Internet of things and consumer engagement on retail: State-of-the-art and future directions

Purpose The growing complexity of consumer engagement (CE) due to the impact of Internet of things (IoT) has been attracting significant attention from both academics and industry practitioners especially in recent times. Hence, understanding this phenomenon remains very crucial to the body of knowledge. This study conducted a systematic review on IoT and CE with the aim of proposing future research opportunities using the TCCM model. Design/methodology/approach Extant literature studies were systematically examined by sourcing high ranking ABS journals from EBSCO, ScienceDirect and Emerald. A total of 58 articles were included in the final analysis of this research. Findings The analysis established the need to conduct more research on CE due to the impact of new technological implementation in retail. The results further suggest the need for extensive research across African countries and emerging markets to enable broader empirical generalizations of research outcomes. Using the TCCM framework, the authors indicated directions for future empirical research. Originality/value This study exposes the current trends in CE and IoT. The results and analysis are both compelling and verifiable, hence, establishing a firm base of reference for future research in related fields.info:eu-repo/semantics/acceptedVersio

The potential of artificial intelligence in retail banking and the challenge of organizational transformation

In the work project “The Future of German Retail Banking”, Artificial Intelligence (AI) was identified as an impactful trend in the industry. AI finds applications in banking bearing great potential for retail banks. With increasing customer expectations towards AI adoption and new competition in the German retail banking market, traditional retail banks are advised to capture the potential of AI technology. This research paper aims to demonstrate the relevance and potential of AI use for retail banks and identifies necessary changes of organizational elements along the McKinsey 7 S change management tool for organizational transformation to successfully adopt AI

Behind the scenes of emerging technologies Opportunities, challenges, and solution approaches along a socio-technical continuum

