Pub Date : 2022-07-29DOI: 10.1080/17517575.2022.2101025
Kusum Yadav, Elham Kariri, Shoayee Alotaibi, W. Viriyasitavat, G. Dhiman, Amandeep Kaur
ABSTRACT Laws and regulations for privacy protection have been promulgated one after another, and the phenomenon of data islands has become a significant bottleneck hindering the development of big data and artificial intelligence technologies. From the perspective of the historical development, concepts, and architecture classification of federated learning, the technical advantages of federated learning are explained using Internet of Things. Simultaneously, numerous attack methods and classifications of federated learning systems are examined, as well as the distinctions between different federated learning encryption algorithms. Finally, it reviews research in the subject of federal learning privacy protection and security mechanisms, as well as identifies difficulties and opportunities.
{"title":"Privacy protection against attack scenario of federated learning using internet of things","authors":"Kusum Yadav, Elham Kariri, Shoayee Alotaibi, W. Viriyasitavat, G. Dhiman, Amandeep Kaur","doi":"10.1080/17517575.2022.2101025","DOIUrl":"https://doi.org/10.1080/17517575.2022.2101025","url":null,"abstract":"ABSTRACT Laws and regulations for privacy protection have been promulgated one after another, and the phenomenon of data islands has become a significant bottleneck hindering the development of big data and artificial intelligence technologies. From the perspective of the historical development, concepts, and architecture classification of federated learning, the technical advantages of federated learning are explained using Internet of Things. Simultaneously, numerous attack methods and classifications of federated learning systems are examined, as well as the distinctions between different federated learning encryption algorithms. Finally, it reviews research in the subject of federal learning privacy protection and security mechanisms, as well as identifies difficulties and opportunities.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48024107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-26DOI: 10.1080/17517575.2022.2098537
Khalid A. Eldrandaly, Mohamed Abdel-Basset, Mahmoud Ibrahim, Nabil M. Abdel-Aziz
ABSTRACT Explainable artificial intelligence (XAI) is an evolving discipline that mainly emphasises unboxing in these Black-Boxes. This study provides in-depth review of XAI literature together with a new taxonomy of categorising XAI methods. Moreover, the security of Deep learning (DL) against different attacks turned to be a critical concern for both industry and academia. This study presents a taxonomic overview of the attacks on DL solutions and methods for securing DL against these attacks. Experiments are performed to evaluate and analyse the cutting-edge methods for explaining and securing DL models on real-world case studies of Twitter sentimental analysis using state-of-the-art DL models.
{"title":"Explainable and secure artificial intelligence: taxonomy, cases of study, learned lessons, challenges and future directions","authors":"Khalid A. Eldrandaly, Mohamed Abdel-Basset, Mahmoud Ibrahim, Nabil M. Abdel-Aziz","doi":"10.1080/17517575.2022.2098537","DOIUrl":"https://doi.org/10.1080/17517575.2022.2098537","url":null,"abstract":"ABSTRACT Explainable artificial intelligence (XAI) is an evolving discipline that mainly emphasises unboxing in these Black-Boxes. This study provides in-depth review of XAI literature together with a new taxonomy of categorising XAI methods. Moreover, the security of Deep learning (DL) against different attacks turned to be a critical concern for both industry and academia. This study presents a taxonomic overview of the attacks on DL solutions and methods for securing DL against these attacks. Experiments are performed to evaluate and analyse the cutting-edge methods for explaining and securing DL models on real-world case studies of Twitter sentimental analysis using state-of-the-art DL models.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44763582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-15DOI: 10.1080/17517575.2022.2093617
Linying Dong, Sameh Al-Natour, U. Omeziri, Ozgur Turetken
ABSTRACT The existing literature pays little attention to the onward and upward stage, the final stage of an ES life cycle where system enhancement and integration cause permanent changes in employees’ work and profoundly impact their well-being. Drawing from the Enterprise System Experience Cycle Framework and human resource management literature, we have proposed, and examined through the survey of 109 users, the impact of user satisfaction on job satisfaction, job stress, and employee engagement. As an early effort at exploring the onward and upward stage, our research contributes to a comprehensive understanding of ES success and its impact on employee well-being.
