSTEM CHAPTER 6

COMMENTS

25650 PDFs
Kerry Brian Walsh. Thakur Prasad Bhattarai. A farm management information system (MIS) entails record keeping based on a database management system, typically using a client-server architecture, i ...
A Study on Management Information Systems Role and Adoption in ...
Abstract. The Management Information System processes that flow through computer data, and integrated with other processes to provide information in a faster and more efficient way to support decision-making and other administrative tasks.
Journal of Management Information Systems
All papers are refereed in a double anonymized process by the internationally recognized expert referees and by Associate Editors who serve on the distinguished Editorial Board of JMIS. Publication office: Taylor & Francis, Inc., 530 Walnut Street, Suite 850, Philadelphia, PA 19106. Authors can choose to publish gold open access in this journal.
JMIS
Special Section: Human-Computer Interaction Research in Management Information Systems. Guest Editors: Ping, Zhang, Fui-Hoon Nah, Fiona, and Benbasat, Izak. Fall Volume 22 Number 2 2005 ... Award-Winning Papers. Subscription Information. Export References ...
Journal of Management Information Systems
The Journal of Management Information Systems is a widely recognized and top-ranked forum for the presentation of research that advances the practice and understanding of organizational information systems. It serves those investigating new modes of information delivery and the changing landscape of information policy making, as well as practitioners and executives managing the information ...
A Review of the Effectiveness of Management Information System in
This research paper presents a comprehensive review of the effectiveness of Management Information Systems in facilitating decision-making within various organizational contexts. The paper begins with an exploration of the fundamental role of MIS in collecting, processing, and presenting relevant data to decision-makers.
[PDF] Management Information Systems Research: What's There in a
A general framework for classifying and examining survey research is presented and this framework is used to analyze the usage of survey research conducted in the past decade in the MIS field and makes specific recommenoations that directly address the major problems highlighted in the review. Expand. 1,376. PDF.
Artificial Intelligence for Management Information Systems ...
The aim of this paper is to present a systematic literature review of the existing research, published between 2006 and 2023, in the field of artificial intelligence for management information systems. Of the 3946 studies that were considered by the authors, 60 primary studies were selected for analysis. The analysis shows that most research is focused on the application of AI for intelligent ...
Smart Management Information Systems (Smis): Concept, Evolution
ABSTRACT. Management information system (MIS), a human-computer system that deeply integrates next-generation information technology and management services, has become the nerve center of society and organizations. With the development of next-generation information technology, MIS has gradually entered the smart period. However, research on smart management information systems (SMIS) is ...
Review of management information systems research: A management support
1. INTRODUCTION A Management Information System (MIS) is generally thought of as an integrated, user- machine system providing information to support operations, management, and decision- making functions in an organization [1]. This article organizes, describes, and critically evaluates MIS research being pursued in schools of business.
Management Information Systems Research: A Topic Modeling Based
This study revealed the primary lines of the MIS field and ended up being a guide for researchers about the topics they can focus on in the future. ABSTRACT Management information systems (MIS) have an interdisciplinary structure. Naturally, it develops and changes with the influence of other fields. This study tries to analyze MIS through academic studies on this topic. In this context, the ...
Research in Management Information Systems: The Minnesota ...
This article. summarizes a series of experiments, The Minnesota Experiments, which were conducted to examine the significance of various information system characteristics on decision activity. Several research programs administered in the period 1970-1975 are discussed in this paper.
(Pdf) Review of Management Information Systems Research: a Management
A CRITICAL 03064573/a 1988 Pergamon $3.00 + .oo Journals Ltd. REVIEW REVIEW OF MANAGEMENT INFORMATION SYSTEMS RESEARCH: A MANAGEMENT SUPPORT EMPHASIS RANDOLPH B. COOPER Graduate School of Business Administration, The University of Michigan, Ann Arbor, MI 48109 (Received June 19, 1987) Abstract-This article organizes, describes, and evaluates ...
Management Information Systems Research: A Topic Modeling Based
Management information systems (MIS) have an interdisciplinary structure. Naturally, it develops and changes with the influence of other fields. This study tries to analyze MIS through academic studies on this topic. In this context, the analysis included 25304 articles published in the Scopus database from 2016 to 2021.
Management information systems for community based interventions to
Background Community based providers are well place to deliver behavioural interventions to improve health. Good project management and reliable outcome data are needed to efficiently deliver and evaluate such interventions, and Management information systems (MIS) can facilitate these processes. We explored stakeholders perspectives on the use of MIS in community based behavioural ...
Introduction to Management Information System
A Management Information System (MIS) is an information system that is intended to be used by the higher management of an organization. The MIS generally collects summarized data from different departments or subsystems of an organization and presents in a form that is helpful to the management for taking better decisions for the organization.
Information Systems Research
Information Systems Research is a peer-reviewed journal that seeks to publish the best research in the information ... This paper investigates the suitability of online loans as an investment through the lens of a portfolio optimization framework. ... The Institute for Operations Research and the Management Sciences. 5521 Research Park Drive ...
The Role of Management Information System: Review on the ...
The literature review shows the big importance of industries and organizations to maximize the utilization of the unit. It is recommended that all institutions should revisit and include the Management Information System unit as a priority unit for improvement for organizational effectiveness and innovation.