Recent Submissions

  • Social sustainability performance: developing and validating measures in the context of emerging African economies

    Denu, Mathias Kofi; Bentley, Yongmei; Duan, Yanqing; ; University of Bedfordshire; Ho Technical University, Ghana (Elsevier, 2023-05-04)
    Social sustainability has attracted growing research interest. However, studies on social sustainability in emerging African economies are still in their early stages. This study found that companies in these countries are keen to improve their social sustainability, but they often lack an adequate understanding of measuring their company's social sustainability performance (SSP). This study addresses this knowledge gap by identifying the SSP measures relevant to emerging African economies. The study adopts a mixed research method involving several stages. First, fifty initial SSP evaluation measures across eight dimensions were identified based on an extensive literature review and interviews. Second, these measures were examined in a pilot survey followed by a formal survey with senior managers and business owners of 110 companies in Ghana's manufacturing and service industries. A total of 369 valid responses were received. Based on the statistical analysis of exploratory and confirmatory factor analysis, 26 specific measures of SSP were established. These measures cover seven broad dimensions: community, equity, poverty alleviation, human rights, ethics, regulatory enforcement, and employees. The validated multidimensional measures provide valuable guidance to managers on evaluating and improving their organisation's social sustainability performance.
  • Impact of video-based learning in business statistics: a longitudinal study

    Lewis, Naowarat; Lewis, Rhidian; Luca, Cristina; Anglia Ruskin University; University of Bedfordshire (Springer Nature, 2023-04-06)
    Many undergraduate business students in the United Kingdom (UK) find themselves during the initial stages of their degree programmes required to study numerical subjects which, for many, have not been encountered since completing compulsory education. This paper considers the utilisation of a technology-based approach in order to support first year undergraduate students engage with and achieve in the business numeracy subject area. The purpose of this paper is providing background introduction to new pedagogy through the use of technology. Through a longitudinal study conducted within a modern university in the UK over a 11-year period (2006-2017), this paper qualifies the impact of a Video Based Learning (VBL) approach on the achievement profiles of first year undergraduate students within a modern business school. Results indicate that the use of a VBL approach such as that adopted within this study supports not only improvement in the number of students gaining an overall pass, but also an overall improvement amongst higher achieving students within business numeracy. Findings also demonstrate those characteristics of a VBL approach that support continuation of student engagement with the subject matter throughout their studies. Whilst the findings offer a range of benefits to both students and educators in enhancing student achievement, this finding served the purpose of introductory of the new learning model within the next researches.
  • Application of sensor data based predictive maintenance and artificial neural networks to enable Industry 4.0

    Fordal, Jon Martin; Schjolberg, Per; Helgetun, Hallvard; Skjermo, Tor Øistein; Wang, Yi; Wang, Chen; Norwegian University of Science & Technology; El Watch AS; University of Bedfordshire; Hubei University of Automotive Technology (Springer, 2023-03-04)
    Possessing an efficient production line relies heavily on the availability of the production equipment. Thus, to ensure that the required function for critical equipment is in compliance, and unplanned downtime is minimized, succeeding with the field of maintenance is essential for industrialists. With the emergence of advanced manufacturing processes, incorporating predictive maintenance capabilities is seen as a necessity. Another field of interest is how modern value chains can support the maintenance function in a company. Accessibility to data from processes, equipment and products have increased significantly with the introduction of sensors and Industry 4.0 technologies. However, how to gather and utilize these data for enabling improved decision making within maintenance and value chain is still a challenge. Thus, the aim of this paper is to investigate on how maintenance and value chain data can collectively be used to improve value chain performance through prediction. The research approach includes both theoretical testing and industrial testing. The paper presents a novel concept for a predictive maintenance platform, and an artificial neural network (ANN) model with sensor data input. Further, a case of a company that has chosen to apply the platform, with the implications and determinants of this decision, is also provided. Results show that the platform can be used as an entry-level solution to enable Industry 4.0 and sensor data based predictive maintenance.
  • Ducks, elephants and sharks: using LEGO® Serious Play® to surface the ‘hidden curriculum’ of equality, diversity and inclusion

