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The purpose of this study is to identify factors that are important for logistics organizations from the perspective of manpower readiness for digitization of logistics operations. The study also prioritizes the identified factors and also evaluates the readiness index of manpower for the digitalization of logistics processes.

The factors for manpower readiness are identified through literature review and analysis of a case study. Three major categories of factors are identified. These are organizational, behavioural and technological factors. Under these three major categories of factors, 18 sub-factors are identified. Thereafter, with experts' inputs, the factors are prioritized using Fuzzy analytic hierarchy process (AHP). Further, a case illustration of an Indian logistics company has been taken to understand the current processes, technical capabilities, manpower skills and organization culture. After the case analysis and expert inputs, the manpower readiness index has been evaluated by using graph theory matrix approach (GTMA).

The prioritization of manpower readiness factors has been done using Fuzzy AHP. Organizational factors are found to be the most important factors which require quick attention. Sub-factors that are most important for building competencies in the logistics sector are providing the right training on functional skill development (0.129), top management support and commitment for digitalization (0.117), and organizational culture for process digitalization (0.114), etc. Finally, framework for evaluation of manpower readiness index for logistics operations in the digital age has been illustrated for a case company.

Indian logistics companies can benchmark their readiness index with respect to the best in the industry. Based on the readiness index, logistics companies can analyse their position, gaps from best and worst and can also identify potential areas for improvement.

The novelty of the study lies in the development of a framework for manpower readiness for digitalization in the logistics sector. In literature, this field is very less researched and provides the scope for developing strategies for improving manpower competencies for Industry 4.0. Logistics companies can improve their performance by making their manpower ready based on results obtained for readiness index.

Due to the unprecedented disruptions in business operations, many organisations are turning to Cloud ERP implementation to ensure employees can access real-time business information from anywhere, enabling the continuity of business activities. As a result, over the past decades, literature on Cloud ERP implementation has seen significant growth across different subject areas. This paper aims to present a systematic literature review (SLR) that consolidates the literature scattered across various multidisciplinary subject areas, explores recent developments and identifies knowledge gaps for more impactful future research.

An SLR approach has been applied to a sample of 73 articles published until 1 February 2022.

Our SLR identifies and consolidates a set of critical enablers and barriers to the implementation of Cloud ERP. What is particularly interesting is that this study established a link between these enablers and barriers and four key innovation outcomes: product, service, process and business model innovations. A rigorous framework has been devised that demonstrates the nexus between enablers and barriers to Cloud ERP implementation and innovation outcomes in an organisation. In addition, this study has recognised several organisational theories from information systems literature that have the potential for future research in this emerging area.

This SLR makes several theoretical contributions to the literature on Cloud ERP implementation and its impact on innovation outcomes.

The review consolidates a wide range of literature to provide decision-makers with an integrated understanding of the most influential factors in Cloud ERP implementation.

SLR provides a comprehensive analysis of the current state of research on the topic, offering unique perspectives on developments in theory and knowledge gaps, as well as identifying future research opportunities in the area.

Today many firms are pushed towards digitalization to ensure business continuity and their survival due to COVID-19. Therefore, this study aims to investigate the emerging knowledge management models in the era of digitalization and disruption.

The authors have adopted a semi-structured approach composed of qualitative data collection from 37 business executives from India representing different industry sectors. The authors adopted a three-layer coding process (axial, open and selective) to develop a framework grounded in organizational information processing theory.

Scanning the business environment leads to understand the status of current and potential business through intelligence of information, whereas better planning and execution can be achieved through employing and using the information intelligently that fits to the overall and strategic objective of the business. Overall, the business continuity can be obtained by information prosperity across the business by engaging diverse stakeholders. According to the findings, these aspects lead to the effective implementation of digital knowledge to ensure business continuity in uncertain business environment.

The study offers the insights for managing and executing the knowledge in digital platforms, where they can think of developing a system architecture on the basis of degree of uncertainty and information processing requirements for combining the knowledge.

The present study is unique, where it offers the meaningful visions to the designers and users of virtual knowledge management systems.

