Reinforcing customer journey through artificial intelligence: a review and research agenda

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jyoti Rana ◽  
Loveleen Gaur ◽  
Gurmeet Singh ◽  
Usama Awan ◽  
Muhammad Imran Rasheed
Keyword(s):  
Artificial Intelligence ◽  
Research Agenda ◽  
Theoretical Framework ◽  
Customer Relationships ◽  
Protective Measure ◽  
Retail Sector ◽  
Model Framework ◽  
Customer Journey ◽  
Content Type ◽  
Research Plan

Purpose This study defines a three-angled research plan to intensify the knowledge and development undergoing in the retail sector. It proposes a theoretical framework of the customer journey to explain the customers' intent to adopt artificial intelligence (AI) and machine learning (ML) as a protective measure for interaction between the customer and the brand.Design/methodology/approach This study presents a research agenda from three-dimensional online search, ML and AI algorithms. This paper enhances the readers' understanding by reviewing the literature present in utilizing AI in the customer journey and presenting a theoretical framework.Findings Using AI tools like Chatbots, Recommenders, Virtual Assistance and Interactive Voice Recognition (IVR) helps create improved brand awareness, better customer relationships marketing and personalized product modification.Originality/value This study intends to identify a research plan based on investigating customer journey trends in today's changing times with AI incorporation. The research provides a novel model framework of the customer journey by directing customers into different stages and providing different touchpoints in each stage, all supported with AI and ML.

scholarly journals Role of artificial intelligence and robotics to foster the touchless travel during a pandemic: a review and research agenda

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Loveleen Gaur ◽  
Anam Afaq ◽  
Gurmeet Singh ◽  
Yogesh Kumar Dwivedi
Keyword(s):  
Artificial Intelligence ◽  
Research Agenda ◽  
Hospitality Industry ◽  
Management Practices ◽  
Hospitality Management ◽  
Protective Measure ◽  
Health Crisis ◽  
Content Type ◽  
Research Areas ◽  
And Robotics

Purpose The hospitality industry experienced an unanticipated challenge from the COVID-19 pandemic. However, research in this area is scarce. Accordingly, this study aims to unfold a three-angled research agenda to intensify the knowledge advancement in the hospitality sector. It proposes a theoretical framework by extending the protection motivation theory (PMT) to explain the guest’s intent to adopt artificial intelligence (AI) and robotics as a protective measure in reaction to COVID-19. Design/methodology/approach The research is centered on outlining the pertinent literature on hospitality management practices and the guest’s transformed behavior during the current crisis. This study intends to identify a research agenda based on investigating hospitality service trends in today’s changing times. Findings The study sets out a research agenda that includes three dimensions as follows: AI and robotics, cleanliness and sanitation and health care and wellness. This study’s findings suggest that AI and robotics may bring out definite research directions at the connection of health crisis and hospitality management, taking into account the COVID-19 crisis. Practical implications The suggested research areas are anticipated to propel the knowledge base and help the hospitality industry retrieve the COVID-19 crisis through digital transformation. AI and robotics are at the cusp of invaluable advancement that can revive the hotels while re-establish guests’ confidence in safe hotel practices. The proposed research areas are likely to impart pragmatic lessons to the hospitality industry to fight against disruptive situations. Originality/value This study stands out to be pioneer research that incorporated AI and robotics to expand the PMT and highlights how behavioral choices during emergencies can bring technological revolution.

Quantifying human resource management: a literature review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Clotilde Coron
Keyword(s):  
Artificial Intelligence ◽  
Resource Management ◽  
Literature Review ◽  
Human Resource Management ◽  
Human Resource ◽  
Design Methodology ◽  
Theoretical Framework ◽  
Data Sources ◽  
Content Type