    Schwabenland, Christina; Kofinas, Alexander K.; University of Bedfordshire (Sage, 2023-03-20)
    Despite widespread agreement on the importance of preparing management students for working in diverse organizations there is evidence (Perriton, Elliott and Humbert 2021; Perriton and Elliot 2018) that this is often ignored or marginalised in formal curricula. Our article draws on the concept of the hidden curriculum to present the results of a project in which business school academics and support staff explored the ‘unthought knowns’ (Bollas 2017: xix) that influence how equality, diversity and inclusion are, or are not, engaged with in the classroom. Our data were generated during workshops using the LEGO® Serious Play® methodology in which participants built LEGO® models to develop their own understandings of equality, diversity and inclusion. The models, and the discussions about them, uncovered complexities and contradictions inherent within these topics, alongside significant levels of anxiety and fear. Our study makes two contributions; firstly through the animal metaphors that featured in the models, we identify some of the anxieties that are generated by these topics which are likely to influence the hidden curriculum. Secondly, our innovative use of LEGO® Serious Play® contains important implications about the actual mechanism through which such insights can be ‘surfaced’ so that they become available for reflection and thought.
  • “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

    Dwivedi, Yogesh K.; Kshetri, Nir; Hughes, Laurie; Slade, Emma Louise; Jeyaraj, Anand; Kar, Arpan Kumar; Baabdullah, Abdullah M.; Koohang, Alex; Raghavan, Vishnupriya; Ahuja, Manju; et al. (Elsevier, 2023-03-11)
    Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts.
  • A comprehensive review on food waste reduction based on IoT and Big Data technologies

    Ahmadzadeh, Sahar; Ajmal, Tahmina; Ramanathan, Ramakrishnan; Duan, Yanqing; University of Bedfordshire; University of Essex (MDPI, 2023-02-14)
    Food waste reduction, as a major application area of the Internet of Things (IoT) and big data technologies, has become one of the most pressing issues. In recent years, there has been an unprecedented increase in food waste, which has had a negative impact on economic growth in many countries. Food waste has also caused serious environmental problems. Agricultural production, post-harvest handling, and storage, as well as food processing, distribution, and consumption, can all lead to food wastage. This wastage is primarily caused by inefficiencies in the food supply chain and a lack of information at each stage of the food cycle. In order to minimize such effects, the Internet of Things, big data-based systems, and various management models are used to reduce food waste in food supply chains. This paper provides a comprehensive review of IoT and big data-based food waste management models, algorithms, and technologies with the aim of improving resource efficiency and highlights the key challenges and opportunities for future research.
  • Motivations and challenges for food companies in using IoT sensors for reducing food waste: some insights and a road map for the future

    Ramanathan, Ramakrishnan; Duan, Yanqing; Ajmal, Tahmina; Pelc, Katarzyna; Gillespie, James; Ahmadzadeh, Sahar; Condell, Joan; Hermens, Imke; Ramanathan, Usha; University of Essex; et al. (MDPI, 2023-01-15)
    Food waste is a serious problem worldwide, including in Europe. Research efforts are being carried out to reduce food waste. In this paper, we focus on using modern digital technologies (also known as Industry 4.0 technologies) to reduce waste in food supply chains. Based on interactions with a number of food companies in Europe over the last four years using Action Research, we provide new insights on the motivations and challenges for food companies when they are engaged in the use of technologies for reducing food waste in their supply chains. Motivations for firms include improved food quality of their produce, improved reliability, support in meeting legal requirements, a green image, and improved revenues from selling the food that has been saved. However, data security issues and trust issues posed challenges in using these technologies. Since this is an emerging area of research, we look at potential business models for technology companies for working with food companies in reducing food waste, identify value propositions and value capture, and look at how these investments in technologies can improve the sustainability of food businesses. We believe technology companies can leverage the opportunities, develop new business models with value propositions around the use of technologies, and support food companies via timely alerts in case of potential quality issues. Value capture occurs via the sale of hardware and subscriptions.
  • Using IoT sensor technologies to reduce easte and improve sustainability in artisanal fish farming in southern Brazil

