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The purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.

The study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.

The results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.

The robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.

The study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.

It is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.

The purpose of this study is to explore and prioritize the factors that determine the social insurance contribution of unorganized workers.

A two-stage procedure was adopted to recognize and prioritize factors influencing the social insurance participation of unorganized workers: first, crucial factors influencing unorganized workers’ contribution towards social insurance were identified by employing exploratory factor analysis, and in the second phase, the fuzzy analytical hierarchal process was applied to rank the specified criteria and then sub-criteria by assigning weights.

Four broad factors were identified, namely, economic, political, operational and socio-psychological, that significantly influence unorganized workers’ contribution towards social insurance. Later findings revealed that the prime influencer of unorganized workers’ contribution is employment contracts followed by average earnings, delivery of quality services, eligibility and accessibility.

The research findings are feasible as the basic propositions are based on real-world scenario. The identification and ranking of factors have the potential to be used as a checklist for policymakers when designing pension and social insurance for unorganized workers. If it is not possible to consider all, the criteria and sub-criteria assigned upper rank can be given priority to extend pension coverage for a large group of working poor.

The key factors driving social insurance contributions have been highlighted by studying the stakeholders’ perceptions at a micro level. By comprehending the challenges, there is a possibility of covering a large section of the working poor into social insurance coverage.

This paper is believed to be one of its kinds to acknowledge a combination of factors that determine the contribution of unorganized workers to social insurance. This study is an empirical investigation to prioritize the essential drivers of social insurance participation by low-income cohorts in the context of emerging countries. The present approach of employing fuzzy logic has also very limited use in social insurance literature yet.

This paper aims to explore the risk and benefit perceptions influencing beer patrons’ purchase and consumption decisions in India. It delves into the drivers behind consumers’ consumption patterns and attitudes towards beer, which subsequently impact their behavioural intentions, including word-of-mouth recommendations and repurchase intentions.

The study uses a structured questionnaire to collect data from 306 beer patrons in Delhi and the National Capital Region. Through exploratory factor analysis and structural equation modelling, the research examines the risk (5) and benefit (3) factors associated with beer consumption using a factor model consisting of 29 constructs. A conceptual framework illustrates the interrelationships between variables, which are subsequently validated empirically.

The findings reveal that patrons’ attitudes towards beer are influenced by their perceptions of risk and benefit. Specifically, health and socio-psychological risks are identified as the most significant and negatively impacting factors on patrons’ attitudes. Factorial analysis demonstrates that patrons’ attitudes towards beer are positively influenced by their perception of benefits such as value for money, sensory appeal and convenience. Furthermore, the study highlights that an increase in benefit perception or a decrease in risk perception leads to a favourable shift in patrons’ attitudes towards beer.

To the best of the authors’ knowledge, this study will be the first to investigate how beer consumers’ consumption patterns and purchase decisions are impacted by assessing consumer risk and benefit perceptions. This study will also aid stakeholders in tailoring their beer offerings better to meet the desires and requirements of their customers.

This paper aims to investigate the impact of online identity orientation and online friendship homophily on online socializing, online information search and ethnic guests’ hospitality experiences.

The study uses structural equation modeling to test a conceptual model developed after reviewing hospitality literature. Data is collected from a sample of 514 Turkish-Dutch ethnic guests living in the Netherlands using a self-administered questionnaire.

The results show that online identity orientations aligned with minority and majority cultures impact online friendship homophily and online socializing, which subsequently impact online information search and hospitality experiences of ethnic guests.

On the whole, ethnic communities have considerable spending power. The findings point to heritage and mainstream cultural socialization accounting for travel and hospitality experiences within an ethnic minority group. The findings supply relevant information for hospitality sectors on services to endorse or promote to guests from ethnic communities.

The study examines the simultaneous effects of online identity orientations and online friendship homophily on online socialization and hospitality experiences of ethnic guests. It highlights the role of culture in explaining the use of social networking sites and its potential impact on hospitality-related behaviors and experiences of ethnic guest consumers.