{"title":"Does user satisfaction affect employee well-being? An exploratory investigation at the onward and upward stage of enterprise system experience cycle","authors":"Linying Dong, Sameh Al-Natour, U. Omeziri, Ozgur Turetken","doi":"10.1080/17517575.2022.2093617","DOIUrl":"https://doi.org/10.1080/17517575.2022.2093617","url":null,"abstract":"ABSTRACT The existing literature pays little attention to the onward and upward stage, the final stage of an ES life cycle where system enhancement and integration cause permanent changes in employees’ work and profoundly impact their well-being. Drawing from the Enterprise System Experience Cycle Framework and human resource management literature, we have proposed, and examined through the survey of 109 users, the impact of user satisfaction on job satisfaction, job stress, and employee engagement. As an early effort at exploring the onward and upward stage, our research contributes to a comprehensive understanding of ES success and its impact on employee well-being.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46966649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-13DOI: 10.1080/17517575.2022.2086021
Shiying Ni, Xiwen Bai, Yuchen Liang, Zhibo Pang, Lefei Li
ABSTRACT There are hypes towards blockchain-based traceability systems (BCTS) both from academia and industry. This paper discusses challenges and policy recommendations for BCTS from a viewpoint of industrial application and market competition. First, the potentials of BCTS and the gaps between the ideal and the reality of BCTS are elaborated. Second, we discuss the applicability of BCTS. Third, by a game-theoretic model, we study when supply chains should invest in BCTS. Investment is recommended when investment cost is relatively low compared to the price and market competition is less intense. A prisoner’s dilemma arises when investment cost is at a moderate level.
{"title":"Blockchain-based traceability system for supply chain: potentials, gaps, applicability and adoption game","authors":"Shiying Ni, Xiwen Bai, Yuchen Liang, Zhibo Pang, Lefei Li","doi":"10.1080/17517575.2022.2086021","DOIUrl":"https://doi.org/10.1080/17517575.2022.2086021","url":null,"abstract":"ABSTRACT There are hypes towards blockchain-based traceability systems (BCTS) both from academia and industry. This paper discusses challenges and policy recommendations for BCTS from a viewpoint of industrial application and market competition. First, the potentials of BCTS and the gaps between the ideal and the reality of BCTS are elaborated. Second, we discuss the applicability of BCTS. Third, by a game-theoretic model, we study when supply chains should invest in BCTS. Investment is recommended when investment cost is relatively low compared to the price and market competition is less intense. A prisoner’s dilemma arises when investment cost is at a moderate level.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41872446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-01DOI: 10.1080/17517575.2022.2081935
I. Szabó, Katalin Ternai, Szabina Fodor
ABSTRACT Blockchain technology creates the possibility for developing knowledge-intensive goods. Only a few studies in Affordance theory deal with investigating blockchain. This paper aims to discover affordances in blockchain when designing an AI-based financial recommendation system as a decision support system. The design thinking methodology was extended with machine learning and business process modelling to discover financial offerings, digital objects to be tokenised, advantages gained from the tracing affordances and consensus mechanism, and the role of smart contracts for each persona. The implementation of discovered blockchain-based applications requires a multichain framework to meet the requirements of design affordances.