    Ramanathan, Ramakrishnan; Duan, Yanqing; Valverde, Joaquim Manoel Monteiro; Van Ransbeeck, Samuel; Ajmal, Tahmina; Valverde, Silma Battezzati; University of Essex; University of Bedfordshire; Instituto Federal de Educação, Ciência e Tecnologia Catarinense; Universidade Federal do Paraná (MDPI, 2023-01-21)
    Modern digital technologies have the great potential to improve the sustainability of fish farming in artisanal fisheries. However, in spite of the popularity of these technologies for fish farming in other parts of the world, Brazil still lags behind. To fill this gap, this study has conducted the first field study in implementing the IoT sensor technologies in Southern Brazil and documents the experiences in this paper. More specifically, it discusses developing sustainable artisanal fisheries infrastructure using these technologies with reference to southern Brazil, where the study explores the use of sensor technology in aquaculture and its effectiveness in reducing waste and improving productivity. The overarching goal of the project is to demonstrate how simple data collection using IoT sensors and its analysis can support artisanal freshwater fish farms in Brazil and beyond to increase production, reduce waste, and thereby improve their sustainability. The pilot implementation of these technologies has demonstrated the potential of increasing the productivity of the artisanal fisheries, reducing waste (e.g., loss of farmed fish, optimised feeding to reduce waste of feeds), and improving the sustainability of aquaculture. This paper documents the valuable firsthand experiences of selecting, adapting, and implementing the IoT sensor technologies with close cooperation from local research institutions and artisanal fish farmers. The paper describes the different implementation stages and use interviews with stakeholders as a testimony of the effectiveness of the IoT technology adoption.
  • An organisational-life cycle assessment approach for Internet of Things technologies implementation in a human milk bank

    da Costa, Tamíris; Gillespie, James; Pelc, Katarzyna; Shenker, Natalie; Weaver, Gillian; Ramanathan, Ramakrishnan; Murphy, Fionnuala; University College Dublin; Ulster University; University of Bedfordshire; et al. (MDPI, 2023-01-06)
    Human milk banks (HMB) are responsible for screening and recruiting milk donors with surplus milk to their own infant’s needs, followed by transporting, heat-treating (pasteurising) and microbiologically confirming the donor human milk (DHM) is safe to issue to vulnerable infants. Maintaining the safety and quality of DHM are vital requirements in HMB operations. DHM must be maintained in ideal temperature conditions throughout the whole period—from expression until delivery. In this regard, monitoring technologies (e.g., sensors, Big Data and the Internet of Things) have become a viable solution to avoid food loss, allowing prompt corrective action. Therefore, this study aimed to understand the trade-offs between optimising DHM transportation and the environmental impact of implementing such technologies. The environmental performance was carried out through an Organisational Life Cycle Assessment (O-LCA). The electricity consumed during milk storage is the main driver for the environmental impacts in this organisation, responsible for up to 82% of the impacts in ionising radiation. The transportation stage and the treatment of discarded DHM were also relevant for ozone formation and marine eutrophication, respectively. Considering the strategy to integrate monitoring technologies to control the temperature conditions during transportation and the reduction of milk discarded by 3%, an environmental impact reduction can be also observed. In some categories, such as global warming, it could avoid around 863 kg of CO2-eq per year. The sensitivity analysis showed that the impacts of the HMB depend highly on the transport distance. In addition, changing the transportation mode from motorcycles to drones or electric vehicles can affect the environmental performance of this organisation. Therefore, human milk transport logistics must be studied in a multidisciplinary way to encompass all possible impacts of these strategies.
  • Life cycle assessment tool for food supply chain environmental evaluation

