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Despite increased interest in the Operator 4.0 concept, there has been scarce attention on practice-oriented frameworks that can assist firms in reaping the potential benefits of technologies within the I4.0 framework. The purpose of this paper is to provide an integrative framework on how to engage Operator 4.0 effectively.

Following meta-synthesis logic and integrative conceptual analysis, this study synthesizes and integrates experimental case studies on Operator 4.0 solutions. The analysis is conducted on 24 cases retrieved from peer-reviewed articles.

The analysis revealed several factors that determine the type and extent of benefits that can be realized within a human-cyber-physical system. However, enhancing these capabilities is not straightforward, as several factors can inhibit the realization of these capabilities. Firstly, the benefits vary depending on the type of Operator 4.0. Secondly, the interoperability of the introduced I4.0 solution with the existing systems is crucial. Thirdly, the adaptability of the solution to serve multiple purposes is crucial, as it tends to increase technology acceptance.

The studies reviewed in this research were based on experimental cases, with limited implementation of the solutions they proposed. As such, their implications when implemented on a larger scale are tentative.

The present study has synthesized existing experimental cases and developed an integrative framework to guide the implementation of Operator 4.0. By gathering primary insights from these experiments, we have clarified when and how Operator 4.0 and the required interactions can lead to successful implementation.

The cyber-physical system (CPS) is a well proven technology for improving system performance, resilience, and interconnectivity. In emerging nations like India, the logistics industry lacks practices connecting logistical equipment with cyberspace. This paper aims to bridge this gap by identifying and evaluating the performance metrics of connectivity solutions. Its goal is to establish an appropriate infrastructure that enables seamless connectivity within the CPS-enabled logistics ecosystem.

A novel integrated decision method is employed to classify the optimal connectivity solution for CPS. It integrates Regret Theory (RT) and Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE-1) method in a Hesitant Fuzzy (HF) environment. This method considers the psychological traits of decision-makers and effectively incorporates their hesitancy for the classification.

The findings highlight security (c10) as the foremost critical performance metric, followed by cost (c6), scalability (c9), traceability (c2) and trustworthiness (c1) to build connective infrastructure for CPS. For extensive coverage scenarios, like freight transportation, cellular connectivity (a2) emerges as the most suitable connectivity solution.

This study provides a roadmap to logistics managers for selecting a suitable connectivity infrastructure to enhance seamless connectivity in logistics operations and processes. Technology providers can utilize the findings to develop the CPS infrastructure for effective freight logistics management.

This research introduces a novel decision-making tool for making choices related to advanced technology assessment. It holds significant value in facilitating well-informed decisions in the digital transformation era.

Augmented reality (AR) and virtual reality (VR) are increasingly recognized among technologies potentially driving the digital innovation of small and medium-sized enterprises (SMEs). Nevertheless, the implications of AR/VR adoption in innovation processes have yet to receive much attention to date, with the need to explore the issues facilitating a systematic implementation in the SME context. This study aims to investigate the possible innovation paths of SMEs as a result of AR/VR adoption.

The authors performed a multiple case study research involving six Italian SMEs in manufacturing and service sectors that are investing in AR and/or VR solutions and are digitally innovating thanks to these technologies.

AR/VR solutions lead to different types of innovation in SMEs, i.e. for innovating product or service offerings, business processes or even the business model, when AR/VR extends to the company business logic. SMEs demonstrate being able to leverage internal sources with the essential commitment of top management and low resistance of employees in all kinds of AR/VR-enabled innovations. Conversely, they involve different external innovation sources according to the type of innovation pursued. Organizational issues emerged as more relevant than technological issues.

Results contribute to the literature on digital transformation of SMEs and provide managerial guidance on innovation sources and organizational issues to be considered to effectively deploy AR/VR solutions into specific innovation paths.

This study explores the impact of emergent technologies in the innovation process along with multiple perspectives, degree of complexity, and strategic importance in the SME context.

Predictive digital twin technology, which amalgamates digital twins (DT), the internet of Things (IoT) and artificial intelligence (AI) for data collection, simulation and predictive purposes, has demonstrated its effectiveness across a wide array of industries. Nonetheless, there is a conspicuous lack of comprehensive research in the built environment domain. This study endeavours to fill this void by exploring and analysing the capabilities of individual technologies to better understand and develop successful integration use cases.