Digitalization is a socio-technical phenomenon that shapes our lives as individuals, economies, and societies. The perceived complexity of technologies continues to increase, and technology convergence makes a clear separation between technologies impossible. A good example of this is the Internet of Things (IoT) with its embedded Artificial Intelligence (AI). Furthermore, a separation of the social and the technical component has become near enough impossible, for which there is increasing awareness in the Information Systems (IS) community. Overall, emerging technologies such as AI or IoT are becoming less understandable and transparent, which is evident for instance when AI is described in terms of a black box. This opacity undermines humans trust in emerging technologies, which, however, is crucial for both its usage and spread, especially as emerging technologies start to perform tasks that bear high risks for humans, such as autonomous driving. Critical perspectives on emerging technologies are often discussed in terms of ethics, including such aspects as the responsibility for decisions made by algorithms, the limited data privacy, and the moral values that are encoded in technology. In sum, the varied opportunities that come with digitalization are accompanied by significant challenges. Research on the negative ramifications of AI is crucial if we are to foster a human-centered technological development that is not simply driven by opportunities but by utility for humanity. As the IS community is positioned at the intersection of the technological and the social context, it plays a central role in finding answers to the question as to how the advantages outweigh the challenges that come with emerging technologies. Challenges are examined under the label of dark side of IS, a research area which receives considerably less attention in existing literature than the positive aspects (Gimpel & Schmied, 2019). With its focus on challenges, this dissertation aims to counterbalance this. Since the remit of IS research is the entire information system, rather than merely the technology, humanistic and instrumental goals ought to be considered in equal measure. This dissertation follows calls for research for a healthy distribution along the so-called socio-technical continuum (Sarker et al., 2019), that broadens its focus to include the social as well as the technical, rather than looking at one or the other. With that in mind, this dissertation aims to advance knowledge on IS with regard to opportunities, and in particular with a focus on challenges of two emerging technologies, IoT and AI, along the socio-technical continuum. This dissertation provides novel insights for individuals to better understand opportunities, but in particular possible negative side effects. It guides organizations on how to address these challenges and suggests not only the necessity of further research along the socio-technical continuum but also several ideas on where to take this future research. Chapter 2 contributes to research on opportunities and challenges of IoT. Section 2.1 identifies and structures opportunities that IoT devices provide for retail commerce customers. By conducting a structured literature review, affordances are identified, and by examining a sample of 337 IoT devices, completeness and parsimony are validated. Section 2.2 takes a close look at the ethical challenges posed by IoT, also known as IoT ethics. Based on a structured literature review, it first identifies and structures IoT ethics, then provides detailed guidance for further research in this important and yet under-appreciated field of study. Together, these two research articles underline that IoT has the potential to radically transform our lives, but they also illustrate the urgent need for further research on possible ethical issues that are associated with IoTs specific features. Chapter 3 contributes to research on AI along the socio-technical continuum. Section 3.1 examines algorithms underlying AI. Through a structured literature review and semi-structured interviews analyzed with a qualitative content analysis, this section identifies, structures and communicates concerns about algorithmic decision-making and is supposed to improve offers and services. Section 3.2 takes a deep dive into the concept of moral agency in AI to discuss whether responsibility in human-computer interaction can be grasped better with the concept of agency. In section 3.3, data from an online experiment with a self-developed AI system is used to examine the role of a users domain-specific expertise in trusting and following suggestions from AI decision support systems. Finally, section 3.4 draws on design science research to present a framework for ethical software development that considers ethical issues from the beginning of the design and development process. By looking at the multiple facets of this topic, these four research articles ought to guide practitioners in deciding which challenges to consider during product development. With a view to subsequent steps, they also offer first ideas on how these challenges could be addressed. Furthermore, the articles offer a basis for further, solution-oriented research on AIs challenges and encourage users to form their own, informed, opinions.Die Digitalisierung ist ein sozio-technisches Phänomen, das unser persönliches Leben, aber auch die Wirtschaft und die gesamte Gesellschaft prägt. Die wahrgenommene Komplexität von Technologie nimmt stetig zu. Die Technologiekonvergenz macht eine klare Trennung zwischen Technologien praktisch unmöglich, wofür das Internet der Dinge (IoT) mit seiner eingebetteten Künstlichen Intelligenz (KI) ein gutes Beispiel ist. Darüber hinaus wird eine Trennung der sozialen und der technischen Komponente nahezu unmöglich, wofür es ein steigendes Bewusstsein in der Information Systems (IS) Community gibt. Insgesamt werden aufstrebende Technologien wie KI oder IoT weniger verständlich und transparent, was sich beispielsweise darin zeigt, dass KI der Begriff der Black Box zugeschrieben wird. Die Undurchsichtigkeit untergräbt das Vertrauen der Menschen in aufstrebende Technologien, das jedoch für die Nutzung und Verbreitung dieser entscheidend ist, insbesondere wenn Technologien Aufgaben übernehmen oder unterstützen, die hohe Risiken für den Menschen bergen, wie z. B. autonomes Fahren. Kritische Perspektiven auf neue Technologien werden oft unter dem Begriff der Ethik diskutiert, darunter Aspekte wie die Verantwortung für Entscheidungen, die von Algorithmen getroffen werden, moralische Werte, die in die Technologie eingebettet sind, und Datenschutz. Zusammenfassend lässt sich sagen, dass die vielfältigen Chancen der Digitalisierung mit Herausforderungen einhergehen. Die Forschung zu Risiken und Nebenwirkungen ist entscheidend, um eine menschenzentrierte technologische Entwicklung zu fördern, die nicht nur von den Möglichkeiten, sondern insbesondere vom Nutzenstiften für die Menschheit getrieben ist. An der Schnittstelle zwischen Technologie und sozialem Kontext angesiedelt, spielt die IS-Community eine wichtige Rolle bei der Suche nach Antworten auf die Frage, wie die Vorteile die Risiken neuer Technologien überwiegen können. Herausforderungen werden im Forschungsbereich dark side of IS untersucht, welcher in der bestehenden Literatur deutlich weniger Aufmerksamkeit erhält als die positiven Aspekte (Gimpel & Schmied, 2019). Dem möchte diese Dissertation ein Stück weit entgegenwirken, indem ein Fokus auf die Herausforderungen gelegt wird. Da in der IS-Forschung das gesamte Informationssystem und nicht nur die Technologie im Mittelpunkt der Betrachtung steht, sollen humanistische und instrumentelle Ziele gleichermaßen berücksichtigt werden. Darüber hinaus folgt diese Dissertation dem Aufruf nach einer angemessenen Verteilung der Forschung entlang des sogenannten sozio-technischen Kontinuums (Sarker et al., 2019) und löst sich somit von Forschung, die am sozialen oder technischen Endpunkt des Kontinuums angesiedelt ist. Zusammenfassend zielt diese Dissertation darauf ab, das Wissen über IS im Hinblick auf die Chancen und insbesondere die Herausforderungen entlang des sozio-technischen Kontinuums der aufkommenden Technologien IoT und KI voranzutreiben. Damit liefert die Dissertation neue Einblicke für Individuen, um die Möglichkeiten, aber insbesondere die potenziellen negativen Nebenwirkungen der Digitalisierung besser zu verstehen, bietet Orientierung für Organisationen, um diese Herausforderungen zu adressieren, und veranschaulicht die Notwendigkeit und Ideen für weitere Forschung entlang des sozio-technischen Kontinuums. Kapitel 2 leistet einen Beitrag zur Forschung über Chancen und Herausforderungen des IoT. Kapitel 2.1 identifiziert und strukturiert Chancen von IoT-Geräten für Kunden im Einzelhandel. Mit einer strukturierten Literaturrecherche werden Affordanzen von IoT-Geräten für Kunden identifiziert und mit einer Stichprobe von 337 IoT-Geräten wird eine Validierung hinsichtlich Vollständigkeit und Sparsamkeit durchgeführt. Kapitel 2.2 beschäftigt sich mit ethischen Herausforderungen des IoT, genannt IoT-Ethik. Basierend auf einer strukturierten Literaturrecherche identifiziert und strukturiert es die IoT-Ethik und gibt detaillierte Hinweise für die weitere Erforschung dieses wichtigen, aber noch zu wenig erforschten Feldes. Mit diesen beiden Forschungsartikeln unterstreicht diese Dissertation das Potenzial des IoT, unser Leben radikal zu verändern, verdeutlicht aber auch den Bedarf an weiterer Forschung zu potenziellen ethischen Fragen, die mit den spezifischen Eigenschaften des IoT verbunden sind. Kapitel 3 trägt zur Forschung über KI entlang des sozio-technischen Kontinuums bei. Kapitel 3.1 untersucht die Algorithmen, die KI zugrunde liegen. Eine strukturierte Literaturrecherche und semi-strukturierte Interviews, die mit einer qualitativen Inhaltsanalyse analysiert werden, zielen darauf ab, Bedenken gegenüber algorithmischer Entscheidungsfindung zu identifizieren, zu strukturieren und zu kommunizieren, um darauf basierend Angebote und Dienstleistungen zu verbessern. Kapitel 3.2 bietet eine ethische Vertiefung in das Konzept der moralischen Handlungsfähigkeit und untersucht, ob Verantwortung in der Mensch-Computer-Interaktion mit dem Konzept der Agency besser erfasst werden kann. In Kapitel 3.3 wird anhand von Daten aus einem Online-Experiment mit einem selbst entwickelten KI-System untersucht, welche Rolle das domänenspezifische Fachwissen der Nutzer für das Vertrauen in und das Befolgen von Vorschlägen von KI-Entscheidungsunterstützungssystemen spielt. Schließlich wird in Kapitel 3.4 auf der Grundlage designwissenschaftlicher Forschung ein Rahmenwerk für ethische Softwareentwicklung vorgestellt, das ethische Aspekte bereits zu Beginn des Design- und Entwicklungsprozesses berücksichtigt. Diese vier Forschungsartikel können Praktikern als Orientierung dienen, welche Herausforderungen bei der Produktentwicklung zu berücksichtigen sind und bieten erste Ideen, wie sie diese angehen können. Darüber hinaus bieten die Forschungsergebnisse eine Grundlage für weitere, lösungsorientierte Forschung zu den Herausforderungen von KI und ermutigen Nutzer, sich eine eigene, fundierte Meinung zu bilden

