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Manufacturing companies continue to encounter a diverse set of obstacles while embracing sustainable development goals. Accordingly, the purpose of this study is to explore critical sustainable development-related barriers to flexible packaging manufacturing companies in the New Zealand context.

Drawing on a qualitative multiple case studies approach, the authors collected data from the New Zealand flexible packaging industry. Semistructured interviews were conducted with the senior corporate managers in two large flexible packaging companies. Following the thematic analysis approach, the authors analyzed the information collected from the participants and synthesized our findings under the key dimensions of internal and external barriers to sustainable development.

The findings revealed that internal barriers to sustainable flexible packaging are linked to economic, operational and technical issues. Conversely, external barriers include global crises and disruption, customer behavior and preferences and institutional and infrastructural-related aspects. Based on the analysis of empirical findings, the authors further identified the underlying reasons for sustainable flexible packaging barriers and recommended guidelines that could assist corporate managers and policymakers in addressing obstacles inhibiting the flexible packaging industry from adopting sustainable business practices.

The authors argue that this study is one of the early studies to consider inhibiting factors to incorporate sustainable development into the New Zealand flexible packaging industry context. Building on a range of theoretical perspectives, the authors extend the current body of knowledge seeking to advance the sustainable development agenda in the New Zealand flexible packaging industry and offer recommended pathways fostering sustainable development in a distinctive manufacturing context.

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by incorporating Industry 4.0 technological innovations into existing quality management frameworks, signifying a significant evolution in quality control systems. Despite the evident advantages, the practical deployment in the Indian manufacturing sector encounters various obstacles. This research is dedicated to a thorough examination of these impediments. It is structured around a set of pivotal research questions: First, it seeks to identify the key barriers that impede the adoption of Quality 4.0. Second, it aims to elucidate these barriers' interrelations and mutual dependencies. Thirdly, the research prioritizes these barriers in terms of their significance to the adoption process. Finally, it contemplates the ramifications of these priorities for the strategic advancement of manufacturing practices and the development of informed policies. By answering these questions, the research provides a detailed understanding of the challenges faced. It offers actionable insights for practitioners and policymakers implementing Quality 4.0 in the Indian manufacturing sector.

Employing Interpretive Structural Modelling and Matrix Impact of Cross Multiplication Applied to Classification, the authors probe the interdependencies amongst fourteen identified barriers inhibiting Quality 4.0 adoption. These barriers were categorized according to their driving power and dependence, providing a richer understanding of the dynamic obstacles within the Technology–Organization–Environment (TOE) framework.

The study results highlight the lack of Quality 4.0 standards and Big Data Analytics (BDA) tools as fundamental obstacles to integrating Quality 4.0 within the Indian manufacturing sector. Additionally, the study results contravene dominant academic narratives, suggesting that the cumulative impact of organizational barriers is marginal, contrary to theoretical postulations emphasizing their central significance in Quality 4.0 assimilation.

This research provides concrete strategies, such as developing a collaborative platform for sharing best practices in Quality 4.0 standards, which fosters a synergistic relationship between organizations and policymakers, for instance, by creating a joint task force, comprised of industry leaders and regulatory bodies, dedicated to formulating and disseminating comprehensive guidelines for Quality 4.0 adoption. This initiative could lead to establishing industry-wide standards, benefiting from the pooled expertise of diverse stakeholders. Additionally, the study underscores the necessity for robust, standardized Big Data Analytics tools specifically designed to meet the Quality 4.0 criteria, which can be developed through public-private partnerships. These tools would facilitate the seamless integration of Quality 4.0 processes, demonstrating a direct route for overcoming the barriers of inadequate standards.

This research delineates specific obstacles to Quality 4.0 adoption by applying the TOE framework, detailing how these barriers interact with and influence each other, particularly highlighting the previously overlooked environmental factors. The analysis reveals a critical interdependence between “lack of standards for Quality 4.0” and “lack of standardized BDA tools and solutions,” providing nuanced insights into their conjoined effect on stalling progress in this field. Moreover, the study contributes to the theoretical body of knowledge by mapping out these novel impediments, offering a more comprehensive understanding of the challenges faced in adopting Quality 4.0.

There is a growing body of literature discussing the green logistics practices (GLPs) that companies could introduce to reduce the logistics environmental impact. Current approaches also identify several influencing factors within firms that could serve as barriers to, or enablers of, GLPs. However, less is known about the role of extra-firm stakeholders, even though these are crucial to operationalizing green logistics effectively. This study merges current theoretical understanding with empirical evidence to provide a detailed stakeholder analysis of GLPs.

Using stakeholder theory as a theoretical lens, the authors aimed at offering a mid-range contribution by conducting multiple embedded case studies examining Italian logistics service providers and shippers. GLPs and the related influencing factors were examined as sub-units of analysis within broader companies' environmental sustainability strategies.

