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Purpose – This paper aims to explore the overall research question “How can artificial intelligence (AI) influence consumer information disclosure?”. It considers how anthropomorphism of AI, personalisation and privacy concerns influence consumers’ attitudes and encourage disclosure of their private information. Design/methodology/approach – This research draws upon the personalisation-privacy paradox (PPP) and privacy calculus theory (PCT) to address the research question and examine how AI can influence consumer information disclosure. It is proposed that anthropomorphism of AI and personalisation positively influence consumer attitudes and intentions to disclose personal information to a digital assistant, while privacy concerns negatively affect attitude and information disclosure. Findings – This paper develops a conceptual model based on and presents seven research propositions (RPs) for future research. Originality/value – Building upon PPP and PCT, this paper presents a view on the benefits and drawbacks of AI from a consumer perspective. This paper contributes to literature by critically reflecting upon on the question how consumer information disclosure is influenced by AI. In addition, seven RPs and future research areas are outlined in relation to privacy and consumer information disclosure in relation to AI. ¿Cómo anima la IA a los consumidores a compartir sus secretos? – El papel del antropomorfismo, la personalización y los problemas de privacidad y perspectivas para la investigación futura Resumen Propósito – Este artículo explora la pregunta general de investigación “¿Cómo puede influir la inteligencia artificial (IA) en la divulgación de información por parte de los consumidores? Se analiza cómo el antropomorfismo de la IA, la personalización y la preocupación por la privacidad influyen en la actitud de los consumidores y fomentan la revelación de su información privada. Diseño/metodología/enfoque – Esta investigación se basa en la paradoja de la personalización y la privacidad y en la teoría del cálculo de la privacidad para abordar la pregunta de investigación y examinar cómo la IA puede influir en la revelación de información de los consumidores. Se propone que el antropomorfismo de la IA y la personalización influyen positivamente en las actitudes de los consumidores y en su intención de revelar información personal a un asistente digital, mientras que la preocupación por la privacidad afecta negativamente a la actitud y a la revelación de información. Conclusiones – Este artículo desarrolla un modelo conceptual basado en siete propuestas de investigación para el futuro. Originalidad – Basándose en la paradoja de la personalización y la privacidad y en la teoría del cálculo de la privacidad, este artículo presenta un punto de vista sobre los beneficios e inconvenientes de la IA desde la perspectiva del consumidor. Este artículo contribuye a la literatura al reflexionar de forma crítica sobre la cuestión de cómo influye la IA en la revelación de información del consumidor. Además, se esbozan siete propuestas de investigación y futuras áreas de investigación en relación con la privacidad y la divulgación de información del consumidor en relación con la IA. 人工智能如何 – 鼓励消费者分享他们的秘密？拟人化、个性化和隐私问题的作用以及未来研究的途径 摘要 目的 – 本文探讨了 “人工智能如何影响消费者的信息披露？"这一总体研究问题。它考虑了人工智能（AI）的拟人化、个性化和隐私问题是如何影响消费者的态度并鼓励他们披露私人信息的。 设计/方法/途径 – 本研究借鉴了个性化-隐私悖论和隐私计算理论来解决研究问题, 并研究人工智能如何影响消费者信息披露。本文提出, 人工智能的拟人化和个性化对消费者向数字助理披露个人信息的态度和意图有积极影响, 而隐私问题对态度和信息披露有消极影响。 研究结果 – 本文在此基础上建立了一个概念模型, 并为未来的研究提出了七个研究命题。 原创性 – 在个性化-隐私悖论和隐私计算理论的基础上, 本文从消费者的角度提出了对人工智能的好处和坏处的看法。本文通过对消费者信息披露如何受到人工智能影响的问题进行批判性反思, 对文献做出了贡献。此外, 本文概述了与人工智能相关的隐私和消费者信息披露方面的七个研究命题和未来研究领域。