{"title":"Affordances in blockchain-based financial recommendations concerned with life events and personalities","authors":"I. Szabó, Katalin Ternai, Szabina Fodor","doi":"10.1080/17517575.2022.2081935","DOIUrl":"https://doi.org/10.1080/17517575.2022.2081935","url":null,"abstract":"ABSTRACT Blockchain technology creates the possibility for developing knowledge-intensive goods. Only a few studies in Affordance theory deal with investigating blockchain. This paper aims to discover affordances in blockchain when designing an AI-based financial recommendation system as a decision support system. The design thinking methodology was extended with machine learning and business process modelling to discover financial offerings, digital objects to be tokenised, advantages gained from the tracing affordances and consensus mechanism, and the role of smart contracts for each persona. The implementation of discovered blockchain-based applications requires a multichain framework to meet the requirements of design affordances.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45754179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-04DOI: 10.1080/17517575.2021.1973570
Milan Zdravković, H. Panetto
The fourth industrial revolution has marked the end of the industrial automation era of simple and repetitive human tasks. Then, it opened a new arena for the efforts of mimicking human intelligence with a clear objective. This arena facilitates i) machinedriven decision-making, ii) seamless machine-to-machine communication using the formalisms easily expressed and understood by humans, iii) solving problems driven by uncertain and unknown variables, and iv) other activities that require more complex considerations and actions, in which humans typically implement in the past. With Artificial Intelligence (AI), Enterprise Information Systems (EIS) are becoming increasingly capable of sensing and perceive (even reach beyond the human cognitive horizon), analyse, or understand and respond, based on the acquired understanding. This combination was made possible using big data, significantly improved algorithms and sufficient computational power to train and run those algorithms with vast amounts of data. In this Special Issue, the concept of AI EIS enablement (Zdravković, Panetto, and Weichhart 2021) is introduced to provide the umbrella for a new way of thinking, architecting, designing, developing and using the EIS. It is placed on the top of the widely discussed data-enablement, sometimes in the context of so-called sensing enterprise. This enterprise continuously listens to its internal and external environments using the technologies, such as sensors, embedded electronics and multi-agent systems. Although today’s hype on AI is driven by the performance of complex deep learning architectures and models, both symbolic and non-symbolic AI applications were considered to reflect the equal importance of challenges and opportunities for logic-based and data-based methods. The Special Issue was advertised on the website of the publisher and by email. Also, the authors of the selected papers from the special session with the title ‘(Industrial) Internetof-Things for Smart & Sensing Systems’, organised at the 8th International Conference for Information Society and Technology (ICIST 2018) were invited to submit the extended versions of those papers to the Special Issue. Twenty submissions have been received, and after several rounds of reviews and revisions, six manuscripts were accepted for publication. Those manuscripts are shortly presented in the following section.
第四次工业革命标志着简单和重复的人工任务的工业自动化时代的结束。然后，它为具有明确目标的模仿人类智能的努力开辟了一个新的舞台。这个领域促进了i)机器驱动的决策，ii)使用人类易于表达和理解的形式进行无缝的机器对机器通信，iii)解决由不确定和未知变量驱动的问题，以及iv)其他需要更复杂的考虑和行动的活动，这些活动在过去通常由人类实施。随着人工智能(AI)的发展，企业信息系统(EIS)越来越有能力基于获得的理解来感知和感知(甚至超越人类的认知范围)、分析或理解和响应。这种组合是通过使用大数据、显著改进的算法和足够的计算能力来训练和运行大量数据的算法而成为可能的。在本期特刊中，介绍了人工智能环境信息系统实现的概念(zdravkovovic, Panetto, and Weichhart 2021)，以提供一种新的思维方式，架构，设计，开发和使用环境信息系统。它被放在广泛讨论的数据支持的顶部，有时在所谓的传感企业的背景下。该企业利用传感器、嵌入式电子和多智能体系统等技术不断地监听其内部和外部环境。尽管今天对人工智能的炒作是由复杂深度学习架构和模型的性能驱动的，但符号和非符号人工智能应用被认为反映了基于逻辑和基于数据的方法的挑战和机遇的同等重要性。特刊在出版商的网站和电子邮件上做了广告。此外，在第8届信息社会与技术国际会议(ICIST 2018)上组织的题为“智能与传感系统的(工业)互联网-物联网”的特别会议上选出的论文的作者被邀请将这些论文的扩展版本提交给特刊。已收到20份投稿，经过几轮审查和修订，6份手稿被接受出版。这些手稿将在下一节中简要介绍。