This study uses a mixed literature review approach, which involves using bibliometric techniques as well as thematic and critical assessments of 137 relevant academic papers. Three separate lists were created using the Scopus database, covering AI and IoT, as well as DT, since AI and IoT are crucial in creating predictive DT. Clear criteria were applied to create the three lists, including limiting the results to only Q1 journals and English publications from 2019 to 2023, in order to include the most recent and highest quality publications. The collected data for the three technologies was analysed using the bibliometric package in R Studio.

Findings reveal asymmetric attention to various components of the predictive digital twin’s system. There is a relatively greater body of research on IoT and DT, representing 43 and 47%, respectively. In contrast, direct research on the use of AI for net-zero solutions constitutes only 10%. Similarly, the findings underscore the necessity of integrating these three technologies to develop predictive digital twin solutions for carbon emission prediction.

The results indicate that there is a clear need for more case studies investigating the use of large-scale IoT networks to collect carbon data from buildings and construction sites. Furthermore, the development of advanced and precise AI models is imperative for predicting the production of renewable energy sources and the demand for housing.

This paper makes a significant contribution to the field by providing a strong theoretical foundation. It also serves as a catalyst for future research within this domain. For practitioners and policymakers, this paper offers a reliable point of reference.

The COVID-19 pandemic has affected around 216 countries and territories worldwide and more than 2000 cities in India, alone. The smart cities mission (SCM) in India started in 2015 and 100 smart cities were selected to be initiated with a total project cost of INR 2031.72 billion. Smart city strategies play an important role in implementing the measures adopted by the government such as the issuance of social distancing regulations and other COVID-19 mitigation strategies. However, there is no research reported on the role of smart cities strategies in managing the COVID-19 outbreak in developing countries.

This paper aims to address the research gap in smart cities, technology and healthcare management through a review of the literature and primary data collected using semi-structured interviews.

Each city is unique and has different challenges, the study revealed six key findings on how smart cities in India managed the COVID-19 outbreak. They used: Integrated Command and Control Centres, Artificial Intelligence and Innovative Application-based Solutions, Smart Waste Management Solutions, Smart Healthcare Management, Smart Data Management and Smart Surveillance.

This paper contributes to informing policymakers of key lessons learnt from the management of COVID-19 in developing countries like India from a smart cities’ perspective. This paper draws on the six Cs for the implications directed to leaders and decision-makers to rethink and act on COVID-19. The six Cs are: Crisis management leadership, Credible communication, Collaboration, Creative governance, Capturing knowledge and Capacity building.

The purpose of this paper is to develop a building information modelling (BIM)-based multi-objective optimization (MOO) framework for volumetric analysis of buildings during early design stages. The objective is to optimize volumetric spaces (3D) instead of 2D spaces to enhance space utilization, thermal comfort, constructability and rental value of buildings

The integration of two fundamental concepts – BIM and MOO, forms the basis of proposed framework. In the early design phases of a project, BIM is used to generate precise building volume data. The non-sorting genetic algorithm-II, a MOO algorithm, is then used to optimize extracted volume data from 3D BIM models, considering four objectives: space utilization, thermal comfort, rental value and construction cost. The framework is implemented in context of a school of architecture building project.

The findings of case study demonstrate significant improvements resulting from MOO of building volumes. Space utilization increased by 30%, while thermal comfort improved by 20%, and construction costs were reduced by 10%. Furthermore, rental value of the case study building increased by 33%.

The proposed framework offers practical implications by enabling project teams to generate optimal building floor layouts during early design stages, thereby avoiding late costly changes during construction phase of project.

The integration of BIM and MOO in this study provides a unique approach to optimize building volumes considering multiple factors during early design stages of a project

This study aims to examine the historical development, present state and potential future directions of the integration between building information modeling (BIM) and life cycle assessment (LCA) in the field of construction. Additionally, this paper identifies current problems while offering insight into worldwide BIM research trends.

This study uses text mining on unstructured abstracts, a novel approach not previously documented in BIM research. By conducting a comprehensive systematic assessment of academic literature, this work uses advanced bibliometric approaches to examine the developmental trajectory of the integration of BIM and LCA. The research incorporates co-citation and keyword co-occurrence mapping, providing a complex visual depiction of the interconnectedness of information across different periods.