Understanding Organizations’ Artificial Intelligence Journey: A Qualitative Approach

Background: With growth in Artificial Intelligence (AI) adoption, challenges and hurdles are also becoming evident. Organizations implementing AI are challenged to find ways to leverage AI to produce optimum results and benefits for the organization. Understanding other organizations’ AI implementation journeys will help them start and implement AI. By understanding the different facets of AI implementation, they can strategize AI to gain business value. Though several studies have examined AI adoption, there are few studies on how firms implement it. We close this gap by studying AI adoption and implementations in various firms. Method: Using a qualitative approach of semi-structured interviews, we studied twenty global organizations of various sizes that have implemented AI. Results: The study categorizes the results into four major themes – facilitators, barriers, trends, and strategies for implementing AI. Our study reinforces the relevance of the TOE framework and Roger’s DOI theory in studying AI adoption. Organizational factors such as top management support, strategic roadmap, availability of skilled resources, and corporate culture influenced AI adoption. Their lack of data or poor data quality is a primary challenge. The privacy laws concerning data, as well as regulatory bottlenecks, further exacerbate this problem. We also identified and mapped the standard AI implementations to their AI technologies. We found that most of them exploit AI’s image and natural language processing capabilities to automate their processes. Regarding implementation, firms work with partners to obtain customer data and use federated learning. Conclusion: Understanding firms’ AI implementation journey will help us promote further adoption and experimentation. Organizations can identify areas where they can leverage AI to enhance value, prepare themselves for the future, start and proceed with AI implementation efforts and overcome barriers they might encounter

Internet of Things for improving Supply Chain Performance: A Qualitative study of Australian retailers

Internet of Things (IoT) is a global platform of Internet connected smart devices that have been argued to improve the supply chain integration (SCI). While the positive effect of IoT capability on SCI influencing supply chain and firm performance is empirically validated, exploratory study in this context is limited. Drawing upon the organisational capability theory, this study investigates the use of IoT in enhancing the integration of suppliers, customers and internal activities of the retail supply chain. Interviews of managers across Australian retail industry were analysed using Nvivo. The thematic analysis reveals the added capability of IoT that improves supply chain visibility, auto-capture and information sharing for greater SCI. The IoT-enabled integration capability demonstrates a positive effect on cost, quality, delivery, and flexibility of the entire supply chain and improves retail firm’s sustainable performance with financial,social and environmental outcomes