PurposeWith a focus on the evolution of human resource management (HRM) quantification over 2000–2020, this study addresses the following questions: (1) What are the data sources used to quantify HRM? (2) What are the methods used to quantify HRM? (3) What are the objectives of HRM quantification? (4) What are the representations of quantification in HRM?Design/methodology/approachThis study is based on an integrative synthesis of 94 published peer-reviewed empirical and non-empirical articles on the use of quantification in HRM. It uses the theoretical framework of the sociology of quantification.FindingsThe analysis shows that there have been several changes in HRM quantification over 2000–2020 in terms of data sources, methods and objectives. Meanwhile, representations of quantification have evolved relatively little; it is still considered as a tool, and this ignores the possible conflicts and subjectivity associated with the use of quantification.Originality/valueThis literature review addresses the use of quantification in HRM in general and is thus larger in scope than previous reviews. Notably, it brings forth new insights on possible differences between the main uses of quantification in HRM, as well as on artificial intelligence and algorithms in HRM.

Developing a theoretical framework for intelligent contract acceptance

2020 ◽  
Vol 20 (3) ◽  
pp. 421-445 ◽  
Author(s):  
Alan J. McNamara ◽  
Samad M.E. Sepasgozar
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Industry 4.0 ◽  
Theoretical Framework ◽  
The Body ◽  
Extensive Literature ◽  
Contributing Factors ◽  
Model Framework ◽  
Content Type ◽  
Acceptance Model

Purpose This paper aims to develop a novel theoretical technology acceptance model, namely, for predicting acceptance of the trending technology of intelligent contracts (iContracts) in construction, which aims to integrate the data from emerging cyber-physical systems being introduced to the sector through the industry 4.0 revolution. This model includes main dimensions and critical contributing factors to assess the readiness for the iContract concept within the construction contract environment. Design/methodology/approach Through an extensive literature review, the structure of a unique theoretical technology acceptance model for iContract implementation, within construction, was developed iContract acceptance model (iCAM). Relevant themes were assessed through the lens of the technology acceptance model framework and the four accepted dimensions of the technology readiness index (TRI) concept. The main components of the model were examined with selected practitioners, with relevant experience and understanding of the iContract concept, with thematic mapping of the discussions correlated back to 12 specific iContract contributing constructs of the four adapted TRI dimensions. Findings The paper contributes to the body of knowledge by proposing a novel iCAM for a trending technology based on the specific requirements of iContract adoption. The interviews show that while the desire to digitalise the contractual environment exists, the readiness of the sector for such a disruptive change is unknown. Practical implications The findings and proposed conceptual iCAM offers a lens for the further development of the iContract concept by assisting practitioners to forecast digital readiness of the contract process in construction. Originality/value This study offers a unique and theoretical framework, in an embryonic field, for predicting the success of iContract implementation within construction organisations through the digital, industry 4.0 and revolution.

When technology meets people: the interplay of artificial intelligence and human resource management

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yusra Qamar ◽  
Rakesh Kumar Agrawal ◽  
Taab Ahmad Samad ◽  
Charbel Jose Chiappetta Jabbour
Keyword(s):  
Artificial Intelligence ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Research Agenda ◽  
Concept Map ◽  
Ethical Framework ◽  
Original Research ◽  
Content Type ◽  
Current State

PurposeAn original systematic review of the academic literature on applications of artificial intelligence (AI) in the human resource management (HRM) domain is carried out to capture the current state-of-the-art and prepare an original research agenda for future studies.Design/methodology/approachFifty-nine journal articles are selected based on a holistic search and quality evaluation criteria. By using content analysis and structural concept analysis, this study elucidates the extent and impact of AI application in HRM functions, which is followed by synthesizing a concept map that illustrates how the usage of various AI techniques aids HRM decision-making.FindingsA comprehensive review of the AI-HRM domain’s existing literature is presented. A concept map is synthesized to present a taxonomical overview of the AI applications in HRM.Research implications/limitationsAn original research agenda comprising relevant research questions is put forward to assist further developments in the AI-HRM domain. An indicative preliminary framework to help transition toward ethical AI is also presented.Originality/valueThis study contributes to the literature through a holistic discussion on the current state of the domain, the extent of AI application in HRM, and its current and perceived future impact on HRM functions. A preliminary ethical framework and an extensive future research agenda are developed to open new research avenues.