The authors identified cascading effects among factors influencing the adoption of GLPs (e.g. key economic factors are affected by external factors which also influence organizational and collaboration factors). These effects are moderated by interdependencies between primary and secondary stakeholders, and the study highlights the prominent involvement of secondary stakeholders, such as final consumers.

This paper contributes to better understanding how and why companies adopt GLPs, emphasizing the wide set of stakeholders involved and illustrating how different stakeholders impact on GLPs adoption by affecting a set of influencing factors. By combining insights from the available literature with contemporary empirical data, the authors emphasize how Logistics Service Providers (LSPs) and shippers can no longer address the adoption of GLPs as “focal companies”, but only as part of a “focal network of interconnected stakeholders”, all of them influencing GLPs adoption.

This study investigates the integration of Industry 4.0 (I4.0) technologies with condition-based maintenance (CBM) in upstream oil and gas (O&G) operations, focussing on developing countries like Nigeria. The research identifies barriers to this integration and suggests solutions, intending to provide practical insights for improving operational efficiency in the O&G sector.

The study commenced with an exhaustive review of extant literature to identify existing barriers to I4.0 implementation and contextualise the study. Subsequent to this foundational step, primary data are gathered through the administration of carefully constructed questionnaires targeted at professionals specialised in maintenance within the upstream O&G sector. A semi-structured interview was also conducted to elicit more nuanced, contextual insights from these professionals. Analytically, the collected data were subjected to descriptive statistical methods for summarisation and interpretation with a measurement model to define the relationships between observed variables and latent construct. Moreover, the Relative Importance Index was utilised to systematically prioritise and rank the key barriers to I4.0 integration to CBM within the upstream O&G upstream sector.

The most ranked obstacles in integrating I4.0 technologies to the CBM strategy in the O&G industry are lack of budget and finance, limited engineering and technological resources, lack of support from executives and leaders of the organisations and lack of competence. Even though the journey of digitalisation has commenced in the O&G industry, there are limited studies in this area.

The study serves as both an academic cornerstone and a practical guide for the operational integration of I4.0 technologies within Nigeria's O&G upstream sector. Specifically, it provides an exhaustive analysis of the obstacles impeding effective incorporation into CBM practices. Additionally, the study contributes actionable insights for industry stakeholders to enhance overall performance and achieve key performance indices (KPIs).

This study aims to identify and analyse critical barriers to cloud manufacturing (CM) adoption for achieving sustainability amongst manufacturing micro, small and medium-sized enterprises (MSMEs) in an emerging economy.

Initially, through a literature survey and expert inputs, this study identified and finalized 21 critical barriers to CM adoption, which were further analysed by employing a hybrid multiple criteria decision-making (MCDM) approach. In this approach, the best–worst method (BWM) was used to rank the identified barriers. However, to analyse the interrelation amongst these barriers and classify them into the cause-effect group, the decision-making trial and evaluation laboratory (DEMATEL) method was employed. Furthermore, the study recommended various strategies that can help overcome high-priority barriers and enhance CM adoption within firms.

The results of the study show that organizational, legal and economic barriers are the high-priority barriers that need to be addressed to enhance CM adoption.

The findings of the study will help managers and decision-makers in manufacturing MSMEs develop effective strategies and policies to enhance CM adoption.

Notably, this investigation is one of the preliminary research activities to explore the sustainability aspect of CM adoption amongst MSMEs in an emerging economy.

This research aims to explore whether or how organizations adopt people analytics (PA), its value and potential socio-technical factors that can enable or hinder PA projects by disrupting and reshaping human resource management. We do this by focusing on the Italian context.

We conduct a scoping review of data collected between 2018 and 2022 via Google Alerts (GA), a content change detection and notification service that is gaining popularity in scholarly research.

Our findings suggest that the diffusion of PA applications in Italy, especially those of a descriptive nature, is growing. Most of the existing PA applications are positioned in a positive technocratic light, envisioning the value of PA for both employees and organizations. The value for the latter appears to be direct, while the value for employees is realized through organizational initiatives. The findings also suggest that while enablers can vary between PA application types, the barriers, especially technological and environmental, are generic for both descriptive and predictive/prescriptive PA applications.

Theoretically, we propose a framework for analyzing PA applications, their values, enablers and barriers. Methodologically, we present and describe in detail a novel approach, drawing on GA that can be used to study PA in specific contexts. Practically, our study serves as a helpful point of reference for managers planning or implementing PA in Italy, for benchmarking PA in Italy over time and for comparative international studies.

The aim of this paper is to explore how multi-national corporations (MNCs) can effectively adopt artificial intelligence (AI) into their talent acquisition (TA) practices. While the potential of AI to address emerging challenges, such as talent shortages and applicant surges in specific regions, has been anecdotally highlighted, there is limited empirical evidence regarding its effective deployment and adoption in TA. As a result, this paper endeavors to develop a theoretical model that delineates the motives, barriers, procedural steps and critical factors that can aid in the effective adoption of AI in TA within MNCs.