The success of SMEs' financial and market performance (MAP) depends on the firms' level of blockchain technology adoption (BCA) and identifying the crucial antecedents that influence SMEs' adoption. Therefore, this research attempts to develop an integrated model to understand and predict the determinants of BCA and its effect on SMEs' performance. The purpose of this paper is to address this issue.

The theoretical foundations are the technology–organization –environment (TOE) framework and the resource-based view (RBV) perspective. The authors distributed a survey to SMEs in South Africa and received 311 responses. The covariance-based structural equation modeling (CB-SEM) followed by the artificial neural network (ANN) technique was used for the data analysis.

The SEM results showed that SMEs' relative advantage, compatibility, top management support (TMS), organizational readiness (ORD), competitive pressures (COP), external support, regulations and legislation significantly influence SMEs' BCA. However, complexity negatively impacts SMEs' BCA. The analysis results also revealed that SMEs' BCA significantly influences the financial performance of the firms, followed by MAP. Furthermore, model determinants were input to an ANN modeling. The ANN results showed that TMS is the most critical predictor of SMEs' BCA, followed by ORD, COP, external support, and regulations and legislation.

The results provide valuable information for SMEs when maneuvering their adoption strategies in the scope of blockchain technology. Additionally, from the perspective of an emerging market, the study has successfully contributed the TOE framework and the RBV.

This study is the first work to explore the determinants of BCA in the context of SMEs from a developing country. This paper is also one pioneer in attempts to develop a causal and predictive statistical model for predicting the determinants of BCA in SMEs' performance.

Health-care knowledge is dispersed among different departments in a health care organization, which makes it difficult at times to provide quality care services to patients. Therefore, this study aims to identify the main challenges in adopting health information technology (HIT).

This study surveyed 148 stakeholders in 4 key categories [patients, health-care providers, United Arab Emirates (UAE) citizens and foresight experts] to identify the challenges they face in adopting health care technologies. Responses were analyzed using exploratory (EFA) and confirmatory factor analysis (CFA).

EFA revealed four key latent factors predicting resistance to HIT adoption, namely, organizational strategy (ORGS); technical barriers; readiness for big data and the internet of things (IoT); and orientation (ORI). ORGS accounted for the greatest amount of variance. CFA indicated that readiness for big data and the IoT was only moderately correlated with HIT adoption, but the other three factors were strongly correlated. Specific items relating to cost, the effectiveness and usability of the technology and the organization were strongly correlated with HIT adoption. These results indicate that, in addition to financial considerations, effective HIT adoption requires ensuring that technologies will be easy to implement to ensure their long-term use.

The results indicate that readiness for big data and the IoT-related infrastructure poses a challenge to HIT adoption in the UAE context. Respondents believed that the infrastructure of big data can be helpful in more efficiently storing and sharing health-care information. On the technological side, respondents felt that they may experience a steep learning curve. Regarding ORI, stakeholders expected many more such initiatives from health-care providers to make it more knowledge-specific and proactive.

This study has implications for knowledge management in the health -care sector for information technologies. The HIT can help firms in creating a knowledge eco-system, which is not possible in a dispersed knowledge environment. The utilization of the knowledge base that emerged from the practices and data can help the health care sector to set new standards of information flow and other clinical services such as monitoring the self-health condition. The HIT can further influence the actions of the pharmaceutical and medical device industry.

This paper highlights the challenges in HIT adoption and the most prominent factors. The conceptual model was empirically tested after the collection of primary data from the UAE using stakeholder theory.

Technological developments have made it possible for organizations to use enterprise resource planning (ERP) services without indulging in heavy investments like IT infrastructure, trained manpower for implementation and maintenance and updating the systems regularly to maintain business competitiveness. Plug and play model offered by cloud ERP has led to a constant creation of large data sets which are structured, semi-structured and unstructured by nature. Thus, there has been a need to analyze such complex data sets and the purpose of this paper is to focus on how cloud ERP and big data predictive analytics (BDPA) will impact the performance of a firm.