Congruency or incongruency: a theoretical framework and opportunities for future research avenues

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Andreas Aldogan Eklund ◽  
Miralem Helmefalk
Keyword(s):  
Research Agenda ◽  
Spillover Effects ◽  
Underlying Mechanism ◽  
Theoretical Framework ◽  
Future Research ◽  
Content Type ◽  
Semantic Cues ◽  
Future Research Agenda ◽  
Trade Offs ◽  
Theoretical Foundations

Purpose The purpose of this paper is to conceptualise and provide a future research agenda for (in)congruence regarding cues between products, brands and atmospheres. Design/methodology/approach A semi-systematic literature review was conducted. The aim was to assess, critique and synthesise (in)congruence, which was found in the literature to be dispersed and interdisciplinary, and to propose a theoretical framework in the marketing domain. Findings Firstly, the review reveals that sensory and semantic cues are interrelated in products, brands and atmospheres. It illustrates that these cues are the foundation for (in)congruence. Secondly, the findings show various theoretical foundations for (in)congruence. These explain where and how congruence occurs. Lastly, a theoretical framework for (in)congruence and a future research agenda were developed to stimulate further research. Research limitations/implications A theoretical framework was developed to enrich the theoretical knowledge and understanding of (in)congruence in the marketing domain. Practical implications The review reveals that products, brands and atmospheres have spillover effects. Managers are advised to understand the semantic meaning carried by cues to foster various outcomes, to estimate the trade-offs when modifying (in)congruent cues for products, brands and atmospheres. Originality/value The developed theoretical framework advances and deepens the knowledge of (in)congruence in the marketing domain by moving beyond the match and fit between two entities and by revealing the underlying mechanism and its outcomes.

scholarly journals Limits of artificial intelligence in controlling and the ways forward: a call for future accounting research

2021 ◽  
Vol 22 (2) ◽  
pp. 365-382
Author(s):  
Heimo Losbichler ◽  
Othmar M. Lehner
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Complex Systems ◽  
Research Agenda ◽  
Future Research ◽  
Ethical Considerations ◽  
Content Type ◽  
Previous Discussion ◽  
Research Questions ◽  
Methodological Considerations

PurposeLooking at the limits of artificial intelligence (AI) and controlling based on complexity and system-theoretical deliberations, the authors aimed to derive a future outlook of the possible applications and provide insights into a future complementary of human–machine information processing. Derived from these examples, the authors propose a research agenda in five areas to further the field.Design/methodology/approachThis article is conceptual in its nature, yet a theoretically informed semi-systematic literature review from various disciplines together with empirically validated future research questions provides the background of the overall narration.FindingsAI is found to be severely limited in its application to controlling and is discussed from the perspectives of complexity and cybernetics. A total of three such limits, namely the Bremermann limit, the problems with a partial detectability and controllability of complex systems and the inherent biases in the complementarity of human and machine information processing, are presented as salient and representative examples. The authors then go on and carefully illustrate how a human–machine collaboration could look like depending on the specifics of the task and the environment. With this, the authors propose different angles on future research that could revolutionise the application of AI in accounting leadership.Research limitations/implicationsFuture research on the value promises of AI in controlling needs to take into account physical and computational effects and may embrace a complexity lens.Practical implicationsAI may have severe limits in its application for accounting and controlling because of the vast amount of information in complex systems.Originality/valueThe research agenda consists of five areas that are derived from the previous discussion. These areas are as follows: organisational transformation, human–machine collaboration, regulation, technological innovation and ethical considerations. For each of these areas, the research questions, potential theoretical underpinnings as well as methodological considerations are provided.