{"title":"Artificial intelligence-enabled enterprise information systems","authors":"Milan Zdravković, H. Panetto","doi":"10.1080/17517575.2021.1973570","DOIUrl":"https://doi.org/10.1080/17517575.2021.1973570","url":null,"abstract":"The fourth industrial revolution has marked the end of the industrial automation era of simple and repetitive human tasks. Then, it opened a new arena for the efforts of mimicking human intelligence with a clear objective. This arena facilitates i) machinedriven decision-making, ii) seamless machine-to-machine communication using the formalisms easily expressed and understood by humans, iii) solving problems driven by uncertain and unknown variables, and iv) other activities that require more complex considerations and actions, in which humans typically implement in the past. With Artificial Intelligence (AI), Enterprise Information Systems (EIS) are becoming increasingly capable of sensing and perceive (even reach beyond the human cognitive horizon), analyse, or understand and respond, based on the acquired understanding. This combination was made possible using big data, significantly improved algorithms and sufficient computational power to train and run those algorithms with vast amounts of data. In this Special Issue, the concept of AI EIS enablement (Zdravković, Panetto, and Weichhart 2021) is introduced to provide the umbrella for a new way of thinking, architecting, designing, developing and using the EIS. It is placed on the top of the widely discussed data-enablement, sometimes in the context of so-called sensing enterprise. This enterprise continuously listens to its internal and external environments using the technologies, such as sensors, embedded electronics and multi-agent systems. Although today’s hype on AI is driven by the performance of complex deep learning architectures and models, both symbolic and non-symbolic AI applications were considered to reflect the equal importance of challenges and opportunities for logic-based and data-based methods. The Special Issue was advertised on the website of the publisher and by email. Also, the authors of the selected papers from the special session with the title ‘(Industrial) Internetof-Things for Smart & Sensing Systems’, organised at the 8th International Conference for Information Society and Technology (ICIST 2018) were invited to submit the extended versions of those papers to the Special Issue. Twenty submissions have been received, and after several rounds of reviews and revisions, six manuscripts were accepted for publication. Those manuscripts are shortly presented in the following section.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45828220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-03DOI: 10.1080/17517575.2022.2069478
Shi Wang, X. Liu, Ming Gao, Mingxia Chen, K. Yung, Shancheng Jiang
ABSTRACT A novel multi-objective (cost, delay, and reliability) auto-scaling optimisation model is proposed for micro-service workflows in containerised hybrid clouds. We compare the container-based model with VM-based model and conclude that the former significantly supersedes. The benchmark of three mainstream algorithms is conducted by the Hypervolume metric, showed that the performance of MOEA/D is inferior to NSGA family, and NSGA-III is not always superior to NSGA-II. So we design an improved NSGA-II based on dynamically changing crossover and mutation operators, which outperforms NSGA-III both in stability and performance by over 60% and 80% in all multi-scale tests.
{"title":"Multi-objective auto-scaling scheduling for micro-service workflows in hybrid clouds","authors":"Shi Wang, X. Liu, Ming Gao, Mingxia Chen, K. Yung, Shancheng Jiang","doi":"10.1080/17517575.2022.2069478","DOIUrl":"https://doi.org/10.1080/17517575.2022.2069478","url":null,"abstract":"ABSTRACT A novel multi-objective (cost, delay, and reliability) auto-scaling optimisation model is proposed for micro-service workflows in containerised hybrid clouds. We compare the container-based model with VM-based model and conclude that the former significantly supersedes. The benchmark of three mainstream algorithms is conducted by the Hypervolume metric, showed that the performance of MOEA/D is inferior to NSGA family, and NSGA-III is not always superior to NSGA-II. So we design an improved NSGA-II based on dynamically changing crossover and mutation operators, which outperforms NSGA-III both in stability and performance by over 60% and 80% in all multi-scale tests.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45837534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-24DOI: 10.1080/17517575.2022.2062683
Heba Mohamed, S. Fathalla, Jens Lehmann, Hajira Jabeen
ABSTRACT Computing dataset statistics is crucial for exploring their structure, however, it becomes challenging for large-scale datasets. This has several key benefits, such as link target identification, vocabulary reuse, quality analysis, big data analytics, and coverage analysis. In this paper, we present the first attempt of developing a distributed approach (OWLStats) for collecting comprehensive statistics over large-scale OWL datasets. OWLStats is a distributed in-memory approach for computing 50 statistical criteria for OWL datasets utilizing Apache Spark. We have successfully integrated OWLStats into the SANSA framework. Experiments results prove that OWLStats is linearly scalable in terms of both node and data scalability.