A dynamic capability view (DCV) theory-based model was developed and the authors have collected data by using an online questionnaire from India. Thereafter, the authors have analyzed it by employing structural equation modeling.

SEM analysis of 231 respondents showcases that the use of DCV theory to define the relationships of cloud ERP and BDPA has been the right move. Out of the 13 hypotheses empirically tested, only 7 hypotheses were supported by the data.

The study showcases cross-sectional data from India. It would be interesting for this study to see if the country-level differences would influence these relationships between cloud ERP and financial performance, BDPA and financial performance and cloud ERP and BDPA.

This study empirically tests the relationship of cloud ERP and BDPA through a model based on DCV theory.

This study aims to propose a collaborative knowledge-based ontological research model for designing a collaborative product development process (PDP) while considering different design for X techniques.

This study follows a thematic literature analysis to identify the key design concepts needed to assess environmental, service, safety, manufacture and assembly, supply chain and quality concerns in developing a collaborative PDP.

The proposed model provides a guide for methodology, engineering and ontology evaluation metrics (verification, assessment and validation). The findings benefit both practitioners and managers because they address the key knowledge taxonomy needed to assist them in storing information, promoting teamwork and making decisions in a collaborative PDP while incorporating various design for X approaches and product life cycles.

This study introduces a novel knowledge-based collaborative ontological research model, which is specifically designed to tackle the challenges of developing collaborative products in the contemporary landscape. The model presents a significant and valuable contribution to the field by introducing an ontological approach for acquiring, representing and leveraging knowledge in a computer-interpretable format to support the design of collaborative products. In addition, it provides a comprehensive guide for evaluating the effectiveness and efficacy of the ontology developed.

The purpose of this study is to disclose ontology of DSI as a novel concept in servitization community, explore the research context and themes (i.e. technological and industrial sectors) where DSI emerges, unveil methodological complexities of the research on digital servitization and DSI and provide guidelines for future research avenues regarding DSI.

Bearing in mind the relative novelty of DSI as a concept in servitization literature, the authors adopted a systematic literature review approach to identify 111 peer-reviewed articles published in English language and available in business and management disciplines via scholar databases (Scopus). The analysis of literature discloses descriptive and thematic insights regarding digital servitization and DSI.

The study provides valuable insights from the descriptive and thematic analyses where classification of articles per publication year, citations, methodology/type of the paper, geographical location of data collection, as well as industrial sector and technological contexts are discussed. Moreover, the unique value of this study is observed through its specific focus on the characteristics of DSI-related literature.

The study is among the first of its kind to provide extensive descriptive and thematic insights on the available literature dealing with digital servitization and DSI, mapping out prior research across a wide spectrum of publication outlets and illustrating the chronological evolution of research on digital servitization and DSI.

The hospitality industry has witnessed numerous changes to enhance the stay experience of guests. To offer a memorable stay experience, the industry has started deploying intelligent robots. Therefore, this case study aims to examine and explore artificial intelligence (AI) enabled robots in hospitality industry in order to enhance guest experience in a smart city.

Semistructured interviews have been conducted at Novotel Ambassador Seoul Dongdaemun Hotels and Residences, Seoul, South Korea, to understand the stay experience of guests regarding services offered by AI enabled robots. The authors have selected employees for interviews since employees listen and witness the guest experience directly. Out of 214 employees in the hotel with varied experience and background, 26 interviews are conducted.

Through a systematic approach of coding, the authors have identified that deploying AI enabled robots facilitates the automation, information gathering, personalization and seamless service in the hospitality industry of a smart city. Further, with a back-and-forth mapping mechanism based on epistemological principles, the authors made four propositions that lead to the development of a research framework.

The practicing managers of hospitality industry can employ AI enabled robots within the scope of improving and automating the processes that can also offer increased personalization to enhance the stay experience, which is expected in a smart city.

The study offers a unique contribution to literature, since it is a live case study, and the information is from the practicing employees of a well-known organization in a hospitality sector from a smart city (Novotel Ambassador Seoul Dongdaemun Hotels and Residences, Seoul, South Korea).