Welcome to the marriage of human capability and artificial intelligence

2019 ◽  
Vol 19 (1) ◽  
pp. 10-14
Author(s):  
Ryan Scott ◽  
Malcolm Le Lievre
Keyword(s):  
Artificial Intelligence ◽  
Team Building ◽  
Workplace Change ◽  
Content Type ◽  
The Future ◽  
Human Capability ◽  
Mind Set ◽  
Future Work ◽  
Crucial Part ◽  
Practical Implications

Purpose The purpose of this paper is to explore insights methodology and technology by using behavioral to create a mind-set change in the way people work, especially in the age of artificial intelligence (AI). Design/methodology/approach The approach is to examine how AI is driving workplace change, introduce the idea that most organizations have untapped analytics, add the idea of what we know future work will look like and look at how greater, data-driven human behavioral insights will help prepare future human-to-human work and inform people’s work with and alongside AI. Findings Human (behavioral) intelligence will be an increasingly crucial part of behaviorally smart organizations, from hiring to placement to adaptation to team building, compliance and more. These human capability insights will, among other things, better prepare people and organizations for changing work roles, including working with and alongside AI and similar tech innovation. Research limitations/implications No doubt researchers across the private, public and nonprofit sectors will want to further study the nexus of human capability, behavioral insights technology and AI, but it is clear that such work is already underway and can prove even more valuable if adopted on a broader, deeper level. Practical implications Much “people data” inside organizations is currently not being harvested. Validated, scalable processes exist to mine that data and leverage it to help organizations of all types and sizes be ready for the future, particularly in regard to the marriage of human capability and AI. Social implications In terms of human capability and AI, individuals, teams, organizations, customers and other stakeholders will all benefit. The investment of time and other resources is minimal, but must include C-suite buy in. Originality/value Much exists on the softer aspects of the marriage of human capability and AI and other workplace advancements. What has been lacking – until now – is a 1) practical, 2) validated and 3) scalable behavioral insights tech form that quantifiably informs how people and AI will work in the future, especially side by side.

scholarly journals An academic perspective on the entrepreneurship policy agenda: themes, geographies and evolution

2019 ◽  
Vol 9 (1) ◽  
pp. 65-93 ◽  
Author(s):  
Alberto Arenal ◽  
Claudio Feijoo ◽  
Ana Moreno ◽  
Cristina Armuña ◽  
Sergio Ramos
Keyword(s):  
Text Mining ◽  
Research Agenda ◽  
Academic Research ◽  
Policy Research ◽  
Policy Agenda ◽  
The European Union ◽  
Entrepreneurship Policy ◽  
Research Activity ◽  
Content Type ◽  
And Shifts

Purpose Academic research into entrepreneurship policy is particularly interesting due to the increasing relevance of the topic and since knowledge about the evolution of themes in this field is still rather limited. The purpose of this paper is to analyse the key concepts, topics, trends and shifts that have shaped the entrepreneurship policy research agenda during the period 1990–2016. Design/methodology/approach This paper uses text mining techniques, cluster analysis and complementary bibliographic data to examine the evolution of a corpus of 1,048 academic papers focused on entrepreneurship-related policies and published during the period 1990–2016 in ten relevant journals. In particular, the paper follows a standard text mining workflow: first, as text is unstructured, content requires a set of pre-processing tasks and then a stemming process. Then, the paper examines the most repeated concepts within the corpus, considering the whole period 1990–2016 and also in five-year terms. Finally, the paper conducts a k-means clustering to divide the collection of documents into coherent groups with similar content. The analyses in the paper also include geographical particularities considering three regional sub-corpora, distinguishing those articles authored in the European Union (EU), the USA and South and Eastern Asia, respectively. Findings Results of the analysis show that inclusion, employment and regulation-related papers have largely dominated the research in the field, evolving from an initial classical approach to the relationship between entrepreneurship and employment to a wider, multidisciplinary perspective, including the relevance of management, geographies and narrower topics such as agglomeration economics or internationalisation instead of the previous generic sectorial approaches. The text mining analysis also reveals how entrepreneurship policy research has gained increasing attention and has become both more open, with a growing cooperation among researchers from different affiliations, and more sophisticated, with concepts and themes that moved the research agenda forward, closer to the priorities of policy implementation. Research limitations/implications The paper identifies main trends and research gaps in the field of entrepreneurship policy providing actionable knowledge by presenting the spectrum of both over-explored and understudied research themes in the field. In practical terms the results of the text mining analysis can be interpreted as a compass to navigate the entrepreneurship policy research agenda. Practical implications The paper presents the heterogeneity of topics under research in the field, reinforcing the concept of entrepreneurship as a multidisciplinary and dynamic domain. Therefore, the definition and adoption of a certain policy agenda in entrepreneurship should consider multiple aspects (needs, objectives, stakeholders, expected outputs, etc.) to be comprehensive and aligned with its complexity. In addition, the paper shows how text mining techniques could be used to map the research activity in a particular field, contributing to the challenge of linking research and policy. Originality/value The exploratory nature of text mining allows us to obtain new knowledge and reveals hidden patterns from large quantities of documents/text data, representing an opportunity to complement other qualitative reviews. In this sense, the main value of this paper is not to advise on the future configuration of entrepreneurship policy as a research topic, but to unwrap the past by unveiling how key themes of the entrepreneurship policy research agenda have emerged, evolved and/or declined over time as a foundation on which to build further developments.

