Miljenka Perovic, Vaughan Coffey, Stephen Kajewski and Ashok Madan
The purpose of this paper is to provide an overview of the diverse issues that affect heritage projects during their lifecycle and in particular, why heritage-listed projects…
Abstract
Purpose
The purpose of this paper is to provide an overview of the diverse issues that affect heritage projects during their lifecycle and in particular, why heritage-listed projects often fail to meet the delivery goals of time, budget, quality and scope.
Design/methodology/approach
This research was undertaken on a qualitative basis by conducting series of semi-structured interviews drawn from three case studies in SE Queensland. Qualitative research involves the evaluation of people’s experiences, feelings, social interactions, and the data gathered from this type of methodology is often varied and rich. A case study allows a researcher to test and generate theories based on real-world practice.
Findings
This paper presents the findings from a data collection exercise accomplished by conducting a series of qualitative case studies. Using a cross-case analysis approach, this paper highlights critical heritage project delivery issues and their causes.
Practical implications
The lessons learned from the study cases could be used in helping to prevent potential heritage project failures in the future.
Originality/value
The paper aims to bring greater awareness to practitioners and academics of the repeating issues that every heritage project is likely to face and offers some insight in how these may be mitigated.
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Hamad Mohamed Almheiri, Syed Zamberi Ahmad, Khalizani Khalid and Abdul Hafaz Ngah
This study aims to evaluate an artificial intelligence (AI) capability scale using resource-based theory and tests its impact on dynamic capabilities and organizational creativity…
Abstract
Purpose
This study aims to evaluate an artificial intelligence (AI) capability scale using resource-based theory and tests its impact on dynamic capabilities and organizational creativity to influence the performance of public organizations.
Design/methodology/approach
The study used qualitative and quantitative methods to develop and validate an AI capability scale using an integrative psychometric approach. An initial set of 26 items was selected from the literature for qualitative analysis. Self-reported data from 344 public managers in United Arab Emirates public organizations were used for scale refinement and validation. Hypotheses were tested against theoretically related constructs for nomological validation.
Findings
A 23-item AI capability scale was developed. Nomological testing confirmed that AI capability positively and significantly enhances dynamic capabilities, which in turn boosts organizational creativity and improves organizational performance.
Originality/value
Previous information system literature has not sufficiently addressed the importance of organizational-level complementary resources in developing distinctive capabilities within public organizations. Grounded in resource-based theory and recent AI research, this study provides a framework for public sector organizations to assess their AI capabilities. The findings empirically support the proposed theoretical framework, showing that AI capability increases dynamic capabilities, organizational creativity and performance.
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Francis Dogbe, Muftawu Dzang Alhassan, Raphael Boahen Adomako and Ezekiel Davies
This study aims to explore how government ICT use influences the relationship between ICT access and public sector performance globally. Previous research has mainly focused on…
Abstract
Purpose
This study aims to explore how government ICT use influences the relationship between ICT access and public sector performance globally. Previous research has mainly focused on the impact of ICT access on private firms' performance, measured by profitability. Moreover, previous studies have mostly examined the effect of ICT access on firms' performance within a single country. This study fills a gap in the literature by investigating how government ICT use mediates the connection between ICT access and public sector performance on a global scale.
Design/methodology/approach
The study develops and empirically validates a conceptual model based on the Technology, Organisation-Environment framework and archival data for 131 countries, using partial least squares-structural equation modelling.
Findings
The findings from the study shows a significant relationship between ICT access and Government ICT use. Also, there was positive relationship between ICT access and Public Sector Performance. In addition, there exist a significant relationship between Government use of ICT and Public Sector Performance. Furthermore, the mediating role of government ICT use on the impact of ICT access on public sector performance was significant.
Originality/value
This study is unique in that it explores the relationship between ICT access, government ICT use and public sector performance on a global scale. By using archival sources, this research findings can easily be replicated and applied to a larger population. Additionally, using the TOE framework, this study demonstrates how technology (ICT access) and organisation (government ICT use) impact public sector performance globally.