    da Costa, Tamíris; Gillespie, James; Pelc, Katarzyna; Adefisan, Abi; Adefisan, Michael; Ramanathan, Ramakrishnan; Murphy, Fionnuala; University College Dublin; Ulster University; University of Bedfordshire; et al. (MDPI, 2022-12-31)
    Food is at the centre of efforts to combat climate change, reduce water stress, pollution, and conserve the world’s wildlife. Assessing the environmental performance of food companies is essential to provide a comprehensive view of the production processes and gain insight into improvement options, but such a tool is currently non-existent in the literature. This study proposed a tool based on the life cycle assessment methodology focused on six stages of the food chain, raw materials acquisition, supplier, manufacturing, distribution, retail and wastes. The user can also evaluate the implementation of Internet of Things (IoT) technologies to reduce food waste applied in the real-world problems. The tool was validated through a case study of a food manufacturing company that prepares frozen meals via vending machines. The LCA results provided by the tool showed that food raw materials production is the main hotspot of nine impact categories. The IoT technologies’ contribution increased the company’s impact by around 0.4%. However, it is expected that employing these monitoring technologies would prevent food waste generation and the associated environmental impacts. Therefore, the results of this paper provide evidence that the proposed tool is suitable for determining environmental impacts and savings of food supply chain companies.
  • A case study of human milk banking with focus on the role of IoT sensor technology

    Ramanathan, Usha; Pelc, Katarzyna; da Costa, Tamíris; Ramanathan, Ramakrishnan; Shenker, Natalie; Nottingham Trent University; University of Bedfordshire; University College Dublin; University of Essex; Imperial College London; et al. (MDPI, 2022-12-23)
    Human milk is the biological norm for newborn nutrition, with breast milk from the mother being recognized as the best source of nutrition for infant health. When the mother’s milk is unavailable, donor human milk is the best alternative for infants with low birthweights. Growing recognition of the benefits of donor human milk has led to increasing global interest in monitoring and controlling human milk’s quality to fulfil the need for donor human milk. In response to this need, the REAMIT project proposed to adapt and apply existing innovative technology to continuously monitor and record human milk quality and signal potential milk quality issues. IoT sensors and big data technology have been used to monitor conditions that may increase spoilage (such as temperature and humidity) in the transportation stage. The sensors were installed in the insulated bags used to transport the milk from the donor’s home or hospital to the human milk bank and vice versa. The temperature and humidity were collected every 30 min, whilst the GPS locator sent data every 2 min. The data are collected in the cloud using GPRS/CAT-M1 technology. An algorithm was designed to send alerts when the milk temperature is above the prespecified threshold specified by the organisation, i.e., above −20 °C. The experience showed evidence that IoT sensors can efficiently be used to monitor and maintain quality in supply chains of high-quality human milk. This rare product needs a high level of quality control, which is possible with the support of smart technologies. The IoT technology used can help the human milk supply chain in five different aspects, namely by reducing waste, assuring quality, improving availability, reducing cost and improving sustainability. This system could be extended to various supply chains of rare and precious commodities, including further medical supplies such as human blood and organs, to completely avoid waste and ensure total quality in supply chains.
  • Leaders, CSR and the role of religion in decision-making processes in Middle Eastern organisations

    Koleva, Petya Milhaylova; Ocler, Rodolphe; Saylors, Rohny G. (Academy of Management, 2018-07-09)
    Despite numerous publications on the role of religion on individual and organisational ethical behaviour, academic literature seems to lack a comprehensive understanding of how religion affects the decision- making of leaders and ethical behaviour of organisations. This gap seems to be even more significant with regard to developing countries and was addressed in the present study by conducting twenty-two interviews with leaders from the public and private sectors of three Middle Eastern countries. The study used Grounded Theory approach for data analysis which identified how Islamic moral postulates and ethics impact on leaders’ ethical behaviour, decision-making and consequently translate to organisational CSR behaviour. With this study, we contribute to the CSR literature by providing empirical evidence on how the repetitive interactions of social actors with religious affiliations create behavioural expectations which, when repeated and consequently internalized, become a constituent part of leaders’ identity and shape how they interact with the surrounding environment.
  • Using constructivist grounded theory to construct a substantive theory for corporate social responsibility

