International Journal of Information Management Data Insights最新文献

英文中文

Harnessing the potential of generative AI in digital marketing using the Behavioral Reasoning Theory approach

International Journal of Information Management Data Insights

Pub Date : 2024-12-17 DOI: 10.1016/j.jjimei.2024.100317

Sujata Joshi , Sonali Bhattacharya , Pankaj Pathak , N.A. Natraj , Juhi Saini , Soumya Goswami

Generative AI (GAI) is an upcoming field and its impact on marketing is indisputable. Very little evidence in academic literature is present regarding the factors affecting the usage of GAI in Digital Marketing (DM). This study addresses this gap by exploring the key drivers and barriers associated with using GAI in DM. Leveraging Behavioral Reasoning Theory (BRT), the research validates prior findings and introduces a conceptual model outlining factors that shape attitudes toward adopting GAI in DM to enhance customer experiences.

A qualitative inductive approach was undertaken by conducting expert interviews to investigate the “reasons for” and ‘reasons against’ using GAI in DM and its impact on customer experience. The transcripts generated were manually coded and a deductive thematic analysis was done using the BRT as the theoretical framework.

The findings indicate four significant themes for adopting GAI in digital marketing viz: innovation, creative communication and content creation, speed, efficiency and timesaving, enhanced customization and personalization; predictive analytics and simulation. It also indicates five significant themes related to the key barriers were also identified viz: ethics and infringement of Intellectual Property; security and deepfake; learning ecosystem for the adoption of new technology; quality of data; reduced manpower requirement. The study further highlights how GAI influences customer experience in DM.

This study contributes to the field by (a) proposing a conceptual framework for applying GAI in DM to improve customer experiences, (b) examining the drivers and challenges of GAI adoption in DM, and (c) presenting a research agenda to guide future studies. These insights offer value to researchers, marketing practitioners, and academics navigating the dynamic intersection of GAI and Digital Marketing

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引用次数: 0

Is software design gender biased? A study on software-design effect on task performance

International Journal of Information Management Data Insights

Pub Date : 2024-12-12 DOI: 10.1016/j.jjimei.2024.100312

Samaa Elnagar

Software design is critical to the development of software. However, existing literature highlighted the presence of gender bias in software design, which might be causing differences in task performance between males and females. Supported by theories such as the cognitive load theory, emotional design theory, and the Aesthetic-Usability Effect, this research aims to explore the potential disparities in task performance between males and females. The study developed two tasks using two different software in terms of user friendliness. The study was performed on two groups that possessed comparable educational backgrounds and professional experiences. The investigation encompassed two tasks aimed at evaluating performance in both professional and domestic contexts. Through the application of structural equation modeling and a range of statistical analyses, the study identified disparities among females, including high perception of cognitive load and lack of emotional design. The study emphasizes on the importance of incorporating phycological cognitive differences in design and ensuring inclusive design personas in software design. Addressing the cognitive and emotional aspects of software design will reduce task performance discrepancies and shift the misbelief that task performance discrepancies are attributable to gender-based intellectual differences, rather than deficiencies in software design.

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引用次数: 0

Digital marketing strategies for luxury fashion brands: A systematic literature review

International Journal of Information Management Data Insights

Pub Date : 2024-12-06 DOI: 10.1016/j.jjimei.2024.100309

Fung Yi Tam, Jane Lung

The main objective of this study is to examine how digital marketing strategies can be put into practice and integrated into the actual operation of luxury fashion brands. To do this, the study explores the implementation of digital marketing strategies that are adopted by the luxury fashion brands. It uses a systematic literature review (SLR) and the real cases of luxury fashion brands as the research methodology. After conducting the SLR, the 15 digital marketing strategies for luxury fashion brands mapping into six categories in terms of types of digital marketing media, and the level of company's control and communication are identified. As digitization has become part of our daily routines and consumers are spending more time online and using social media, this study proposes that digital marketing strategies emerge as a powerful force for luxury fashion brands to better succeed in the competitive global market.

