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This article aims at - exploring and prioritizing the barriers to adoption of digitization in supply chains (SCs), categorizing them into sustainability triple bottom line (STBL) based upon their direct impact and suggesting digital technologies to address each barrier.

A five-phase methodology is used which consists of an exploration of 44 barriers to the adoption of digitization in SCs, analysis of 44 barriers for mean, standard deviation and Cronbach alpha based on questionnaire-based feedback of 25 experts, extraction of 10 most significant barriers through 05 experts, followed by categorization of the barriers into STBL referring to their direct impact on STBL, prioritization of ten barriers using Fuzzy Technique for Order Performance by Similarity to Ideal Solution and recommendation of digital technologies to address each barrier.

While all the barriers considered in this study significantly impede the adoption of digitization in SCs, lack of top management commitment (B1) is found to be most crucial while lack of culture toward use of information and communication technology required for digitization (B3) has minimum impact. Large investment in digital infrastructure (B6), difficulty in integration of cyber physical systems (CPSs) on varied platforms (B8) and lack of experts having knowledge of digital technologies (B2) are equally important barriers requiring more attention while adopting digitization in SCs.

This study is mainly based on feedback from 25 seasoned experts; a wider cross section of experts will give more insight.

The outcomes are very significant for organizations looking to adopt digitization in their SCs. Simultaneous consideration to all the barriers becomes impractical hence prioritization of same will be useful for the SC managers to benchmark their preparedness and decide strategies for the adoption of digitization with due consideration toward the impact of barriers on STBL. The digital technologies recommended will further aid in planning the digital strategies to address each barrier.

A unique approach to explore, analyze, prioritize and categorize the barriers to adoption of digitization in SCs is used to provide a deeper understanding of factors deterring the same. It implies that a supportive top management along with systematic allocation of finances plays a crucial role. The importance of availability of digital experts for integrating CPSs on a single platform is also highlighted. The digital technologies recommended will further assist the organizations toward adoption of digitization in SCs with due consideration to STBL.

Building information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative digital representation of built environment data. Competitive advantage can be achieved with collaborative project delivery and rich information modelling. Despite the abundant benefits, BIM’s adoption in the AEC is susceptible to confrontation. A substantial impediment to BIM adoption often cited is data interoperability. Other facets of interoperability got limited attention. Other academic areas, including information systems, discuss the interoperability construct ahead of data interoperability. These interoperability factors have yet to be surveyed in the AEC industry. This study aims to investigate the effect of interoperability factors on BIM adoption and develop a comprehensive BIM adoption model.

The theoretical foundations of the proposed model are based on the European interoperability framework (EIF) and technology, organization, environment framework (TOE). Quantitative data collection from construction firms is gathered. The model has been thoroughly examined and validated using partial least squares structural equation modelling in SmartPLS software.

The study’s findings indicate that relative advantage, top management support, government support, organizational readiness and regulation support are determinants of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, organizational interoperability and uncertainty are barriers to BIM adoption. However, compatibility, competitive pressure and legal interoperability do not affect BIM adoption.

Finally, this study provides recommendations containing the essential technological, organizational, environmental and interoperability factors that AEC stakeholders can address to enhance BIM adoption.

To the best of the authors’ knowledge, this paper is one of the first studies to combine TOE and EIF in a single research model. This research provides empirical evidence for using the proposed model as a guide to promoting BIM adoption. As a result, the highlighted determinants can assist organizations in developing and executing successful policies that support BIM adoption in the AEC industry.

This study aims to explore the adoption behaviour of consumers towards innovative technology products and services (ITPS).

A qualitative study using semi-structured in-depth interviews was conducted with 47 respondents. Their lived experiences across 50+ ITPS were studied. A grounded theory approach was used to develop a theory with reference to consumer adoption of ITPS.

Themes emerged across the adoption process, such as triggers for adoption (pressing need, making life more pleasurable, urge to acquire and forced initiation); hesitancies faced by consumers during evaluation (value alignment, utilization, ecosystem, risks with new technology and price); and factors that help in overcoming the hesitancies (word of mouth, de-risking schemes and self-devised strategies).