Megaproject's construction is essential for the development and economic growth of any country, especially in the developing world. In Kuwait, megaprojects are facing many restrictions that discourage their execution causing a significant delay in bidding, design, construction and operation phases with the execution quality being affected. The objective of this study is to develop a complexity measurement model using analytic hierarchy process (AHP) for megaprojects in Kuwait, with a focus on the New Kuwait University multi-billion campus Shadadiyah (College of Social Science, Sharia and Law (CSSL)) as a case study.

The study applies a hybrid fuzzy analytic hierarchy process (FAHP) method to compare the results with those obtained using the conventional AHP method. This can facilitate the project management activities during the different stages of construction. Data were collected based on the results of a two-round Delphi questionnaire completed by seniors and experts of the selected project.

It was found that project modeling methodology was responsible for complexity. It was grouped under several categories that include technological, goal, organizational, environmental and cultural complexities. The study compares complexity degrees assessed by AHP and FAHP methods. “Technological Complexity” scores highest in both methods, with FAHP reaching 7.46. “Goal Complexity” follows closely behind, with FAHP. “Cultural Complexity” ranks third, differing between methods, while “Organizational” and “Environmental Complexity” consistently score lower, with FAHP values slightly higher. These results show varying complexity levels across dimensions. Assessing and understanding such complexities were essential toward the completion of such megaprojects.

The contribution of this study is on providing the empirical evidential knowledge for the priority over construction complexities in a developing country (Kuwait) in the Middle East.

This paper investigates the interactional relationships between sustainable human resource management (SHRM) and organizational performance (OP). Sustainable HRM is an approach that links HRM and sustainability. These studies focused on integrating HR with sustainable developments, such as economic and social aspects, in favour of focusing on the environmental aspect. Organizational change is an ongoing process that has to be managed effectively to keep the change in place for a long time.

A framework was offered to estimate the cause-and-effect relation of the SHRM and OP factors. Data is gathered from professionals from various pharmaceutical industries. This study applied two methods, Fuzzy AHP and DEMATEL Type II. These techniques are used to understand the cause-and-effect factors and their interactions.

It was observed from the findings that the factor of SHRM, such as Social Justice (F2), Green Job Design (F5), Green Training (F6) and Implementation of Green Policy (F8), was the most critical for the pharmaceutical sector that effects Financial performance (F13), Customer Satisfaction (F15) and Market performance (F14). Pharmaceutical firms ought to coordinate public health advocacy efforts, engage in healthcare initiatives and provide financial support for environmentally friendly efforts that improve social and economic conditions.

For this sustainability, managers concentrate on creating an environment that is healthy and acceptable, and they work hard to mitigate the impact of natural factors and repair damage done to the environment; it is essential to move towards sustainable development to resolve environmental problems. Improving HR efficiency is among essential HRM responsibilities, as they expand the knowledge base of the workforce, enhance human capital, and eventually create valuable intangible assets and promote and encourage sustainable pharmaceutical products for some years.

This research paper has presented exclusive worth to the SHRM and organizational performance literature as it employs fuzzy FAHP and DEMATEL type 2. There is less research on SHRM in the pharmaceutical sector with these factors. In addition, FAHP and TYPE 2 DEMATEL are used in very few researches on SHRM approaches.

This study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) and cloud computing (CC) in Gujarat, India’s building sector.

From the previous studies, 25 significant factors were identified, and a questionnaire survey with personal interviews obtained 120 responses from building experts in Gujarat, India. The questionnaire survey data’s validity, reliability and descriptive statistics were also assessed. Building experts’ opinions are inputted into the CFPR method, and priority weights and ratings for probable outcomes are obtained to forecast success and failure.

The findings demonstrate that the most important factors are affordable system and ease of use and battery life and size of sensors, whereas less important ones include poor collaboration between IoT and cloud developer community and building sector and suitable location. The forecasting values demonstrate that the factor suitable location has a high probability of success; however, factors such as loss of jobs and data governance have a high probability of failure. Based on the forecasted values, the probability of success (0.6420) is almost twice that of failure (0.3580). It shows that deploying IoT and CC in the building sector of Gujarat, India, is very much feasible.