{"title":"Efficient computation of comprehensive statistical information of large OWL datasets: a scalable approach","authors":"Heba Mohamed, S. Fathalla, Jens Lehmann, Hajira Jabeen","doi":"10.1080/17517575.2022.2062683","DOIUrl":"https://doi.org/10.1080/17517575.2022.2062683","url":null,"abstract":"ABSTRACT Computing dataset statistics is crucial for exploring their structure, however, it becomes challenging for large-scale datasets. This has several key benefits, such as link target identification, vocabulary reuse, quality analysis, big data analytics, and coverage analysis. In this paper, we present the first attempt of developing a distributed approach (OWLStats) for collecting comprehensive statistics over large-scale OWL datasets. OWLStats is a distributed in-memory approach for computing 50 statistical criteria for OWL datasets utilizing Apache Spark. We have successfully integrated OWLStats into the SANSA framework. Experiments results prove that OWLStats is linearly scalable in terms of both node and data scalability.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48045353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-17DOI: 10.1080/17517575.2022.2065457
Xiaohan Liu, Donghan Wang, Meng Gu, Jiajia Yang
ABSTRACT For the emerging marketing mode of livestream shopping, this study constructed a model to empirically analyze how anchors’ professionalism affects consumers' impulse buying intention. The results have shown that professional level of anchors is positively correlated with the impulse buying intention of consumers and a sense of presence partially plays an intermediary role in the interaction between anchors’ professionalism and consumers’ impulse buying intention. In addition, consumers’ competitive arousal has been found to have a negative moderating effect on the relationship between anchors’ professionalism and consumers’ sense of presence.
{"title":"Research on the influence mechanism of anchors’ professionalism on consumers’ impulse buying intention in the livestream shopping scenario","authors":"Xiaohan Liu, Donghan Wang, Meng Gu, Jiajia Yang","doi":"10.1080/17517575.2022.2065457","DOIUrl":"https://doi.org/10.1080/17517575.2022.2065457","url":null,"abstract":"ABSTRACT For the emerging marketing mode of livestream shopping, this study constructed a model to empirically analyze how anchors’ professionalism affects consumers' impulse buying intention. The results have shown that professional level of anchors is positively correlated with the impulse buying intention of consumers and a sense of presence partially plays an intermediary role in the interaction between anchors’ professionalism and consumers’ impulse buying intention. In addition, consumers’ competitive arousal has been found to have a negative moderating effect on the relationship between anchors’ professionalism and consumers’ sense of presence.","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48989608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-16DOI: 10.1080/17517575.2022.2052187
L. Goel, Z. Zhang, Steven A. Williamson
ABSTRACT Unintentional employee behaviours can be a major cause of security breaches. To mitigate the risk, employees need to habituate their new behaviours, implying a transfer of learning that may occur at ‘work’ to ‘personal’ contexts. Against this backdrop, we examine a new construct – IT Assimilation – grounded in situated learning theory by its definition as the incorporation of enterprise IT into an individual’s IT repertoire. We use a multi-phase methodological approach to conceptualise the construct and develop a validated scale to measure it. Our findings offer valuable insights for researchers and practitioners about transferring IT behaviours, particularly in the cybersecurity context..
{"title":"IT assimilation: construct, measurement, and implications in cybersecurity","authors":"L. Goel, Z. Zhang, Steven A. Williamson","doi":"10.1080/17517575.2022.2052187","DOIUrl":"https://doi.org/10.1080/17517575.2022.2052187","url":null,"abstract":"ABSTRACT Unintentional employee behaviours can be a major cause of security breaches. To mitigate the risk, employees need to habituate their new behaviours, implying a transfer of learning that may occur at ‘work’ to ‘personal’ contexts. Against this backdrop, we examine a new construct – IT Assimilation – grounded in situated learning theory by its definition as the incorporation of enterprise IT into an individual’s IT repertoire. We use a multi-phase methodological approach to conceptualise the construct and develop a validated scale to measure it. Our findings offer valuable insights for researchers and practitioners about transferring IT behaviours, particularly in the cybersecurity context..","PeriodicalId":11750,"journal":{"name":"Enterprise Information Systems","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47831251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：