Innovators must understand customer triggers and design offerings that activate the same – addressing a pressing need or making lives more pleasurable. Users driven purely by an urge to acquire can be a source of early word of mouth for radical innovations. Innovations must be designed and communicated to minimize hesitancies. Mitigating schemes such as equated monthly installment and return policy can be offered to empower customers to overcome hesitancies. Factors such as price, risk, beliefs, traditions and nationalistic values assume importance, specifically in an emerging economy.

This study based on grounded theory keeps the user at the centre and explains the innovation adoption phenomenon for a wide variety of 50+ ITPS in the context of an emerging economy.

This study aims to investigate the factors influencing the adoption of data analytics in performance management. By examining the role of organizational and environmental contexts, this study contributes to the existing literature by proposing a novel and detailed technology-organization-environment (TOE) model for the complex interplay between firm characteristics and the adoption of data analytics. The results offer valuable insights and practical implications for organizations seeking to leverage data analytics for effective performance management.

The research draws upon a data set encompassing over 21,869 companies operating across all European Union member states. A multilevel logistic regression model was developed to evaluate the influence of organizational and environmental factors on the likelihood of adopting performance analytics in organizations.

The findings indicate that the lack of awareness of the benefits of data analytics and its practical application to address specific business challenges is a significant barrier to its adoption. Organizational contexts, such as variable-pay systems, employee training, hierarchical structures and frequency of monetary rewards, also influence the adoption of data analytics.

The study informs managers about the strategic role of data analytics capabilities in performance management for improved business intelligence and driving data culture.

The study helps managers understand the strategic role of data analytics capabilities in performance management, leading to improved business intelligence and fostering a data-driven culture in five key areas: structural alignment, strategic decision-making, resource allocation, performance improvement and change management.

The study advances the TOE theory, making it a more detailed and complete framework, particularly applicable to the adoption of performance analytics. It identifies the main factors of adoption that play a crucial role in this process.

Battery electric vehicles (BEVs) are living up to their claims as consumers choose them more frequently. The increasing demand for sustainable vehicles translates into the global need for specific components, materials, and infrastructures and drives the regulatory frameworks in each country. While BEVs offer environmental benefits and global business opportunities, the technology has not yet gained mainstream acceptance. Thus, this work aims to investigate the characteristics of BEV users and their role in the diffusion of products to larger segments, as this may vary from country to country. For this purpose, a survey based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) (Venkatesh et al., 2012) framework and structural equation modeling (SmartPLS) was adopted. The results indicated that, except for the constructs of effort expectancy (EE) and social influence (SI), the predictors in the model performed well in this context. Current users are satisfied with their vehicles and are supportive of BEVs in the future. The analysis also revealed that in addition to the availability of financial resources, early adopters are attracted by new technologies in a way that leads them to make decisions outside of the traditional influence of the other members of society. It is suggested to leverage the perceived benefits of status, differentiation, or uniqueness motives, to appeal to those seeking to appear trendy and tech-savvy in society. Companies and policymakers should acknowledge the peculiarities of early customers in their communication strategies to reach a wider audience around the globe and encourage the adoption of BEV technology.

This study aims to investigate the influence of specific socioeconomic factors, namely neighborhood, gender roles and affordability, on the continuous use of clean cooking technologies (CCTs) in households, using evidence from Uganda.

This study adopted an explanatory quantitative design. A questionnaire survey with 379 clean household responses was conducted. The data were analyzed using the Smart Partial Least Squares (PLS) software.

The results indicate that the sustained use of clean cooking technologies in households in Uganda is significantly associated with neighborhood influence, shared gender roles and affordability, collectively accounting for 27.7% of the variance.

The three dimensions of socioeconomic factors under study partially explain the sustained use of CCTs in Uganda. The study does not delve into other socioeconomic factors that could probably account for 72.2% of the variance not explained. The quantitative design may have overlooked the social reality perspectives inherent in qualitative studies that other researchers may endeavor to exploit.

The authors integrated three dimensions of socioeconomic factors – neighborhood influence, gender roles and affordability – with the diffusion of innovation theory (DIT) using Smart PLS to explain the continuous use of CCTs within households.