The results of this analysis reveal the historical development of the integration of BIM and LCA, including its roots and the initial research that established the foundation for further investigations. The aforementioned seminal works signify the inception of the discipline, serving as a source of inspiration for current scholarly investigations. Currently, there is a complex network of interdisciplinary cooperation that can be observed, combining knowledge and perspectives from the fields of design, engineering, construction and sustainability.

This research contributes novelty to the scholarly discourse by offering a holistic and up-to-date panorama of the dynamic BIM and LCA research landscape. It identifies emerging trends, influential contributors and uncharted territories, thus providing a foundation for scholars to contribute meaningfully to the advancement of knowledge in sustainable construction practices.

Despite increasing focus among scholars and practitioners on the design of product-service systems (PSS), there exists no compilation of current knowledge on the role played by small and medium-sized enterprises (SMEs) in designing such systems. Thus, this paper sets out to identify and organise the existing research and suggest questions for future research.

A systematic literature review was performed to identify and provide in-depth details on key themes in the literature addressing the design of PSS in SMEs.

This paper identifies five themes in the literature on the design of PSS in SMEs: motives, challenges, SME characteristics, methods and digitalisation. The themes are interrelated, and SME characteristics seem to be at the core as they are related to all the other themes. Gaps in the current knowledge are identified, and questions for future research are suggested.

The suggestions for future research provide a starting point for expanding the research on PSS design and devising practical support for SMEs.

This article aims to unfold digital servitization by exploring the key resources and resource orchestration (i.e. resource configuration and interaction).

This article conducted an explorative two-stage research strategy of Chinese servitized manufacturers using a preliminary case study and fuzzy-set Qualitative Comparative Analysis (fsQCA) design. The data collection was conducted between 2016 and 2021.

This article identifies five key resources – radical, complex technological resources, complementary, specific market resources and digital resources – and their configurations – leveraging market opportunities, leveraging innovation integration and leveraging resource advantages – to facilitate servitization in the digital age. The findings underscore the interaction between technological and market resources as well as the role of digital resources in promoting the servitization journey.

This article contributes to the understanding of servitization in the digital context by examining the key resources and their interactions involved. It builds upon the configurational logic of servitization, expanding the existing framework in the digital context and highlighting the significance of technological and market resource orchestration and interaction in servitization research. Moreover, the paper contributes through its exploratory two-stage approach, going beyond a conceptual understanding of servitization by focusing on both the factors that enable servitization (WHAT) and the configurations that lead to servitization (HOW). Additionally, the article investigates the attributes of resources as lower-level components, addressing the need to explore the micro-level practice of resource realignment. By providing clarity on the configurations of servitization, the paper offers practical guidelines for practitioners on how to effectively utilize resources and benefit from digital servitization.

Advanced servitization is the process that involves the combination of different services that facilitate both the use of a product and customer operations. Although servitization has emerged as a frequent strategy for manufacturers to differentiate themselves from the competition, its implementation can pose major challenges and may not always result in superior firm performance. Consequently, successful advanced servitization may require specific organizational capabilities to unleash performance-enhancing effects. To date, little is known about how to effectively configure advanced servitization to achieve such performance gains.

Adopting a fit theory perspective and using a configurational approach, we examine the interplay between servitization, organizational capabilities, contextual factors and financial performance. Specifically, we focus on advanced servitization and assess its necessity and sufficiency for achieving high financial performance. In addition, we study how the alignment of servitization approaches with organizational capabilities and contextual factors affects financial performance. We analyze data from 151 manufacturers in an emerging economy using fuzzy-set Qualitative Comparative Analysis (fsQCA).

Our findings indicate that advanced servitization is sufficient, but not necessary for high financial performance. In addition, the findings indicate that the alignment of servitization approaches with specific service-related capabilities unfolds complementarity effects that contribute to achieving high financial performance for manufacturers with different firm size and competitive intensity. The findings indicate three configurations that may serve as templates for managers to orchestrate resource allocation and successfully deploy advanced servitization.

Our study advances the servitization literature by further illuminating advanced servitization as a more complex servitization process. We show how high-performing manufacturers align servitization and organizational capabilities across different contexts, and thus provide design choices for managers in configuring servitization.