Genetically modified food (GMF) is one of the most debated issues in the food market. There has been considerable interest from both academic researchers and policy makers regarding the antecedents and consequences of the commercial adoption of GMF applications. Conceptually, GMF can be defined as “Genetically modified (hereafter GM) foods are produced from genetically modified seeds or ingredients derived from plants or animals whose DNA has been manipulated using genetic engineering methods” [1, p. 2861]. However, only a limited number of studies have tested the related issues of GMF products from a customer perspective. Thus, this project intends to discover and examine the main drivers and hindrances in predicting customers’ intention and buying decision behaviour in developing Arabian countries (i.e., Jordan). A diffusion of innovations (DOIs) model was selected as the theoretical basis for the current study project. A field survey study was conducted to collect the requested quantitative data from a convenience sample of Jordanian customers. Statistical results largely supported the role of relative advantage, compatibility, trialability, social approval, awareness, perceived risk and price value on the behavioural intention to adopt GMF products, which in turn significantly predicted actual adoption behaviour. The results of the current project will hopefully expand the current academic understanding of the main factors that predict Jordanian customers’ perception and adoption of GMF products.

Purpose – Number of disastrous events are rising globally, and it is important to manage the humanitarian supply chain management process to assist the disaster affected individuals in terms of relief operations. Effective relief operations can help to recover the materialistic loss due to any disaster. But there is a paucity of studies regarding this issue for developing countries. This study, hence, inspected the factors that affect the disaster supply chain management (DSCM) processes for relief operations in Bangladesh. Design/methodology/approach – This study examined the factors affecting relief operations through a qualitative analysis. This study used thematic analysis. Interviews were conducted with related supply chain individuals who were triangulated by data from related publications and blogs. Findings – The study showed that sustainable DSCM for relief operations in Bangladesh require addressing few factors as organizational capabilities, warehousing locations and inventory management, infrastructure facility, coordination among partners, government and local authority support to create a transparent, efficient, effective and sustainable DSCM process for relief operations in Bangladesh. The system loopholes can be identified and rectified on the base of these factors. Research limitations/implications – The number of interview respondents was limited to twenty who were selected randomly from four organizations. To create a sustainable disaster supply chain management (SCM) for relief operations few factors were considered as predominant factors in Bangladesh context to generalize the developing country contexts and other factors were not considered. Therefore, for farther humanitarian research, the model of this study can be used for quantitative research and the hypotheses can be tested empirically to get more acute findings. Practical implications – As this study identifies the factors which can help to create a sustainable DSCM system for relief operations, hence practically, Bangladesh humanitarian SCM agencies will be beneficial from this study. They can easily recognize the factors need to be considered to create a sustainable DSCM process for relief operations. Originality/value – This is a unique study carried out to examine the factors affecting DSCM process for relief operations in Bangladesh.

This study seeks to explain why telecom customers would continue to use mobile value-added services (MVAS), including information, communication, entertainment, and transaction services. We developed a model based on the S-O-R paradigm and existing research on MVAS and mobile service quality, in which we hypothesize that customers' intention to continue using MVAS as a behavioural response (R) is a direct result of their satisfaction with the services and their perception of its value as affective and cognitive states (O), respectively. The developed model also recognizes the importance of mobile service quality (S) in terms of characteristics and features in developing customer satisfaction and perceived value. In this investigation, mobile service quality aspects: customer service, service content, and mobile network quality are utilized as stimuli. The data was collected from 371 respondents utilizing an online survey instrument. PLS-SEM with SmartPLS3 software was used for data analysis. While both customer satisfaction and perceived value have direct positive influences on continuance usage intention, the customer satisfaction effect is more significant, according to the structural findings. Moreover, customer service quality, service content quality, and mobile network quality were all discovered to be direct predictors of perceived value. In contrast, mobile network quality was not revealed to be a significant predictor of customer satisfaction. This paper is one of the few investigating the major factors contributing to the continued use of MVAS in the Arab world. This work adds to the growing knowledge on post-adoption in mobile services and business. This investigation provides crucial suggestions for decision-makers in the mobile telecommunications industry from a practical standpoint.