scholarly journals Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda

2021 ◽  
Vol 7 (1) ◽  
pp. 71
Author(s):  
Tan Yigitcanlar ◽  
Juan M. Corchado ◽  
Rashid Mehmood ◽  
Rita Yi Man Li ◽  
Karen Mossberger ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Local Government ◽  
Conceptual Framework ◽  
Research Agenda ◽  
Future Studies ◽  
Expert Team ◽  
Research Questions ◽  
Urban Problems ◽  
Technological Opportunities ◽  
Made In

The urbanization problems we face may be alleviated using innovative digital technology. However, employing these technologies entails the risk of creating new urban problems and/or intensifying the old ones instead of alleviating them. Hence, in a world with immense technological opportunities and at the same time enormous urbanization challenges, it is critical to adopt the principles of responsible urban innovation. These principles assure the delivery of the desired urban outcomes and futures. We contribute to the existing responsible urban innovation discourse by focusing on local government artificial intelligence (AI) systems, providing a literature and practice overview, and a conceptual framework. In this perspective paper, we advocate for the need for balancing the costs, benefits, risks and impacts of developing, adopting, deploying and managing local government AI systems in order to achieve responsible urban innovation. The statements made in this perspective paper are based on a thorough review of the literature, research, developments, trends and applications carefully selected and analyzed by an expert team of investigators. This study provides new insights, develops a conceptual framework and identifies prospective research questions by placing local government AI systems under the microscope through the lens of responsible urban innovation. The presented overview and framework, along with the identified issues and research agenda, offer scholars prospective lines of research and development; where the outcomes of these future studies will help urban policymakers, managers and planners to better understand the crucial role played by local government AI systems in ensuring the achievement of responsible outcomes.

Country of origin branding: an integrative perspective

2016 ◽  
Vol 25 (4) ◽  
pp. 322-336 ◽  
Author(s):  
Roderick J. Brodie ◽  
Maureen Benson-Rea
Keyword(s):  
Country Of Origin ◽  
Theoretical Framework ◽  
Illustrative Case ◽  
Business Relationships ◽  
Content Type ◽  
Brand Meaning ◽  
Value Propositions ◽  
Illustrative Case Study ◽  
Strategic Perspective

Purpose A new conceptualization of the process of country of origin (COO) branding based on fresh theoretical foundations is developed. This paper aims to provide a strategic perspective that integrates extant views of COO branding, based on identity and image, with a relational perspective based on a process approach to developing collective brand meaning. Design/methodology/approach A systematic review of the literature on COO branding and geographical indicators is undertaken, together with a review of contemporary research on branding. Our framework conceptualizes COO branding as an integrating process that aligns a network of relationships to co-create collective meaning for the brand’s value propositions. Findings An illustrative case study provides empirical evidence to support the new theoretical framework. Research limitations/implications Issues for further research include exploring and refining the theoretical framework in other research contexts and investigating broader issues about how COO branding influences self and collective interests in business relationships and industry networks. Practical implications Adopting a broadened perspective of COO branding enables managers to understand how identity and image are integrated with their business relationships in the context of developing collective brand meaning. Providing a sustained strategic advantage for all network actors, an integrated COO branding process extends beyond developing a distinctive identity and image. Originality/value Accepted consumer, product, firm and place level perspectives of COO branding are challenged by developing and verifying a new integrated conceptualization of branding.

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