引用次数: 0

How digital technologies and AI contribute to achieving the health-related SDGs 数字技术和人工智能如何促进实现与卫生相关的可持续发展目标

International Journal of Information Management Data Insights

Pub Date : 2024-11-29 DOI: 10.1016/j.jjimei.2024.100298

Philipp Koebe

Enhancing global health stands as a pivotal objective within the United Nations' Sustainable Development Goals (SDGs). In the wake of the ongoing digital transformation across various spheres of life, the incorporation of new digital technologies and the utilization of artificial intelligence hold the potential to contribute significantly to the attainment of these objectives. Leveraging the scalability inherent in digital business models, coupled with the widespread adoption of smartphones, facilitates the broad dissemination of digital healthcare services, even within emerging and developing nations. This inquiry adopts a quantitative research methodology to examine the implications of this phenomenon. In 2023, a cohort of 103 experts within German-speaking countries participated in an online survey, offering their insights into the impact of digitalization on health-related sustainability goals. The survey encompassed an assessment of the influence of digital technologies and AI on 13 sub-goals within the health domain, as well as on six additional SDGs. The comprehensive evaluation revealed that all 19 sub-goals exhibit a discernible medium to high impact. The analysis underscores that domains such as education and early warning systems are particularly amenable to digital interventions. Conversely, endeavors targeting the reduction of tobacco consumption or drug abuse may benefit from complementary measures. Conclusively, this study not only presents a developmental perspective on modeling but also formulates ten actionable recommendations, elucidating potential avenues for advancing the integration of digital technologies and artificial intelligence to enhance health-related sustainability goals.

加强全球卫生是联合国可持续发展目标中的一项关键目标。随着生活各个领域正在进行的数字化转型，新数字技术的结合和人工智能的利用有可能为实现这些目标做出重大贡献。利用数字商业模式固有的可扩展性，再加上智能手机的广泛采用，促进了数字医疗保健服务的广泛传播，甚至在新兴国家和发展中国家也是如此。本调查采用定量研究方法来检验这一现象的含义。2023年，来自德语国家的103名专家参加了一项在线调查，就数字化对健康相关可持续发展目标的影响提供了他们的见解。调查包括评估数字技术和人工智能对卫生领域13个分目标以及另外6个可持续发展目标的影响。综合评价显示，所有19个子目标都表现出明显的中到高影响。分析强调，教育和预警系统等领域特别适合数字化干预。相反，旨在减少烟草消费或药物滥用的努力可能受益于补充措施。最后，本研究不仅提出了建模的发展前景，还提出了十项可操作的建议，阐明了推进数字技术和人工智能集成以增强健康相关可持续性目标的潜在途径。

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引用次数: 0

Monitoring semantic relatedness and revealing fairness and biases through trend tests 通过趋势测试监测语义相关性，揭示公平性和偏见

International Journal of Information Management Data Insights

Pub Date : 2024-11-28 DOI: 10.1016/j.jjimei.2024.100305

Jean-Rémi Bourguet , Adama Sow

An emerging application domain concerning content-based recommender systems provides a better consideration of the semantics behind textual descriptions. Traditional approaches often miss relevant information due to their sole focus on syntax. However, the Semantic Web community has enriched resources with cultural and linguistic background knowledge, offering new standards for word categorization. This paper proposes a framework that combines the information extractor ReVerb with the WordNet taxonomy to monitor global semantic relatedness scores. Additionally, an experimental validation confronts human-based semantic relatedness scores with theoretical ones, employing Mann–Kendall trend tests to reveal fairness and biases. Overall, our framework introduces a novel approach to semantic relatedness monitoring by providing valuable insights into fairness and biases.