    Koleva, Petya Milhaylova; Ocler, Rodolphe (Springer International Publishing, 2018-01-24)
    Grounded Theory strategy (GT) has been introduced almost 50 years ago as the approach developed significantly since that time and contributed to emergence of variety of GT strategies. One of these variations is the constructive turn of Kathy Charmaz. In this paper we demonstrate (1) the potential of Constructive Grounded Theory (CGT) into scientific inquiry on CSR and (2) how the approach was implemented in order to build a substantive theory for CSR by utilising a practical example from a recently completed doctoral study by the lead author.
  • Chapitre 107. Lever le voile d’une illusion managériale par l’apport du "SIOFHIS" (Système d’Informations Opérationnelles et Fonctionnelles Humainement Intégrées et stimulantes)

    Delattre, Miguel; Ocler, Rodolphe ({EMS} Editions, 2021-01-12)
    Organisation et information sont indissociables en sciences de gestion, pour autant, le manque d’explicitation des hypothèses mobilisées conduit parfois à entretenir un flou sur la nature du lien concernant leur rapprochement ainsi que des biais de représentations pour la prise de décisions. La notion de Système d’informations opérationnelles et fonctionnelles humainement intégrées et stimulantes propose une perspective féconde pour ne pas céder à la facilité d’un discours managérial trop normatif.
  • Understanding business model development through the lens of complexity theory: enablers and barriers

    Vatankhah, Sanaz; Bamshad, Vahideh; Altinay, Levent; De Vita, Glauco; University of Bedfordshire; University of Tehran; Oxford Brookes University; Coventry University (Elsevier, 2022-11-02)
    A winning business model is the key to business success in today’s fragmented market environment. However, businesses need to develop their business models over time to meet the requirements of environmental uncertainties and shifts surrounding the business. Drawing on complexity theory and its related concept of hierarchy, this study advances a systematic approach to theoretically investigate the factors that favourably or adversely affect business model development (BMD), in a hierarchical order. In particular, multiple fuzzy multicriteria decision making techniques were applied to develop the list of enablers of and barriers to BMD, to determine the priorities among enablers, and to determine the significance of barriers with respect to the main enablers of BMD. The results reveal that organizational form is the most salient enablers of BMD, while type II barriers are the most significant barriers, challenging the development of business models. Implications and future research directions are also provided.
  • Assessing the application of multi-criteria decision making techniques in hospitality and tourism research: a bibliometric study

    Vatankhah, Sanaz; Darvishmotevali, M.; Rahimi, R.; Jamali, S.M.; Ale Ebrahim, N.; (Emerald, 2023-01-04)
    Purpose: Multi-criteria decision-making (MCDM) techniques are decision support systems that provide systematic approaches to solve hospitality and tourism (H&T) problems while minimizing the risk of failure. However, less is known about the application of MCDM techniques in H&T research. This study aims to systematically assess the use of MCDM techniques in H&T research to classify its current application and determine its application potential for H&T research. Design/methodology/approach: This study used bibliometric analysis to examine all published MCDM studies focused on H&T industries, since 1997. In addition, topic modelling was used to discover key concepts. Finally, top cited studies in terms of total citations per year and total citations were qualitatively reviewed for more insights. Findings: The findings revealed an ongoing interest in applying MCDM techniques in H&T research. Specifically, the extension of fuzzy theory in MCDM techniques is burgeoning among H&T researchers. However, a certain number of MCDM techniques seem to be ignored in this field with a repetitive application of MCDM techniques in particular areas. Research limitations/implications: The data for the current research was solely retrieved from Scopus and other databases were not included. Therefore, future research is called for to re-examine the study by considering data from various databases. Originality/value: This study contributes to extant H&T literature by a) identifying the most prolific and influential countries, journals, publications, and trends by applying MCDM techniques in H&T research, and b) elucidating the implications and characteristics of MCDM techniques in H&T research.
  • Understanding factors affecting the managers' perception of AI applications in information processing