Application of Internet of Things to Ensure Improved Performance within the Internal Supply Chain Unit of an Organization

With the rapidly changing business world, technology adapted for doing business has also undergone rapid transformation leading to use Internet of Things as an advanced technological innovation required to connect production units to internet devices for smooth production and operation, with enhanced ICT systems and infrastructure. Internet of Things is considered to be an advanced information and communication technology, whose applicability is highly needed to ensure smart performance of organizations in Indonesia. Indonesia, being a developing country, adapting to new ways of doing things, including the use of IoT takes time, hence affecting studies regarding the use of IoT in business units, such as the internal supply chain sector. Thus, there is no much studies from a localized perspective, measuring the importance and using IoT as well as supply chain performance of the country. The present paper applied an organizational capacity theory to establish the Internet of Things impact on varying dimensions of Supply Chain, which included supply chain integration process, organizational performance of supply chain and the capacity to the influence production. The research applied a survey of cross-section on several companies within the Greater Jakarta area as the research approach. Data was obtained from over 161 companies from across Jakarta. Finally, the data was analyzed with the help of the structural equation modelling (SEM-AMOS) for the development of an empirical structural model

The effect of “Internet of Things” on supply chain integration and performance: An organisational capability perspective

The Internet of things (IoT) is a next generation of Internet connected embedded ICT systems in a digital environment to seamlessly integrate supply chain and logistics processes. Integrating emerging IoT into the current ICT systems can be unique because of its intelligence, autonomous and pervasive applications. However, research on the IoT adoption in supply chain domain is scarce and acceptance of the IoT into the retail services in specific has been overly rhetoric. This study is drawn upon the organisational capability theory for developing an empirical model considering the effect of IoT capabilities on multiple dimensions of supply chain process integration, and in turn improves supply chain performance as well as organisational performance. Cross-sectional survey data from 227 Australian retail firms was analysed using structural equation modelling (SEM). The results indicate that IoT capability has a positive and significant effect on internal, customer-, and supplier-related process integration that in turn positively affects supply chain performance and organisational performance. Theoretically, the study contributes to a body of knowledge that integrates information systems research into supply chain integration by establishing an empirical evidence of how IoT-enabled process integration can enhance the performance at both supply chain and organisational level. Practically, the results inform the managers of the likely investment on IoT that can lead to chain’s performance outcome

The connected consumer‎: A theoretical framework of consumer adoption/consequences of the Internet of Things and smart connected objects

Over the last decade, technological and Internet innovations have increasingly invaded the consumer market (N’Goala, 2016). The Internet of Things (IoT) is becoming a common platform, and disrupts relationships between consumers and companies (Bohli et al., 2009); in essence, this is a timely research. The major goal of this thesis is to deepen the understanding of the acceptance and the adoption processes of the IoT and smart connected technologies, as well as the related consequences on perceived well-being. To do this, four contexts of study have been explored: smart connected objects, smart sleep applications, smart homes, and smart stores. First, we performed qualitative exploratory studies, and secondly we conducted quantitative studies to build conceptual models according to our qualitative findings and the literature. The results show that technology benefits are the first factors that enable technology acceptance through perceived usefulness and perceived ease of use; subsequently, self-improvement, through perceived social image and well-being benefits, are the main reasons to continue using the IoT and smart connected technologies. The acceptance and the adoption of these technologies also depend on users’ personality traits while perceived risks and fears on the use of the personal data are the main barriers. In turn, the IoT and smart connected technologies influence perceived well-being according to the experience of use, personality traits, and the technology.Le résumé en français n'a pas été communiqué par l'auteur

Digital Analytics:Modeling for Insights and New Methods

Firms are increasingly turning towards new-age technologies such as artificial intelligence (AI), the internet of things (IoT), blockchain, and drones, among others, to assist in interacting with their customers. Further, with the prominence of personalization and customer engagement as the go-to customer management strategies, it is essential for firms to understand how to integrate the new-age technologies into their existing practices seamlessly to aid in the generation of actionable insights. Towards this end, this study proposes an organizing framework to understand how firms can use digital analytics, within the changing technology landscape, to generate consumer insights. The proposed framework begins by recognizing the forces that are external to the firm that then leads to the generation of specific capabilities by the firm. Further, the firm capabilities can lead to the generation of insights for decision making that can be data-driven and/or analytics-driven. Finally, the proposed framework identifies the creation of value-based outcomes for firms and customers, resulting from the insights generated. Additionally, we identify moderators that influence (a) the impact of external forces on the development of firm capabilities, and (b) the creation of insights and subsequent firm outcomes. This study also identifies questions for future research that combines the inclusion of new-age technologies, generation of strategic insights, and the achievement of established firm outcomes