关于基于内容的推荐系统的新兴应用领域提供了对文本描述背后语义的更好考虑。传统的方法由于只关注语法而经常错过相关信息。然而，语义Web社区丰富了文化和语言背景知识资源，为词分类提供了新的标准。本文提出了一个将信息提取器ReVerb与WordNet分类法相结合的框架来监测全局语义相关性评分。此外，实验验证将基于人的语义相关性评分与理论的语义相关性评分进行比较，采用Mann-Kendall趋势检验来揭示公平性和偏见。总的来说，我们的框架通过对公平和偏见提供有价值的见解，引入了一种新的语义相关性监测方法。

引用次数: 0

Fraud detection skills of Thai Gen Z accountants: The roles of digital competency, data science literacy and diagnostic skills 泰国 Z 世代会计师的欺诈侦查技能：数字能力、数据科学素养和诊断技能的作用

International Journal of Information Management Data Insights

Pub Date : 2024-11-26 DOI: 10.1016/j.jjimei.2024.100308

Narinthon Imjai , Watcharawat Promma , Nimnual Visedsun , Berto Usman , Somnuk Aujirapongpan

The issue of accounting fraud presents a significant challenge within the business sector, prompting an increase in scholarly investigations across various contexts. Despite this growing interest, research specifically addressing the Thai context has remained scarce. Thus, this quantitative study aimed to bridge this gap by assessing the proficiency of Thai Gen Z accountants in detecting accounting fraud, with a particular emphasis on their digital, data science, and diagnostic skills. The study collected data from 150 participants using a structured survey questionnaire distributed to licensed accountants affiliated with the Thailand accounting program. It adopted a theoretical framework inspired by social learning theory and information processing theory to examine both direct and mediated relationships among the key variables under investigation. The results were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine these relationships. The results showed that digital competency have significant direct effects on the fraud detection skills, with diagnostic skills playing a key role in the process. The study revealed that digital competency not only furnishes accountants with necessary technological expertise but also bolsters their analytical skills, which are vital for identifying fraudulent activities. Likewise, data science literacy—encompassing skills in predictive analytics, big data management, and data insight communication—significantly enhances accountants' capacity to identify and understand fraudulent patterns. The emergent role of diagnostic skills as a key intermediary emphasizes the importance of comprehensive training programs that foster both technical prowess and critical analytical thinking.

会计欺诈问题是商界面临的一个重大挑战，促使学术界在各种背景下开展更多的调查。尽管人们对这一问题的兴趣与日俱增，但专门针对泰国背景的研究仍然很少。因此，本定量研究旨在通过评估泰国 Z 世代会计师在侦查会计欺诈方面的熟练程度来弥补这一差距，尤其侧重于他们的数字、数据科学和诊断技能。研究采用结构化调查问卷的形式，向泰国会计专业的持证会计师发放问卷，收集了 150 名参与者的数据。研究采用了一个受社会学习理论和信息处理理论启发的理论框架，来研究调查的关键变量之间的直接关系和中介关系。研究结果采用偏最小二乘法结构方程模型（PLS-SEM）进行分析，以检验这些关系。结果显示，数字化能力对欺诈检测技能有显著的直接影响，诊断技能在这一过程中发挥了关键作用。研究表明，数字化能力不仅能为会计人员提供必要的技术专业知识，还能提高他们的分析能力，这对识别欺诈活动至关重要。同样，数据科学素养--包括预测分析、大数据管理和数据洞察交流方面的技能--大大提高了会计师识别和理解欺诈模式的能力。诊断技能作为关键中间环节的作用日益凸显，强调了同时培养技术能力和批判性分析思维的综合培训计划的重要性。

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引用次数: 0

A machine learning algorithm for personalized healthy and sustainable grocery product recommendations 用于个性化健康和可持续杂货产品推荐的机器学习算法