    Duan, Yanqing; Cao, Guangming; Xu, Mark; Ong, Vincent Koon; Dietzmann, Christian; University of Bedfordshire; Ajman University; Portsmouth University; Regents University London; University of Leipzig (Acad Conferences Ltd, 2021-12-31)
    Artificial Intelligence (AI) bears great potential in supporting and/or replacing managers' information processing activities, but the benefits of AI can only be realized if the organisational managers are willing to use AI for information processing. The academic literature contains very limited theoretical and empirical research focusing on understanding the acceptance and applications of AI in manager's personal information processing. To address this knowledge gap, this workin- progress paper aims to develop a conceptual framework on factors affecting the managers' perceived roles of AI in their information processing and their intention to use AI. Underpinned by the relevant theories of information processing, the research framework can be used to examine if and to what extent the situational, personal, and performative factors of information systems (IS) influence the managers' perception of AI-based applications in terms of preferred human-AI collaboration modes and levels of AI input in information processing activities. The proposed framework offers a theoretical understanding and development of AI-based applications in the context of information processing from an end user's perspective.
  • EPPR: blockchain for educational record sharing and recommendation using the Ethereum platform

    Alkouz, Akram; HajYasien, Ahmed; Alarabeyyat, Abdulsalam; Samara, Khalid; Al-Saleh, Mohammed; Higher Colleges of Technology; Al-Balqa' Applied University; Jordan University of Science and Technology (Inderscience, 2021-09-24)
    There has been a great deal of discussion of the challenges on privacy of Educational Professional Personal Record (EPPR). Therefore, it is required to reassess the current models, in which various parties generate, exchange and observe a huge amount of personal data with regard to EPPR. Ethereum blockchain has shown that trusted, auditable transactions are detectible using a decentralised network of nodes. In this paper, we propose a novel decentralised framework to manage EPPR using Ethereum blockchain. The framework provides the owner of the EPPR a comprehensive immutable log and accessibility to their educational records across the educational record editors and consumers. Furthermore, it provides a recommender engine to endorse skills and competencies to the education record owners and similar candidates for educational records editors and consumers. The aim of the proposed framework is to enable educational stakeholders to participate in the network as blockchain miners rewarded by pseudonymised data.
  • Micro-foundations as a grounding for readiness-for change in knowledge sharing initiatives

    Samara, Khalid; Al Serhan, Omar (Inderscience, 2021-11-17)
    While many organisations are often engaged in conventional change practices that usually involve top-down strategies for creating change, knowledge sharing initiatives differ where most of the complex processes are handled at the human-level. Therefore, knowledge sharing initiatives present a unique type of conundrum where there is a need to closely interconnect human behaviours and the person's readiness to identify the most effective approaches to achieve change. This paper investigates the individual level readiness-for change by studying organisational knowledge sharing initiatives from a micro-foundational perspective. These issues have been largely missing in the knowledge sharing literature which is integral to understanding of how to manage individuals at the micro-level who are experiencing a behavioural change as result of knowledge sharing initiatives. In this study an inductive grounded theory approach is being used to analyse the individuals' level experiences and origins of various influential factors supporting or inhibiting their readiness during knowledge sharing initiatives. The results indicate that asymmetries in communication and lack of awareness to knowledge sharing initiatives are fundamentally constructs akin to micro-level behaviours that have obvious effects on the individuals' readiness-for change.
  • Readiness as a microfoundational approach to knowledge-management

    Samara, Khalid; London South Bank University (2013-03-31)
    Over the years, many theories have noted that the core factor that acts as a barrier to successful knowledge management (KM) initiatives is attributable, in part, to the individual’s lack of readiness to change. However, a significant gap in the literature is the lack of empirical and conceptual support to the idea that KM is inherently a change effort affecting issues of how to enact change in individuals. More recent work, have highlighted that one of the reasons for this gap in the knowledge literature, is that majority of studies as a whole are usually pre-occupied with macro-level constructs stemming from forces at the organizational level. The study argues that readiness-for change is an important step towards understanding the micro processes of individual actions and interactions, because research in this area examines how change occurs from the individual’s perspective. Based on the literature, the paper presents a model to help us explore the micro processes of organizational KM initiatives. The study also builds on previous work of Foss (2007) explanation of microfoundations and integrates it with insights of Armenakis and Harris (2002) theory of readiness for individual change. A discussion is presented demonstrating future directions towards a microfoundational approach to KM.

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