Previous studies analysed IoT and CC factors using different multi-criteria decision-making (MCDM) methods to merely prioritise ranking in the building sector, but forecasting success/failure makes this study unique. This research is generally applicable, and its findings may be utilised for decision-making and deployment of IoT and CC in the building sector anywhere globally.

This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics.

This study gathers a large Twitter dataset comprising political discussions across various topics from general users. It utilizes an unsupervised machine learning algorithm with pre-defined language features to detect language styles in political discussions on Twitter. Furthermore, it employs a multinomial model to explore the relationships between language styles and users' online characteristics.

Through the analysis of over 700,000 political tweets, this study identifies six language styles: mobilizing, self-expressive, argumentative, narrative, analytic and informational. Furthermore, by investigating the covariation between language styles and users' online characteristics, such as social connections, expressive desires and gender, this study reveals a preference for an informational style and an aversion to an argumentative style in political discussions. It also uncovers gender differences in language styles, with women being more likely to belong to the mobilizing group but less likely to belong to the analytic and informational groups.

This study provides insights into the psychological mechanisms and social statuses of users who adopt particular language styles. It assists political communicators in understanding their audience and tailoring their language to suit specific contexts and communication objectives.

This study reveals gender differences in language styles, suggesting that women may have a heightened desire for social support in political discussions. It highlights that traditional gender disparities in politics might persist in online public spaces.

This study develops a computational methodology by combining cluster analysis with pre-defined linguistic features to categorize language styles. This approach integrates statistical algorithms with communication and linguistic theories, providing researchers with an unsupervised method for analyzing textual data. It focuses on detecting language styles rather than topics or themes in the text, complementing widely used text classification methods such as topic modeling. Additionally, this study explores the associations between language styles and the online characteristics of social media users in a political context.

The purpose of this study is to investigate the reasons behind the persistent preference for printed content among Arabic-speaking library patrons in Jordan. Specifically, this study highlights the availability of reading materials in print, electronic and audible formats in Arabic as an intervening factor shaping reading behavior. More broadly, it aims to contribute to a deeper understanding of how language preference can impact reading format preferences.

This study’s research design revolves around understanding reading format preferences among registered members of Jordan’s largest and oldest private library. This approach involved the examination of secondary library user survey data collected from N = 313 of its patrons in 2022. To gain a greater understanding of the preference for printed materials, this study conducted semistructured interviews over the phone with n = 31 participants of the library’s survey.

The findings of this study indicate a strong preference for print books among Arabic-speaking library patrons in Jordan. However, the availability of content in electronic and audible formats in Arabic, their preferred reading language, emerged as a potentially significant factor in the persistent preference for printed reading materials.

This study offers new insights into the specific role that the availability of content in Arabic, and possibly languages other than English, may play in shaping reading format preferences. By shedding light on this aspect of reading behavior, this research offers valuable information for libraries and publishers seeking to cater to the needs and preferences of Arabic readers.

Drawing on the resource-based view, ecological modernization theory and upper-echelon theory, this study aims to explore how green manufacturing practices (GMGP) affect the sustainable performance of small and medium enterprises (SMEs).

It also examines the mediating role of green innovation (GIN) and the moderating role of managerial discretion (MD). To test the hypothesized model, the data was collected from 394 manufacturing SMEs though survey and analyzed using SPSS and AMOS (SEM).

The results provide evidence for the positive relationship between GMGP and corporate sustainable performance (CSPR), mediated by GIN. Furthermore, the presence of MD enhances the positive effect of GMGP on CSPR through GIN. Thus, this study enhances the understanding of the relationship between GMGP and CSPR, including its underlying mechanism and conditional effects.

This study collected sample from SMEs located in Punjab province of Pakistan which represents majority of the SMEs; however, future research can take data from other province and with large sample size.

The findings highlight the significance of GMGP and GIN in the manufacturing sector for attaining CSPR goals. GMGP guides business leaders to be more inclined toward the energy and resource consumption as well as waste generation within their organizations which lead to improved CSPR outcomes.

The findings of this study make significant contributions to the existing literature, shedding light on the dynamics between GMGP and CSPR. Moreover, the study offers managerial implications for organizations aiming to enhance their sustainable performance by implementing effective GMGP.