This study aims to investigate the motivations for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Specifically, the effects of relative advantage of the technologies, competitive pressure, and government support on the adoption are explored. Moreover, the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies is examined.

A research model is developed based on the technology-organization-environment (TOE) framework strengthened by institutional theory. Structural equation modeling (SEM) approach is employed to evaluate the model using data obtained from 215 manufacturing firms through a cross-industry survey. Additionally, a post-hoc analysis is conducted using cluster analysis and ANOVA.

The results show that competitive pressure and government support significantly promote top management support, which in turn contributes to the adoption of Industry 4.0 technologies. Relative advantage of the technologies is not significantly related to the adoption.

This study does not explore the relationship between technology type and the specific needs of manufacturing firms. Future researchers can conduct a more comprehensive analysis by examining how different technology types align with the unique needs of individual companies.

The findings of this study have implications for both policymakers and managers. Policymakers can leverage these insights to understand the underlying motivations behind manufacturing firms' adoption of Industry 4.0 technologies and develop promoting policies. In turn, managers should keep an eye on government policies and utilize government support to facilitate technology adoption.

This study uncovers the underlying motivations—government support and competitive pressure—for the adoption of Industry 4.0 technologies among manufacturing firms in developing economies. Meanwhile, it complements previous research by showing the mediating role of top management support between environmental factors (government support and competitive pressure) and the adoption of Industry 4.0 technologies.

The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.

Potential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.

The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.

Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.

At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

Although social media has gained prominence as a communication and marketing tool in various sectors, its adoption and utilization within the construction industry remain relatively underexplored. Therefore, this study fills this gap by evaluating the level of awareness and the extent of adoption of social media within the Nigerian construction industry, shedding light on its current status and potential impact.

This objective was attained via a quantitative research approach that utilized a structured questionnaire to obtain responses from construction professionals such as architects, builders, engineers, quantity surveyors and estate managers. Frequencies and percentages and the mean item score (MIS) were used to analyze the questionnaire responses and assess the overall awareness and adoption of social media among construction professionals. Additionally, the Kruskal–Wallis H-test provided valuable insights into the variations in social media adoption levels among different professional categories within the construction industry.

The results indicate that construction professionals possess a generally high level of awareness regarding various social media platforms. However, despite this awareness, the extent of adoption does not align with the level of awareness, suggesting that adoption rates are not as widespread as anticipated.

The findings of this study underscore the importance of not just awareness but also effective adoption and utilization of social media platforms. While awareness is a crucial first step, construction firms should focus on implementing strategies to encourage greater adoption and integration of these platforms into their daily operations. This can go a long way in bridging the awareness – adoption gap which was revealed in this study.

While the limited existing research on social media in the construction industry has predominantly concentrated on areas such as marketing, addressing the root causes of fatalities, data environment tools and business branding, none have undertaken a thorough evaluation of social media awareness and adoption within the sector. This study fills a critical gap by narrowing its focus to the adoption dynamics and the technology’s potential impact on communication, collaboration and knowledge sharing among construction professionals.

This study aims to investigate the determinant factors as barriers and facilitators of the B2B degree of digital use and customer–brand engagement in travel services by applying technology and behavioral theories.

A face-to-face survey was administered to retail travel agencies offering offline and online services (N = 301). Structural equation modeling using the partial least square method was conducted using Smart PLS 3.0 software to examine the proposed hypotheses in the research model.

The results revealed that the integrated composite model significantly predicts the B2B degree of digital use and brand engagement. The study established that facilitators had positive effects, and barriers negatively impacted the degree of digital use, which positively impacted brand engagement. However, the facilitator perceived cost and barrier lack of critical mass showed the opposite influence. The effects of facilitator customer pressure and barriers, information and communication technology infrastructure problems and security risks were insignificant. The results also established that the buyer firm size moderated the relationships between barriers and facilitators with the degree of digital use.

This study combined technology and behavioral theories to explain the buyer–seller relationship. The expanded framework contributed to understanding B2B digital usages and brand engagement in the seller–intermediary relationship. This study conceptualized firm size as a contingency variable and established its moderating effect. The study defined cost as a formative construct and an organizational factor. The study suggested practical implications for travel agencies and online travel service sellers.