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Valentin Vasilev, Dimitrina Stefanova and Catalin Popescu
The development puts the problem under consideration in a strategic light and gains attention with its wide comprehensiveness on the plane of unification of the activity of…
Abstract
The development puts the problem under consideration in a strategic light and gains attention with its wide comprehensiveness on the plane of unification of the activity of several modern scientific fields, which have always had intersections, but in their essence perform rather different roles – human resources management (HRM), public relations (PR), and sustainable development (SD). Examining the possibilities of applying innovative approaches in the research of these areas, in the context of the influence of digital and smart technologies and an entirely new scientific field. In this sense, the theoretical substantiation of the thesis on the synergy between HR, PR, and sustainable development is targeted in the aspect of highlighting contemporary challenges and the relevant response to achieve organizational effectiveness, based on knowledge of the impact of digitization processes and their connection with the development of human capital in the organization.
Emphasis in the present work is placed on the relationship between the management of human capital in the organization and the influence of digital and smart technologies on these processes. Focus in the research is placed in three directions – first of all – the role of digital/smart/technologies on sustainable development. Second, the impact of digital and smart technologies on green human resource management is explored, and third, emphasis is placed on the changed role of strategic communications in the context of the digital revolution.
The development brings out some good practices and ideas in the described areas.
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A. Paula Rodriguez Müller, Jaume Martin Bosch and Luca Tangi
This study aims to systematically explore the anticipated realisation of public values through blockchain technology (BCT) within the European public sector. Its purpose is to…
Abstract
Purpose
This study aims to systematically explore the anticipated realisation of public values through blockchain technology (BCT) within the European public sector. Its purpose is to offer a comprehensive analysis of BCT implementations, focusing on the various expected public values and understanding how these expectations shape the adoption of BCT in public administration across Europe.
Design/methodology/approach
This research involves a qualitative analysis of 165 BCT use cases across European governments at the national, regional and local levels. The study employs a public values lens, categorising the expected public values into three clusters: internal, external and relational.
Findings
The results indicate that most cases focus on external transformation, aiming to improve public service provision and enhance citizen satisfaction and engagement by increasing public trust, efficiency, accountability and transparency. For the internal dimension, the results emphasise security, efficiency and cooperativeness as expected public values in adopting BCT. Finally, fewer cases highlight expectations related to relational public values, such as citizen involvement and democratic participation.
Originality/value
This research offers new insights into BCT in the public sector through a public values lens within the European context. It examines the expected public values arising from BCT adoption, providing insights for policymakers and practitioners considering BCT integration in daily operations. This study emphasises the need for further empirical research to explore BCT’s potential in realising these expected public values and to evaluate the trade-offs and disruptive impacts on public administrations.
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Albandari Alshahrani, Anastasia Griva, Denis Dennehy and Matti Mäntymäki
Artificial intelligence (AI) has received much attention due to its promethean-like powers to transform the management and delivery of public sector services. Due to the…
Abstract
Purpose
Artificial intelligence (AI) has received much attention due to its promethean-like powers to transform the management and delivery of public sector services. Due to the proliferation of research articles in this context, research to date is fragmented into research streams based on different types of AI technologies or a specific government function of the public sector (e.g. health, education). The purpose of this study is to synthesize this literature, identify challenges and opportunities, and offer a research agenda that guides future inquiry.
Design/methodology/approach
This paper aggregates this fragmented body of knowledge by conducting a systematic literature review of AI research in public sector organisations in the Chartered Association of Business Schools (CABS)-ranked journals between 2012 and 2023.
Findings
The search strategy resulted in the retrieval of 2,870 papers, of which 61 were identified as primary papers relevant to this research. These primary papers are mapped to the ten classifications of the functions of government as classified by the Organisation for Economic Co-operation and Development (OECD), and the reported challenges and benefits aggregated.
Originality/value
This study advances knowledge by providing a state-of-the-art of AI research based the OECD classifications of government functions, reporting of claimed benefits and challenges and providing a research agenda for future research.
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Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share…
Abstract
Purpose
Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.
Design/methodology/approach
The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.
Findings
Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.
Originality/value
The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.
Objetivo
La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.
Diseño/metodología/enfoque
Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.
Resultados
Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.
Originalidad
El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.
人工智能(AI)为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。
研究方法
本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。
研究发现
研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。
独创性
本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。
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Arne Walter, Kamrul Ahsan and Shams Rahman
Demand planning (DP) is a key element of supply chain management (SCM) and is widely regarded as an important catalyst for improving supply chain performance. Regarding the…
Abstract
Purpose
Demand planning (DP) is a key element of supply chain management (SCM) and is widely regarded as an important catalyst for improving supply chain performance. Regarding the availability of technology to process large amounts of data, artificial intelligence (AI) has received increasing attention in the DP literature in recent years, but there are no reviews of studies on the application of AI in supply chain DP. Given the importance and value of this research area, we aimed to review the current body of knowledge on the application of AI in DP to improve SCM performance.