International Journal of Information Management Data Insights

Pub Date : 2024-11-20 DOI: 10.1016/j.jjimei.2024.100303

Laura Z.H. Jansen , Kwabena E. Bennin

Nowadays, retailers try to optimize the shopping experience for consumers by offering personalized services. Recommending food options, i.e. providing consumers suggestions on what products to buy, is one of such services. Food recommender systems for grocery shopping are typically preference-based, using consumers' shopping history to determine what products they would like. These systems can predict well what a consumer would potentially like to buy, however, they do not stimulate consumers to buy healthier or more sustainable food options. In response to increasing global concerns about public health and sustainability, this paper aims to integrate healthiness and sustainability levels of food options in recommender systems to encourage consumers to buy better food options. To assess the impact of integrating healthiness and sustainability information of food choices in predicting an item to buy, we employ three food recommendation models: a Baseline popularity-based model, Restricted Boltzmann Machine (RBM), and Variational Bayesian Context-Aware Representation (VBCAR) based on (1) preferences, (2) preferences and health, (3) preferences and sustainability, and (4) all combined attributes. Models were trained and tested using two different datasets: Instacart and a Dutch supermarket dataset. The experimental results indicate improved performance for VBCAR compared to Baseline and RBM. Models that emphasize healthiness and/or sustainability of food choices do not significantly alter model performance compared to preference-based models. The results of the health and sustainability-based recommender systems demonstrate the potential of recommender systems to assist people in finding healthier and more sustainable products that are also suited to their preferences.

如今，零售商试图通过提供个性化服务来优化消费者的购物体验。推荐食品选择，即向消费者提供购买何种产品的建议，就是此类服务之一。用于食品杂货购物的食品推荐系统通常以偏好为基础，利用消费者的购物记录来确定他们喜欢什么产品。这些系统可以很好地预测消费者可能喜欢购买的产品，但却不能刺激消费者购买更健康或更可持续的食品。针对全球日益关注的公共健康和可持续发展问题，本文旨在将食品选择的健康度和可持续发展水平纳入推荐系统，以鼓励消费者购买更好的食品选择。为了评估整合食品选择的健康性和可持续性信息对预测购买项目的影响，我们采用了三种食品推荐模型：基于流行度的基准模型、受限玻尔兹曼机（RBM）和基于（1）偏好、（2）偏好和健康、（3）偏好和可持续性以及（4）所有综合属性的变异贝叶斯情境感知表征（VBCAR）。使用两个不同的数据集对模型进行了训练和测试：Instacart 和荷兰超市数据集。实验结果表明，与 Baseline 和 RBM 相比，VBCAR 的性能有所提高。与基于偏好的模型相比，强调食品选择的健康性和/或可持续性的模型并没有显著改变模型的性能。基于健康和可持续性的推荐系统的结果表明，推荐系统有潜力帮助人们找到更健康、更可持续的产品，同时也符合他们的偏好。

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引用次数: 0

User-driven technology in NGOs—A computationally intensive theory approach 非政府组织中的用户驱动技术--计算密集型理论方法

International Journal of Information Management Data Insights

Pub Date : 2024-11-17 DOI: 10.1016/j.jjimei.2024.100307

Marie-E. Zubler (née Godefroid) , Julian Koch , Ralf Plattfaut

Non-governmental organizations (NGOs) typically have restrained information and communication technology (ICT) budgets and resources. At the same time, they face high pressure to reduce administrative costs. A possible solution to the resulting conundrum could be user-driven technology. This term describes a selection of technologies, including intelligent process automation, low-code platforms, and business intelligence tools that push innovation and user-centricity by letting operational employees directly deploy comparably cheap solutions without the need for central ICT support. Practitioner literature indicates, however, that user-driven technologies are lagging in the social sector despite evidence from some individual success stories published by researchers. Thus, a systematic assessment of user-driven technologies within NGOs and of potential challenges in their introduction is necessary. To close this research gap, we employ the method of computationally intensive theory construction, combining data mining with qualitative interviews. Results indicate that user-driven technologies are indeed lagging and that forming a problem-mindset and creating adequate governance structures are the main challenges to their introduction within NGOs.

非政府组织（NGO）的信息和传播技术（ICT）预算和资源通常都很有限。与此同时，它们还面临着降低行政成本的巨大压力。用户驱动技术是解决这一难题的一个可行办法。这一术语描述了一系列技术，包括智能流程自动化、低代码平台和商业智能工具，通过让业务员工直接部署价格相当低廉的解决方案而无需中央信息和通信技术的支持，推动创新和以用户为中心。然而，实践文献表明，尽管有研究人员发表的一些成功案例为证，但用户驱动技术在社会部门的应用仍然滞后。因此，有必要对非政府组织内部的用户驱动型技术及其引入过程中的潜在挑战进行系统评估。为了填补这一研究空白，我们采用了计算密集型理论构建方法，将数据挖掘与定性访谈相结合。结果表明，用户驱动技术确实滞后，而形成问题思维模式和建立适当的管理结构是在非政府组织内引入这些技术的主要挑战。