Given the scant empirical literature on our research objective, we utilized a qualitative methodology, encompassing a multiple-case study (consisting of 19 cases across seven industries) and a grounded theory approach.

Our proposed framework, termed the Framework on Effective Adoption of AI in TA, contextualizes the motives, barriers, procedural steps and critical success factors essential for the effective adoption of AI in TA.

This paper contributes to literature on effective adoption of AI in TA and adoption theory.

Additionally, it provides guidance to TA managers seeking effective AI implementation and adoption strategies, especially in the face of emerging challenges.

To the best of the authors' knowledge, this study is unparalleled, being both grounded in theory and based on an expansive dataset that spans firms from various regions and industries. The research delves deeply into corporations' underlying motives and processes concerning the effective adoption of AI in TA.

The current environment is unhelpful to female entrepreneurs, and they need to overcome numerous barriers when starting their own businesses. In this study, the researchers investigated the significant barriers that Pakistani female entrepreneurs require to overcome in this respect.

In this study, the researchers used a quantitative study and they used a questionnaire to survey the respondents and collect cross-sectional data. The researchers targeted female students who were undertaking bachelor’s and master’s degree programs in different Pakistani public and private sector universities. Accordingly, the researchers based this study’s findings on the usable samples received from 498 Pakistani female students.

The researchers used a structural equation model (SEM) in this study and its findings highlight that aversion to risk (ATR) has an insignificant impact on entrepreneurial inclinations (EI). In addition, fear of failure (FoF), lack of resources (LoR), aversion to hard work and stress (ASH) and the lack of social networking (LSN) have negative and insignificant effects on EI. The ATR factor has an insignificant effect on entrepreneurial success (ES), whereas FoF, LoR, ASH and LSN are negative and insignificant predictors of Pakistani female students’ ES.

This study’s findings may help Pakistani women to overcome the barriers to ES. In this respect, the researchers recommend that the Pakistan Government and policymakers develop significant strategies to provide the conducive business environment and to financially support Pakistani women to start their own businesses. Furthermore, this study’s findings contribute greatly to the vast amount of current literature and help to overcome the entrepreneurial conditions and barriers that potential entrepreneurs from advanced and developing countries experience frequently.

This study’s findings provide empirical evidence of EI and ES in Pakistan.

The purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within the logistics industry. In addition, the moderating effect that the risk factor has on the technological, environmental and organizational factors regarding the implementation of IoT in logistics.

For the purpose of testing the models and hypotheses, a survey was carried out in order to collect the responses from currently employed individuals at various companies working in the field of logistics or IoT. For the purpose of analysis, the authors made use of the partial least squares structure equation model (PLS-SEM) technique.

Findings of this study concluded that technology- and environmental-related factors significantly affect the adoption of IoT in logistics, while risk acts as a moderator for the technological-related factor only in the adoption of IoT in logistics.

The relevance of the authors' study lies in the growing importance of IoT in logistics and the need for logistics companies to understand the factors that impact the adoption of IoT in their operations. By identifying and analyzing the factors that influence IoT adoption in logistics, the authors' study provides valuable insights that can help logistics companies make informed decisions about whether and how to adopt IoT.

The research will help organizations make strategies for the successful adoption of IoT and ease the lives of all the stakeholders.

In this research, the authors attempted to find the factors that influence the adoption of IoT in logistics management. The influence of the technological, environmental, organizational and risk-related factors on the adoption of IoT in logistics management was studied. The moderating effect of risk over these factors on the adoption of IoT in logistics was also analyzed. This is original work and has never been done earlier.

The aim of this study is to identify the travel constraints of people with special needs (PwSN) and the strategies used to overcome them. The article also intends to analyze the differences in travel constraints and negotiation strategies according to the type of disability and/or special need.

A qualitative study was conducted in which a sample of PwSN (people with disabilities – mobility, sensory and cognitive – seniors and people with food allergies) were interviewed in depth.

PwSN face a wide range of constraints when engaging in tourism activities. These constraints are very diverse and influence people with different intensity and have to be overcome using different negotiation strategies. However, differences in the constraints were observed according to the type of special needs.

One of the most significant practical implications of this research is the need for raising awareness regarding human diversity among tourism stakeholders. It is critical to link sectoral policies that are reflected in the social and business reality, creating public–private partnerships to raise the sharing of knowledge, equipment and services. By addressing the constraints that prevent PwSN from traveling, the tourism sector can create more opportunities for them to participate in social activities, improving their quality of life and contributing to a more sustainable and inclusive industry.

Traveling can present significant challenges for people with special needs, which affect the quality of their tourism experience. Despite growing academic attention to this issue in recent years, research in this field has primarily focused on specific aspects of disability. This study seeks not only to identify the barriers to travel faced by people with different special needs but also to explore the negotiation strategies used to overcome these barriers and the differences according to the type of special need.