Despite the worldwide surge in smartphone use, there are no classification metrics based on its use. In this article, a comprehensive concept called ‘Cellulographics’ is introduced for characterization of smartphone users, which includes behavioral classification based on user characteristics like smartphone experience (SE), smartphone use skill (SUS), smartphone internet experience (SIE), smartphone use periods (SUP), smartphone screen time (SST), smartphone use frequency (SUF), smartphone use activities (SUA), and smartphone use location (SUL). This concept can be applied to any field of study without limitations, where smartphone use is involved.

In recent years, examining the determinants and outcomes of online trust in emerging online markets in the North Africa Region has been lacking. Therefore, the purpose of this study is twofold: first, to gain knowledge of the key predictors of online trust in Morocco; second, to investigate the consequences of online trust on perceived risk, attitude, and online purchase intentions in Morocco. A research model based on the work of Jarvenpaa et al. (2000) was empirically tested. Data was collected from a total of 414 experienced online buyers through online surveys. The PLS approach using SmartPLS 3 was performed to test the hypotheses. The results demonstrate that the effect of perceived size and perceived reputation on online trust is positively significant; online trust has a significant positive influence on attitude and significant negative influence on perceived risk; online trust and attitude positively influence purchase intention; perceived risk has a significant negative effect on attitude and the negative influence of perceived risk on purchase intentions was found to be not significant. The post-hoc analysis further shows that attitude transmits completely the effect of perceived risk on purchase intention, while perceived risk partially mediates the effects of online trust on attitude.

Researchers have collected Twitter data to study a wide range of topics. This growing body of literature, however, has not yet been reviewed systematically to synthesize Twitter-related papers. The existing literature review papers have been limited by constraints of traditional methods to manually select and analyze samples of topically related papers. The goals of this retrospective study are to identify dominant topics of Twitter-based research, summarize the temporal trend of topics, and interpret the evolution of topics withing the last ten years. This study systematically mines a large number of Twitter-based studies to characterize the relevant literature by an efficient and effective approach. This study collected relevant papers from three databases and applied text mining and trend analysis to detect semantic patterns and explore the yearly development of research themes across a decade. We found 38 topics in more than 18,000 manuscripts published between 2006 and 2019. By quantifying temporal trends, this study found that while 23.7% of topics did not show a significant trend (P = 0.05), 21% of topics had increasing trends and 55.3% of topics had decreasing trends that these hot and cold topics represent three categories: application, methodology, and technology. The contributions of this paper can be utilized in the growing field of Twitter-based research and are beneficial to researchers, educators, and publishers.

The importance of data-driven decisions and support is increasing day by day in every management area. The constant access to volume, variety, and veracity of data has made big data an integral part of management studies. New sub-management areas are emerging day by day with the support of big data to drive businesses. This study takes a systematic literature review approach to uncover the emerging management areas supported by big data in contemporary times. For this, we have analyzed the research papers published in the reputed management journals in the last ten years, fir using network analysis followed by natural language processing summarization techniques to find the emerging new management areas which are yet to get much attention. Furthermore, we ran the same exercise in each of these management areas to uncover these areas better. This research will act as a reference for future information systems (IS) scholars who want to perform analysis that is deep-dive in nature on each of these management areas, which in the coming times will get all the due attention to become dedicated research domains in the management area. We finally conclude the study by identifying the scope of future research in each of these management areas, which will be a true value addition for IS researchers.

Widespread academic dishonesty among higher education (HE) students has been a concern for higher education institutes (HEIs). Ethics literature reports that unintentional plagiarism is more prevalent among HE students and the root cause is, limited or no awareness of nuances of ethics concerning plagiarism resulting in poor ethical judgments. This study attempts to examine what is students' ethical reasoning for unintentional plagiarism and how HEIs' ethical awareness efforts impact students' ethical judgments which ultimately shape their ethical behavior. The study also explored whether and how individual-level factors such as intrinsic religiosity, age, gender, and work experience moderate the focal relationships. A longitudinal quasi-experimental field study was conducted. The subjects of the study were 294 postgraduate students of an internationally accredited higher education institution in India. The pretest-posttest design involved a set of experimental manipulations reflecting the HEI's endeavors to explicate the unethical implications of plagiarism.