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引用次数: 0

Examining the effect of AI-BDA on manufacturing firm performance: An Indian approach 研究人工智能-BDA 对制造业公司业绩的影响：印度的方法

International Journal of Information Management Data Insights

Pub Date : 2024-11-16 DOI: 10.1016/j.jjimei.2024.100306

Vaibhav S. Narwane , Pragati Priyadarshinee

Manufacturing firms face an uncertain and continuosly changing environment because of innovations, technological changes, and globalization. To cope with this quick and uncertain environment, firms need to be flexible. Artificial Intelligence (AI) and Big Data Analytics (BDA) are must for manufacturing firms to achieve the flexibility in procurement to manufacturing to marketing. This study explores role of AI-BDA played between Supply Chain Flexibility (SCF) and Supply chain firms performance(SCFP) through six hypothesis. A sample data of 297 responses from forty Indian manufacturing firms were collected. Exploratory and confirmatory factorial analysis were used to analyse the collected data. Out of six hypothesis, four hypothesis are supported. The results show positive impact of AI, BDA and SCF on supply chain firm performance. Also AI positively impacts on BDA. However two hypothesis not supported are positive effect of AI and BDA on SCF needs further investigated. The study can guide decision makers to understand role of AI and BDA to improve supply chain performance.

由于创新、技术变革和全球化，制造企业面临着不确定且不断变化的环境。为了应对这种快速而不确定的环境，企业需要具有灵活性。人工智能（AI）和大数据分析（BDA）是制造企业实现从采购到制造再到营销的灵活性的必备条件。本研究通过六个假设探讨了人工智能-大数据分析在供应链灵活性（SCF）和供应链企业绩效（SCFP）之间的作用。研究收集了来自 40 家印度制造企业的 297 份样本数据。对收集到的数据进行了探索性和确认性因子分析。在六个假设中，四个假设得到了支持。结果显示，人工智能、BDA 和 SCF 对供应链企业绩效有积极影响。此外，人工智能对 BDA 也有积极影响。但有两个假设未得到支持，即人工智能和 BDA 对 SCF 的积极影响需要进一步研究。这项研究可以指导决策者了解人工智能和 BDA 在提高供应链绩效方面的作用。

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引用次数: 0

Blockchain-based conceptual model for enhanced transparency in government records: a design science research approach 基于区块链的提高政府记录透明度概念模型：一种设计科学研究方法

International Journal of Information Management Data Insights

Pub Date : 2024-11-14 DOI: 10.1016/j.jjimei.2024.100304

Eid M Alotaibi , Hussein Issa , Mauricio Codesso

In recent years, there have been massive changes to the government reporting requirements, which reflect the government's recognition of the need for a more open evidence-based practice. As a response, the U.S. government ordered to apply open government in all government agencies. The open government's objective is to have open government systems that include open access to their records, procedures, and data for public review and engagement. Currently, government agencies control and filter shared data with the public, limiting the ability to efficiently and effectively promote public oversight. This paper proposes a conceptual model, named GovBlockchain, that has the potential to achieve open government data objectives. The GovBlockchain is illustrated using the procurement cycle, and the results are subsequently compared with current open government practice. The results indicate that GovBlockchain provides stakeholders with a higher level of transparency.

近年来，政府报告要求发生了巨大变化，这反映出政府认识到需要更加开放的循证实践。作为回应，美国政府下令在所有政府机构实行开放式政府。开放式政府的目标是建立开放式政府系统，包括开放其记录、程序和数据，供公众审查和参与。目前，政府机构控制并过滤与公众共享的数据，从而限制了有效促进公众监督的能力。本文提出了一个名为 GovBlockchain 的概念模型，它有可能实现开放政府数据的目标。本文利用采购周期对 GovBlockchain 进行了说明，随后将其结果与当前的开放式政府实践进行了比较。结果表明，GovBlockchain 为利益相关者提供了更高的透明度。

引用次数: 0

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