Design/methodology/approach
Using a systematic literature review approach, we identified 141 peer-reviewed articles and conducted content analysis to examine the body of knowledge on AI in DP in the academic literature published from 2012 to 2023.
Findings
We found that AI in DP is still in its early stages of development. The literature is dominated by modelling studies. We identified three knowledge clusters for AI in DP: AI tools and techniques, AI applications for supply chain functions and the impact of AI on digital SCM. The three knowledge domains are conceptualised in a framework to demonstrate how AI can be deployed in DP to improve SCM performance. However, challenges remain. We identify gaps in the literature that make suggestions for further research in this area.
Originality/value
This study makes a theoretical contribution by identifying the key elements in applying AI in DP for SCM. The proposed conceptual framework can be used to help guide further empirical research and can help companies to implement AI in DP.
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Ahmad A. Khanfar, Reza Kiani Mavi, Mohammad Iranmanesh and Denise Gengatharen
Despite the potential of artificial intelligence (AI) systems to increase revenue, reduce costs and enhance performance, their adoption by organisations has fallen short of…
Abstract
Purpose
Despite the potential of artificial intelligence (AI) systems to increase revenue, reduce costs and enhance performance, their adoption by organisations has fallen short of expectations, leading to unsuccessful implementations. This paper aims to identify and elucidate the factors influencing AI adoption at both the organisational and individual levels. Developing a conceptual model, it contributes to understanding the underlying individual, social, technological, organisational and environmental factors and guides future research in this area.
Design/methodology/approach
The authors have conducted a systematic literature review to synthesise the literature on the determinants of AI adoption. In total, 90 papers published in the field of AI adoption in the organisational context were reviewed to identify a set of factors influencing AI adoption.
Findings
This study categorised the factors influencing AI system adoption into individual, social, organisational, environmental and technological factors. Firm-level factors were found to impact employee behaviour towards AI systems. Further research is needed to understand the effects of these factors on employee perceptions, emotions and behaviours towards new AI systems. These findings led to the proposal of a theory-based model illustrating the relationships between these factors, challenging the assumption of independence between adoption influencers at both the firm and employee levels.
Originality/value
This study is one of the first to synthesise current knowledge on determinants of AI adoption, serving as a theoretical foundation for further research in this emerging field. The adoption model developed integrates key factors from both the firm and individual levels, offering a holistic view of the interconnectedness of various AI adoption factors. This approach challenges the assumption that factors at the firm and individual levels operate independently. Through this study, information systems researchers and practitioners gain a deeper understanding of AI adoption, enhancing their insight into its potential impacts.
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Per Erik Andersson, Katarina Arbin and Christopher Rosenqvist
The main purpose of this study is to enhance knowledge regarding the early stages of planning for and adopting artificial intelligence (AI) in governmental public procurement…
Abstract
Purpose
The main purpose of this study is to enhance knowledge regarding the early stages of planning for and adopting artificial intelligence (AI) in governmental public procurement. While there are numerous studies on AI and procurement in private companies, there is limited information on AI and public procurement.
Design/methodology/approach
The empirical data consists of information obtained from 18 semi-structured interviews with procurement managers and individuals involved in the development of procurement at governmental agencies. Additionally, a workshop was conducted with the respondents to discuss and validate the study’s findings.
Findings
Findings indicate a generally low level of AI maturity in previous research and within the investigated governmental agencies. The perceived benefits of AI primarily revolve around improved operational capabilities, potential for certain process efficiencies and the ability to enhance monitoring through AI. Various challenges related to organizational, process, technological and data management were highlighted. Findings also indicate that perceived benefits and value created by AI can be viewed from a short-term perspective to a long-term perspective.
Social implications
The study provides insights into societal values that can be achieved using AI in public procurement.
Originality/value
This study provides a new perspective on AI in public procurement by focusing on governmental agencies. It explores the perceived benefits, interests and challenges associated with AI implementation in public procurement. Furthermore, this study discusses the potential outcomes of incorporating AI in public procurement and the impact it may have on the values created by the public service, both short- and long term.